Electrical and Electronics Engineering publications abstract of: 02-2018 sorted by title, page: 13

» Joint Interference Mitigation and Data Recovery for Massive Carrier Aggregation via Non-Linear Compressive Sensing
Abstract:
Due to the demand for higher throughput, there is need for aggregating more carriers to serve one user equipment. Massive carrier aggregation (MCA) may help as it aggregates a large number of potentially non-contiguous carriers spanning a wide bandwidth. However, implementing MCA brings challenges to the design of the receiver and corresponding data recovery algorithms. For example, if we assign a separate receiver chain for each carrier, the number of receiver chains will be large, which imposes a huge cost. If we use a single receiver chain for all non-contiguous carriers, an expensive high rate analog-to-digital converter (ADC) is required to sample the entire span of the carriers. To reduce the cost, we propose a receiver architecture that employs only one receiver chain with a non-uniform ADC, whose sampling rate is much smaller than the Nyquist rate, and a low cost power amplifier with small dynamic range. Under such architecture, the received signal suffers from non-linear distortion and interference, and the resulting data recovery is a challenging non-linear compressive sensing problem. We propose an algorithm to jointly mitigate the interference and recover the data, which is proved to have theoretical performance guarantees and verified advantageous over baselines in simulations.
Autors: Feibai Zhu;An Liu;Vincent K. N. Lau;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1389 - 1404
Publisher: IEEE
 
» Joint Listening, Probing, and Transmission Strategies for the Frame-Based Equipment in Unlicensed Spectrum
Abstract:
The recent efforts of extending cellular technologies to unlicensed spectrum have led to concerns about the coexistence between cellular and incumbent systems. To harmonize coexistence, regions including European Union and Japan require that a radio equipment operating in unlicensed spectrum shall perform listen-before-talk (LBT). In this paper, we study joint listening, probing, and transmission strategies for a frame-based equipment (FBE) in unlicensed spectrum. We first investigate throughput optimal strategy and find that the optimal rule for an FBE is to transmit whenever allowed by the regulation. We then turn to nominal throughput optimal transmission that takes into account transmission costs such as power consumption. We find that the nominal throughput optimal rule is a pure threshold policy: The FBE should stop listening and transmit once the channel quality exceeds an optimized threshold. The optimal threshold can be found by solving a fixed point equation, but the fixed point equation in general does not admit a closed-form solution. We then derive a lower bound and an upper bound on the optimal threshold. We further devise an iterative algorithm with convergence analysis to compute the optimal threshold. Our results shed further light on LBT strategies for radio equipment operating in unlicensed spectrum.
Autors: Ning Wei;Xingqin Lin;Youzhi Xiong;Zhi Chen;Zhongpei Zhang;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1750 - 1764
Publisher: IEEE
 
» Joint Optimization of Multicast Energy in Delay-Constrained Mobile Wireless Networks
Abstract:
This paper studies the problem of optimizing multicast energy consumption in delay-constrained mobile wireless networks, where information from the source needs to be delivered to all the destinations within an imposed delay constraint. Most existing works simply focus on deriving transmission schemes with the minimum transmitting energy, overlooking the energy consumption at the receiver side. Therefore, in this paper, we propose ConMap, a novel and general framework for efficient transmission scheme design that jointly optimizes both the transmitting and receiving energy. In doing so, we formulate our problem of designing minimum energy transmission scheme, called DeMEM, as a combinatorial optimization one, and prove that the approximation ratio of any polynomial time algorithm for DeMEM cannot be better than . Aiming to provide more efficient approximation schemes, the proposed ConMap first converts DeMEM into an equivalent directed Steiner tree problem through creating auxiliary graph gadgets to capture energy consumption, then maps the computed tree back into a transmission scheme. The advantages of ConMap are threefolded: 1) Generality– ConMap exhibits strong applicability to a wide range of energy models; 2) Flexibility– Any algorithm designed for the problem of directed Steiner tree can be embedded into our ConMap framework to achieve different performance guarantees and complexities; 3) Efficiency– ConMap preserves the approximation ratio of the embedded Steiner tree algorithm, to which only slight overhead will be incurred. The three features are then empirically validated, with ConMap also yielding near-optimal transmission schemes compared to a brute-force exact algorithm. To o- r best knowledge, this is the first work that jointly considers both the transmitting and receiving energy in the design of multicast transmission schemes in mobile wireless networks.
Autors: Luoyi Fu;Xinzhe Fu;Zesen Zhang;Zhiying Xu;Xudong Wu;Xinbing Wang;Songwu Lu;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Feb 2018, volume: 26, issue:1, pages: 633 - 646
Publisher: IEEE
 
» Joint Relay Beamforming and Receiver Processing for Multi-Way Multi-Antenna Relay Networks
Abstract:
We consider a multi-way relay network with multiple users exchanging information with each other via a multi-antenna relay. The multi-way relaying strategy consists of one multiple access phase and multiple broadcast phases. We jointly design relay beamforming matrices and users’ linear processing receivers in the broadcast phases to maximize the minimum signal-to-interference-and-noise ratio (SINR) under the relay power budget. For the non-convex joint optimization problem, we propose to solve it by iteratively optimizing the relay beam matrices and receiver processing matrices in two sub-problems. For the receiver processing, both maximum-ratio-combining (MRC) receiver and zero-forcing (ZF) receiver are designed. We show that our iterative approach with the MRC receiver leads to a local maximum for the original joint optimization problem, while the ZF receiver has the computational advantage with a lower complexity. To further improve the performance, we design the successive interference cancellation at each user’s receiver based on the SINR criterion to sequentially decode symbols from other users. Simulation shows that our proposed algorithm for joint design provides substantial improvement in the sum rate than the existing methods that use the sum rate as the design objective. Finally, we investigate the performance of our proposed algorithm under partial channel state informations (CSIs). We show in simulation that using quantized CSIs at each receiver only incurs a small performance loss for the typical range of relay channel quality.
Autors: Wen Li;Min Dong;
Appeared in: IEEE Transactions on Communications
Publication date: Feb 2018, volume: 66, issue:2, pages: 576 - 588
Publisher: IEEE
 
» Joint Resource Allocation for Software-Defined Networking, Caching, and Computing
Abstract:
Although some excellent works have been done on networking, caching, and computing, these three important areas have traditionally been addressed separately in the literature. In this paper, we describe the recent advances in jointing networking, caching, and computing and present a novel integrated framework: software-defined networking, caching, and computing (SD-NCC). SD-NCC enables dynamic orchestration of networking, caching, and computing resources to efficiently meet the requirements of different applications and improve the end-to-end system performance. Energy consumption is considered as an important factor when performing resource placement in this paper. Specifically, we study the joint caching, computing, and bandwidth resource allocation for SD-NCC and formulate it as an optimization problem. In addition, to reduce computational complexity and signaling overhead, we propose a distributed algorithm to solve the formulated problem, based on recent advances in alternating direction method of multipliers (ADMM), in which different network nodes only need to solve their own problems without exchange of caching/computing decisions with fast convergence rate. Simulation results show the effectiveness of our proposed framework and ADMM-based algorithm with different system parameters.
Autors: Qingxia Chen;F. Richard Yu;Tao Huang;Renchao Xie;Jiang Liu;Yunjie Liu;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Feb 2018, volume: 26, issue:1, pages: 274 - 287
Publisher: IEEE
 
» Joint Sensing Duration Adaptation, User Matching, and Power Allocation for Cognitive OFDM-NOMA Systems
Abstract:
In this paper, the non-orthogonal multiple access (NOMA) technology is integrated into cognitive orthogonal frequency-division multiplexing (OFDM) systems, called cognitive OFDM-NOMA, to boost the system capacity. First, a capacity maximization problem is considered in half-duplex cognitive OFDM-NOMA systems with two accessible users on each subcarrier. Due to the intractability of the considered problem, we decompose it into three subproblems, i.e., the optimization of, respectively, sensing duration, user scheduling, and power allocation. By investigating and exploiting the characteristics of each subproblem, the optimal sensing duration adaptation, a matching-theory-based user scheduling, and the optimal power allocation are proposed correspondingly. An alternate iteration framework is further proposed to jointly optimize these three subproblems, with its convergence proved. Moreover, based on the non-cooperative game theory, a generalized power allocation algorithm is proposed and then used in the framework to accommodate half-duplex cognitive OFDM-NOMA systems with multiple users on each subcarrier. Finally, the proposed framework is extended to solve the capacity maximization problem in full-duplex cognitive OFDM-NOMA systems. Simulation results validate the superior performance of the proposed algorithms. For example, for the case of two accessible users, the proposed framework approaches the optimal solution with less than 1% capacity loss and 120 times lower complexity compared with exhaustive search.
Autors: Wenjun Xu;Xue Li;Chia-Han Lee;Miao Pan;Zhiyong Feng;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1269 - 1282
Publisher: IEEE
 
» Joint Synchronization and Channel Estimation of ACO-OFDM Systems With Simplified Transceiver
Abstract:
To facilitate the development of asymmetrically clipped optical orthogonal frequency division multiplexing systems, a joint synchronization and channel estimation scheme is proposed. The preamble used in the scheme is based on zero correlation code pair and has impulse-like correlation relationship. This property can let the results of synchronization process be the coarsely estimated channel time response, thus simplifies channel frequency response generation. Also, a transceiver with low complexity is proposed. The proposed transceiver needs only half the amount of multiplications compared with conventional transceiver. Simulation results reveal that the proposed scheme achieves better performance both in synchronization and channel estimation than existing schemes.
Autors: Xuewen Qian;Honggui Deng;Hailang He;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 383 - 386
Publisher: IEEE
 
» Ka-Band Dual-Frequency Single-Slot Antenna Based on Substrate Integrated Waveguide
Abstract:
This letter presents a novel dual-frequency single-slot antenna in Ka-band based on a substrate integrated waveguide (SIW). From the view of an SIW resonator, the single-slot cuts currents of the TE101 and TE102 mode in two frequencies, respectively, which leads to a dual-frequency performance. In addition, the difference between two resonance frequencies may be tuned by varying the length of the SIW, which changes the resonant frequencies of the two modes. Three antennas operating from 25.3 to 30.7 GHz with gain greater than 6 dBi are designed and fabricated. Simulated and measured results of the antennas are presented as well. The results show that the proposed antennas achieve stable tunable dual-frequency performance, which may be applied to a Ka-band communication system.
Autors: Wan Jiang;Kama Huang;Changjun Liu;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Feb 2018, volume: 17, issue:2, pages: 221 - 224
Publisher: IEEE
 
» KID Model-Driven Things-Edge-Cloud Computing Paradigm for Traffic Data as a Service
Abstract:
The development of intelligent traffic systems can benefit from the pervasiveness of IoT technologies. In recent years, increasing numbers of devices are connected to the IoT, and new kinds of heterogeneous data sources have been generated. This leads to traffic systems that exist in extended dimensions of data space. Although cloud computing can provide essential services that reduce the computational load on IoT devices, it has its limitations: high network bandwidth consumption, high latency, and high privacy risks. To alleviate these problems, edge computing has emerged to reduce the computational load for achieving TDaaS in a dynamic way. However, how to drive all edge servers' work and meet data service requirements is still a key issue. To address this challenge, this article proposes a novel three-level transparency-of-traffic-data service framework, that is, a KID-driven TEC computing paradigm. Its aim is to enable edge servers to cooperatively work with a cloud server. A case study is presented to demonstrate the feasibility of the proposed new computing paradigm with associated mechanisms. The performance of the proposed system is also compared to other methods.
Autors: Bowen Du;Runhe Huang;Zhipu Xie;Jianhua Ma;Weifeng Lv;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 34 - 41
Publisher: IEEE
 
» Kinematic Accuracy Improvement of a Novel Smart Structure-Based Parallel Kinematic Machine
Abstract:
The complex structure of the parallel kinematic machine (PKM) challenges its high kinematic accuracy. An innovative smart structure-based PKM design method was generated in our previous work as a possible solution to improve its accuracy, wherein a prototype was successfully developed. This paper mainly examined the theoretical and technique methods to improve the kinematic accuracy of the novel smart structure-based PKM to promote its practical application. The developed smart structure-based PKM was first introduced and the procedure of improving its kinematic accuracy was presented. The kinematic error model of this PKM was then established by considering the kinematic property of the machine. Due to the special structure of the smart structure-based PKM, several key preparations, including the installation of the grid encoder, the origin returning of the smart structure chains, and the automatic measurement of the motion information, were performed for kinematic accuracy improvement. On this basis, the PKM's kinematic accuracy was improved by the kinematic calibration method and the smart structure chains. The regularization method was employed to deal with the ill-conditioning problem in the error identification of the PKM, thereby reducing the maximum positioning error of the smart structure-based PKM from 300 to 25 μm through error compensation. An experimental test was performed to verify the existence of nonlinear geometric errors in the actual PKM. A regional error identification and compensation method was proposed to reduce their effects on the result of the kinematic calibration. Finally, the smart structure chains were controlled to further improve the PKM's kinematic accuracy. The experimental results indicated that the smart structure-based PKM achieved micron-level positioning accuracy in its whole workspace by following the proposed kinematic accuracy impr- vement process.
Autors: Yao Jiang;Tiemin Li;Liping Wang;Feifan Chen;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 469 - 481
Publisher: IEEE
 
» Kraken: Online and Elastic Resource Reservations for Cloud Datacenters
Abstract:
In cloud environments, the absence of strict network performance guarantees leads to unpredictable job execution times. To address this issue, recently, there have been several proposals on how to provide guaranteed network performance. These proposals, however, rely on computing resource reservation schedules a priori. Unfortunately, this is not practical in today’s cloud environments, where application demands are inherently unpredictable, e.g., due to differences in the input data sets or phenomena, such as failures and stragglers. To overcome these limitations, we designed Kraken, a system that allows to dynamically update minimum guarantees for both network bandwidth and compute resources at runtime. Unlike previous work, Kraken does not require prior knowledge about the resource needs of the applications but allows to modify reservations at runtime. Kraken achieves this through an online resource reservation scheme, which comes with provable optimality guarantees. In this paper, we motivate the need for dynamic resource reservation schemes, present how this is provided by Kraken, and evaluate Kraken via extensive simulations and a preliminary Hadoop prototype.
Autors: Carlo Fuerst;Stefan Schmid;Lalith Suresh;Paolo Costa;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Feb 2018, volume: 26, issue:1, pages: 422 - 435
Publisher: IEEE
 
» L-Shape Model Switching-Based Precise Motion Tracking of Moving Vehicles Using Laser Scanners
Abstract:
Detection and tracking of moving objects is one of the most essential functions of autonomous cars. In order to estimate the dynamic information of a moving object accurately, laser scanners are widely used for their highly accurate distance data. However, these data only represent the surface of an object facing the sensor and changes the appearance of an object over time. This change produces unexpected tracking errors of estimated dynamic states. In this paper, in order to minimize the tracking error caused by appearance changes, a tracking algorithm based on L-shaped model switching is proposed. The suggested algorithm is validated in real traffic experiments where position, velocity, and heading angle error were measured by using precise GPS. The L-shape tracking algorithm successfully mitigated the effect of appearance changes and improved estimation performance.
Autors: Dongchul Kim;Kichun Jo;Minchul Lee;Myoungho Sunwoo;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 598 - 612
Publisher: IEEE
 
» Labor of love: Re-creating the burned hp archives [Spectral Lines]
Abstract:
Some 100 boxes of correspondence, speeches, and other documents produced by William Hewlett and David Packard as they built the company considered to be the original Silicon Valley startup were reduced to ashes by the massive fires that took place in Sonoma County, Calif., last fall. These documents- the collected papers of Hewlett and Packard, containing records of the Hewlett-Packard Co. going as far back as 1937-were assembled before HP began the first of several splits starting in 1999. In recent years, the collection was stored in a modular building on the campus of Keysight Technologies, in Santa Rosa, Calif. (Keysight got custody of the documents when it spun out of Agilent Technologies, which had previously split off from HP.) The collection was hard to access by historians, had yet to be digitized, and was, as we now know, vulnerable to fire.
Autors: Tekla S. Perry;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 6 - 6
Publisher: IEEE
 
» Large-Scale Multimodality Attribute Reduction With Multi-Kernel Fuzzy Rough Sets
Abstract:
In complex pattern recognition tasks, objects are typically characterized by means of multimodality attributes, including categorical, numerical, text, image, audio, and even videos. In these cases, data are usually high dimensional, structurally complex, and granular. Those attributes exhibit some redundancy and irrelevant information. The evaluation, selection, and combination of multimodality attributes pose great challenges to traditional classification algorithms. Multikernel learning handles multimodality attributes by using different kernels to extract information coming from different attributes. However, it cannot consider the aspects fuzziness in fuzzy classification. Fuzzy rough sets emerge as a powerful vehicle to handle fuzzy and uncertain attribute reduction. In this paper, we design a framework of multimodality attribute reduction based on multikernel fuzzy rough sets. First, a combination of kernels based on set theory is defined to extract fuzzy similarity for fuzzy classification with multimodality attributes. Then, a model of multikernel fuzzy rough sets is constructed. Finally, we design an efficient attribute reduction algorithm for large scale multimodality fuzzy classification based on the proposed model. Experimental results demonstrate the effectiveness of the proposed model and the corresponding algorithm.
Autors: Qinghua Hu;Lingjun Zhang;Yucan Zhou;Witold Pedrycz;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 226 - 238
Publisher: IEEE
 
» Large-Scale Remote Sensing Image Retrieval by Deep Hashing Neural Networks
Abstract:
As one of the most challenging tasks of remote sensing big data mining, large-scale remote sensing image retrieval has attracted increasing attention from researchers. Existing large-scale remote sensing image retrieval approaches are generally implemented by using hashing learning methods, which take handcrafted features as inputs and map the high-dimensional feature vector to the low-dimensional binary feature vector to reduce feature-searching complexity levels. As a means of applying the merits of deep learning, this paper proposes a novel large-scale remote sensing image retrieval approach based on deep hashing neural networks (DHNNs). More specifically, DHNNs are composed of deep feature learning neural networks and hashing learning neural networks and can be optimized in an end-to-end manner. Rather than requiring to dedicate expertise and effort to the design of feature descriptors, we can automatically learn good feature extraction operations and feature hashing mapping under the supervision of labeled samples. To broaden the application field, DHNNs are evaluated under two representative remote sensing cases: scarce and sufficient labeled samples. To make up for a lack of labeled samples, DHNNs can be trained via transfer learning for the former case. For the latter case, DHNNs can be trained via supervised learning from scratch with the aid of a vast number of labeled samples. Extensive experiments on one public remote sensing image data set with a limited number of labeled samples and on another public data set with plenty of labeled samples show that the proposed remote sensing image retrieval approach based on DHNNs can remarkably outperform state-of-the-art methods under both of the examined conditions.
Autors: Yansheng Li;Yongjun Zhang;Xin Huang;Hu Zhu;Jiayi Ma;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 950 - 965
Publisher: IEEE
 
» Laser Cladding-Based Metallic Embedding Technique for Fiber Optic Sensors
Abstract:
In many applications in the industry, securely attaching fiber optic sensors to metallic structures is important for optimum monitoring, overcoming the limitations of glues and adhesives which are known to degrade under certain circumstances. To avoid that problem, creating a metallic bond to attach the sensors securely to the metal surface is important. Commercial fiber optics with metal coatings can be used but it is important not to damage the sensor itself which is written in the thin optical fiber. In this work, an alternative laser cladding technology has been studied for embedding metal-coated fiber optics into which fiber Bragg grating (FBG) sensors have been written. A three-step strategy was selected for embedding the metal coating fibers to create the best conditions to allow high-quality measurements. This has been seen to allow good control of the embedding process to be achieved and to minimize the thermal and mechanical stress generated. The research undetaken has shown that it is possible to embed Cu- and Ni-coated fiber optics containing sensors to over 300 μm with low losses, of between 0–1.5 dB (or 0–30%) and yet still enable satisfactory strain and temperature measurement results to be obtained. The research has shown that both Ni- and Cu-coated FBG-based fiber optic sensors could be embedded successfully and shown to give good mechanical and thermal response to similar nonembedded sensors and excellent cross-comparison with the conventional gauge used for calibration. The results are, therefore, particularly encouraging for the use of sensors of this type when incorporated to create metallic “smart structures” achieving durability of the sensors through the use of this innovative technique.
Autors: Tania Grandal;Ander Zornoza;Sergio Fraga;Gemma Castro;Tong Sun;Kenneth T. V. Grattan;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 1018 - 1025
Publisher: IEEE
 
» Laser Patterning a Chem-FET Like Device on a V2O5 Xerogel Film
Abstract:
Vanadium pentoxide xerogel films deposited onto gold microelectrodes were micropatterned by thermally induced conversion into crystalline -V2O5, using optical lithography written at the focus of a confocal Raman microscope. The laser scribing process improved the electric contact and promoted the -doping of the film with ions. In this way, a field effect transistor like device was constructed and successfully applied as humidity sensor, where the combined lithographic design and the application of a negative back gate field ( V) boosted the source–drain current by a hundred times, leading to a large gain in sensitivity.
Autors: Manuel F. G. Huila;André L. A. Parussulo;Luis E. G. Armas;Henrique E. M. Peres;Antonio C. Seabra;Francisco J. Ramirez-Fernandez;Koiti Araki;Henrique E. Toma;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1358 - 1363
Publisher: IEEE
 
» Laser Phase-Noise Cancellation in Chirped-Pulse Distributed Acoustic Sensors
Abstract:
Distributed acoustic sensors based on chirped-pulse phase sensitive-optical time-domain reflectometry (chirped-pulse ΦOTDR) have proven capable of performing fully distributed, single shot measurements of true strain or temperature perturbations, with no need for frequency scanning or phase detection methods. The corresponding refractive index variations in the fiber are revealed in the chirped-pulse ΦOTDR trace through a local temporal shift, which is evaluated using trace-to-trace correlations. The accuracy in the detection of this perturbation depends upon the correlation noise and the coherence of the laser source. In this paper, we theoretically and experimentally analyze the impact of the laser phase noise in chirped-pulse ΦOTDR. In particular, it is shown that the noise in the readings of strain/temperature variations scales directly with the frequency noise power spectral density of the laser. To validate the developed model, an experimental study has been performed using three lasers with different static linewidths (5 MHz, 50 kHz, and 25 kHz), i.e., with different phase noise. Besides, we present a simple technique to mitigate the effect of the laser phase noise in chirped-pulse ΦOTDR measurements. The proposed procedure enables to detect perturbations with high signal-to-noise ratio even when using relatively broad linewidth (i.e., comparatively high phase noise) lasers. Up to 17 dB increase in signal-to-noise ratio has been experimentally achieved by applying the proposed noise cancellation technique.
Autors: María R. Fernández-Ruiz;Juan Pastor-Graells;Hugo F. Martins;Andres Garcia-Ruiz;Sonia Martin-Lopez;Miguel Gonzalez-Herraez;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 979 - 985
Publisher: IEEE
 
» Laser Self-Mixing Grating Interferometer for MEMS Accelerometer Testing
Abstract:
A simple and robust testing system based on a laser self-mixing grating interferometer (SMGI) is proposed to determine the sensitivity of accelerometers. Self-mixing grating interference occurs when the light emitted from a laser diode is incident onto a reflective grating at a fixed angle and the first-order diffracted light returns back into the laser cavity. Frequency ratio method and minimum point method that are officially used to calibrate accelerometers are modified to make it suitable to an SMGI testing system. In order to evaluate the performance of the proposed method, the sensitivity of a commercial microelectromechanical system accelerometer was tested at different vibration frequency. The obtained results show good agreement with the sensitivity given by the manufacturer's specification. Given its stability, simplicity, and efficiency, the proposed system has the potential to be adopted as an alternative method to test accelerometers for industrial applications.
Autors: Dongmei Guo;Haiqing Jiang;Liheng Shi;Ming Wang;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 9
Publisher: IEEE
 
» Laser-Assisted Wet Etching of Quartz Crystal Resonators
Abstract:
This paper reports on the development of a laser-assisted wet etching process for quartz crystal resonators. The quartz crystals are in contact with hydrofluoric acid on the backside while the laser is irradiating the front side of the crystal. The quartz crystal has a chromium thin film deposited with thicknesses varying from 5 to 20 nm to absorb the energy from the laser during processing. The laser used has a wavelength of 808 nm ±3 nm with a power output of 5 W. By increasing the power density, the etch rate with the laser setup can be adjusted from 3.8 to 278 . This can be done through beam shaping with focusing lenses. Current wet etching processes require quartz crystals to be frequency trimmed after each step with multiple steps required for processing. With the laser assisted wet etching process quartz resonators can have their frequency tuned by varying the etch rate through adjust the laser’s power density. [2017-0193]
Autors: William Clower;Ville Kaajakari;Chester G. Wilson;
Appeared in: Journal of Microelectromechanical Systems
Publication date: Feb 2018, volume: 27, issue:1, pages: 22 - 24
Publisher: IEEE
 
» LDPC Code Design for Distributed Storage: Balancing Repair Bandwidth, Reliability, and Storage Overhead
Abstract:
Distributed storage systems suffer from significant repair traffic generated due to the frequent storage node failures. This paper shows that properly designed low-density parity-check (LDPC) codes can substantially reduce the amount of required block downloads for repair thanks to the sparse nature of their factor graph representation. In particular, with a careful construction of the factor graph, both low repair-bandwidth and high reliability can be achieved for a given code rate. First, a formula for the average repair bandwidth of LDPC codes is developed. This formula is then used to establish that the minimum repair bandwidth can be achieved by forcing a regular check node degree in the factor graph. Moreover, it is shown that given a fixed code rate, the variable node degree should also be regular to yield minimum repair bandwidth, under some reasonable minimum variable node degree constraint. It is also shown that for a given repair-bandwidth requirement, LDPC codes can yield substantially higher reliability than the currently utilized Reed–Solomon codes. Our reliability analysis is based on a formulation of the general equation for the mean-time-to-data-loss (MTTDL) associated with LDPC codes. The formulation reveals that the stopping number is closely related to the MTTDL. It is further shown that LDPC codes can be designed such that a small loss of repair-bandwidth optimality may be traded for a large improvement in erasure-correction capability and thus the MTTDL.
Autors: Hyegyeong Park;Dongwon Lee;Jaekyun Moon;
Appeared in: IEEE Transactions on Communications
Publication date: Feb 2018, volume: 66, issue:2, pages: 507 - 520
Publisher: IEEE
 
» Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
Abstract:
Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Therefore, in this article, we first introduce deep learning for IoTs into the edge computing environment. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. In the performance evaluation, we test the performance of executing multiple deep learning tasks in an edge computing environment with our strategy. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT.
Autors: He Li;Kaoru Ota;Mianxiong Dong;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 96 - 101
Publisher: IEEE
 
» Learning process for reducing uncertainties on network parameters and design margins
Abstract:
In this paper, we propose to lower the network design margins by improving the estimation of the signal-tonoise ratio (SNR) given by a quality of transmission (QoT) estimator, for new optical demands in a brownfield phase, based on a mathematical model of the physics of propagation. During the greenfield phase and the network operation, we collect and correlate information on the QoT input parameters, issued from the established initial demands and available almost for free from the network elements: amplifiers output power and the SNR at the coherent receiver side. Since we have some uncertainties on these input parameters of the QoT model, we use a machine learning algorithm to reduce them, improving the accuracy of the SNR estimation. With this learning process and for a European backbone network (28 nodes, 41 links), we could reduce the QoT inaccuracy by several dBs for new demands whatever the amount of uncertainties of the initial parameters.
Autors: E. Seve;J. Pesic;C. Delezoide;S. Bigo;Y. Pointurier;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Feb 2018, volume: 10, issue:2, pages: A298 - A306
Publisher: IEEE
 
» Learning to Detect an Oddball Target
Abstract:
We consider the problem of detecting an odd process among a group of Poisson point processes, all having the same rate except the odd process. The actual rates of the odd and non-odd processes are unknown to the decision maker. We consider a time-slotted sequential detection scenario where, at the beginning of each slot, the decision maker can choose which process to observe during that time slot. We are interested in policies that satisfy a given constraint on the probability of false detection. We propose a variation on a sequential policy based on the generalised likelihood ratio statistic. The policy, via suitable thresholding, can be made to satisfy the given constraint on the probability of false detection. Furthermore, we show that the proposed policy is asymptotically optimal in terms of the conditional expected stopping time among all policies that satisfy the constraint on the probability of false detection. The asymptotic is as the probability of false detection is driven to zero. We apply our results to a particular visual search experiment studied recently by neuroscientists. Our model suggests a neuronal dissimilarity index for the visual search task. The neuronal dissimilarity index, when applied to visual search data from the particular experiment, correlates strongly with the behavioural data. However, the new dissimilarity index performs worse than some previously proposed neuronal dissimilarity indices. We explain why this may be attributed to some experiment conditions.
Autors: Nidhin Koshy Vaidhiyan;Rajesh Sundaresan;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 831 - 852
Publisher: IEEE
 
» Learning Wireless Networks’ Topologies Using Asymmetric Granger Causality
Abstract:
Sharing spectrum with a communicating incumbent user (IU) network requires avoiding interference to IU receivers. But since receivers are passive when in the receive mode and cannot be detected, the network topology can be used to predict the potential receivers of a currently active transmitter. For this purpose, this paper proposes a method to detect the directed links between IUs of time multiplexing communication networks from their transmission start and end times. It models the response mechanism of commonly used communication protocols using Granger causality: The probability of an IU starting a transmission after another IU's transmission ends increases if the former is a receiver of the latter. This paper proposes a nonparametric test statistic for detecting such behavior. To help differentiate between a response and the opportunistic access of the available spectrum, the same test statistic is used to estimate the response time of each link. The causal structure of the response is studied through a discrete time Markov chain that abstracts the IUs’ medium access protocol and focuses on the response time and response probability of 2 IUs. Through NS-3 simulations, it is shown that the proposed algorithm outperforms existing methods in accurately learning the topologies of infrastructure-based networks and that it can infer the directed data flow in ad hoc networks with finer time resolution than an existing method.
Autors: Mihir Laghate;Danijela Cabric;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Feb 2018, volume: 12, issue:1, pages: 233 - 247
Publisher: IEEE
 
» Length measurements in ancient Greece: Human standards in the golden age of the Olympic Games
Abstract:
Standards are quickly moving towards quantum metrology and provide extremely low uncertainties, which let people perform highly accurate measurements. Yet in the golden age of the early Olympic Games, most standards were based on human elements and were limited by their poor reproducibility. This paper discusses the old standards of length, their differences between cultures and places, their large uncertainty and, notwithstanding this, their great importance in the natural evolution of humanity.
Autors: Luca Parvis;
Appeared in: IEEE Instrumentation & Measurement Magazine
Publication date: Feb 2018, volume: 21, issue:1, pages: 46 - 49
Publisher: IEEE
 
» Lessons Learned from Protection and Control Schemes Testing: The Results of Multiple Trials Using IEC 61850 Goose Messaging at an Oil Refinery
Abstract:
Several Trials for Protection and Control Schemes based on the International Electrotechnical Commission (IEC) 61850 standard were recently implemented for the new electrical system at a U.S. oil refinery. IEC 61850, generic object-oriented substation event (GOOSE) messaging, was used for several schemes, including transfer tripping, breaker failure, islanding detection, remote synchronizing, automatic restoration, manual transfer, and load shedding. Site acceptance tests validated the operation of the protection and control schemes. Bench testing was also performed for the load-shedding scheme using a power-system simulator. All of the testing focused on verifying scheme operations during normal operation and failure modes. The experience gained during early project trials influenced the design and testing of subsequent schemes. This article describes the bench and site acceptance testing approaches used and presents example tests along with their relevant results and the lessons learned.
Autors: Jared Mraz;Aaron Cowan;Keith Gray;Kirti S. Shah;
Appeared in: IEEE Industry Applications Magazine
Publication date: Feb 2018, volume: 24, issue:1, pages: 60 - 70
Publisher: IEEE
 
» Leveraging Analysis of User Behavior to Identify Malicious Activities in Large-Scale Social Networks
Abstract:
With the enormous growth and volume of online social networks and their features, along with the vast number of socially connected users, it has become difficult to explain the true semantic value of published content for the detection of user behaviors. Without understanding the contextual background, it is impractical to differentiate among various groups in terms of their relevance and mutual relations, or to identify the most significant representatives from the community at large. In this paper, we propose an integrated social media content analysis platform that leverages three levels of features, i.e., user-generated content, social graph connections, and user profile activities, to analyze and detect anomalous behaviors that deviate significantly from the norm in large-scale social networks. Several types of analyses have been conducted for a better understanding of the different user behaviors in the detection of highly adaptive malicious users. We attempted a novel approach regarding the process of data extraction and classification to contextualize large-scale networks in a proper manner. We also collected a significant number of user profiles from Twitter and YouTube, along with around 13 million channel activities. Extensive evaluations were conducted on real-world datasets of user activities for both social networks. The evaluation results show the effectiveness and utility of the proposed approach.
Autors: Muhammad Al-Qurishi;M. Shamim Hossain;Majed Alrubaian;Sk Md Mizanur Rahman;Atif Alamri;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 799 - 813
Publisher: IEEE
 
» Leveraging High Order Cumulants for Spectrum Sensing and Power Recognition in Cognitive Radio Networks
Abstract:
Hybrid interweave-underlay spectrum access in cognitive radio networks can explore spectrum opportunities when primary users (PUs) are either active or inactive, which significantly improves spectrum utilization. The practical wireless systems, such as long-term evolution-advanced, usually operate at multiple transmission power levels, leading to a multiple primary transmission power scenario. In such a case, the two fundamental issues in hybrid interweave-underlay spectrum access are to detect the “ON/OFF” status of PUs and to recognize the operating power level of PUs, which are challenging due to non-Gaussian transmitted signals. In this paper, we exploit high-order cumulants (HOCs) to efficiently perform spectrum sensing and power recognition. Specifically, for a given order and time lag, we first propose a single HOC-based spectrum sensing and power recognition scheme with low computational complexity, by leveraging minimum Bayes risk criterion. Moreover, we propose a hybrid multiple HOCs-based spectrum sensing and power recognition scheme with multiple orders and time lags, to further improve the detection performance. Both the proposed schemes can eliminate the adverse impact of the noise power uncertainty. Finally, simulation results are provided to evaluate the proposed schemes.
Autors: Danyang Wang;Ning Zhang;Zan Li;Feifei Gao;Xuemin Shen;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1298 - 1310
Publisher: IEEE
 
» Leveraging mixed-strategy gaming to realize incentive-driven VNF service chain provisioning in broker-based elastic optical inter-datacenter networks
Abstract:
This paper investigates the problem of how to optimize the provisioning of virtual network function service chains (VNF-SCs) in elastic optical inter-datacenter networks (EO-IDCNs) under elastic optical networking and DC capacity constraints. We take advantage of the broker-based hierarchical control paradigm for the orchestration of cross-stratum resources and propose to realize incentive-driven VNF-SC provisioning with a noncooperative mixed-strategy gaming approach. The proposed gaming model enables tenants to compete for VNF-SC provisioning services due to revenue and quality-of-service incentives and therefore can motivate more reasonable selections of provisioning schemes. We detail the modeling of the game, discuss the existence of the Nash equilibrium states, and design an auxiliary graph-based heuristic algorithm for tenants to compute approximate equilibrium solutions in the games. A dynamic resource pricing strategy, which can set the prices of network resources in real time according to the actual network status, is also introduced for EO-IDCNs as a complementary method to the game-theoretic approach. Results from extensive simulations that consider both static network planning and dynamic service provisioning scenarios indicate that the proposed game-theoretic approach facilitates both higher tenant and network-wide profits and improves the network throughput as well compared with the baseline algorithms, while the dynamic pricing strategy can further reduce the request blocking probability with a factor of ∼2.4×.
Autors: Xiaoliang Chen;Zuqing Zhu;Jiannan Guo;Sheng Kang;Roberto Proietti;Alberto Castro;S. J. B. Yoo;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Feb 2018, volume: 10, issue:2, pages: A232 - A240
Publisher: IEEE
 
» Leveraging Software-Defined Networking for Incident Response in Industrial Control Systems
Abstract:
In the past decade, the security of industrial control systems has emerged as a research priority in order to safeguard our critical infrastructures. A large number of research efforts have focused on intrusion detection in industrial networks; however, few of them discuss what to do after an intrusion has been detected. Because the safety of most of these control systems is time sensitive, we need new research on automatic incident response. This article shows how software-defined networks and network function virtualization can facilitate automatic incident response to a variety of attacks against industrial networks. It also presents a prototype of an incident-response solution that detects and responds automatically to sensor attacks and controller attacks. This work shows the promise that cloud-enabled software-defined networks and virtual infrastructures hold as a way to provide novel defense-in-depth solutions for industrial systems. This article is part of a special issue on Software Safety and Security Risk Mitigation in Cyber-physical Systems.
Autors: Andrés F. Murillo Piedrahita;Vikram Gaur;Jairo Giraldo;Álvaro A. Cárdenas;Sandra Julieta Rueda;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 44 - 50
Publisher: IEEE
 
» LiDAR Point Clouds to 3-D Urban Models$:$ A Review
Abstract:
Three-dimensional (3-D) urban models are an integral part of numerous applications, such as urban planning and performance simulation, mapping and visualization, emergency response training and entertainment, among others. We consolidate various algorithms proposed for reconstructing 3-D models of urban objects from point clouds. Urban models addressed in this review include buildings, vegetation, utilities such as roads or power lines and free-form architectures such as curved buildings or statues, all of which are ubiquitous in a typical urban scenario. While urban modeling, building reconstruction, in particular, clearly demand specific traits in the models, such as regularity, symmetry, and repetition; most of the traditional and state-of-the-art 3-D reconstruction algorithms are designed to address very generic objects of arbitrary shapes and topology. The recent efforts in the urban reconstruction arena, however, strive to accommodate the various pressing needs of urban modeling. Strategically, urban modeling research nowadays focuses on the usage of specialized priors, such as global regularity, Manhattan-geometry or symmetry to aid the reconstruction, or efficient adaptation of existing reconstruction techniques to the urban modeling pipeline. Aimed at an in-depth exploration of further possibilities, we review the existing urban reconstruction algorithms, prevalent in computer graphics, computer vision and photogrammetry disciplines, evaluate their performance in the architectural modeling context, and discuss the adaptability of generic mesh reconstruction techniques to the urban modeling pipeline. In the end, we suggest a few directions of research that may be adopted to close in the technology gaps.
Autors: Ruisheng Wang;Jiju Peethambaran;Dong Chen;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 606 - 627
Publisher: IEEE
 
» Life in the C-Suite 2.0
Abstract:
An introduction to the new Life in the C-Suite column, which will help C-level executives understand the vast digital world in which they live, and how they should leverage digital technology into their business processes and business models.
Autors: Stephen J. Andriole;
Appeared in: IT Professional
Publication date: Feb 2018, volume: 20, issue:1, pages: 77 - 79
Publisher: IEEE
 
» Lifetime Estimation of Discrete IGBT Devices Based on Gaussian Process
Abstract:
Discrete package insulated gate bipolar transistor (IGBT) devices are a popular choice for low-power converters. Although IGBT power modules used in high-power applications have recently been studied in the literature, there are major knowledge gaps regarding reliability and lifetime estimation of discrete devices. In this paper, on-state collector–emitter voltage drop variations are characterized for discrete IGBT devices exposed to cyclic thermal stresses. Variations in are carefully identified and classified depending on different aging mechanisms, stress levels, and device structures. A probabilistic framework for remaining useful lifetime (RUL) estimation based on the knowledge obtained by accelerated aging experiments for real-time RUL estimation has been proposed. Specifically, the proposed model uses Gaussian process regression (GPR) for applying a Bayesian inference (BI) on RUL estimation of the device under test. Using BI reduces the uncertainty associated with RUL estimation and leads to more accurate results. This concept is also tested by comparing the classical maximum-likelihood estimation and GPR estimation results with the ones obtained by accelerated aging tests.
Autors: Syed Huzaif Ali;Mehrdad Heydarzadeh;Serkan Dusmez;Xiong Li;Anant S. Kamath;Bilal Akin;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 395 - 403
Publisher: IEEE
 
» Limiting Effects on the Design of Vertical Superjunction Collectors in SiGe HBTs
Abstract:
The implementation of a “superjunction” collector design in a silicon–germanium heterojunction bipolar transistor technology is explored for enhancing breakdown performance. The superjunction collector is formed via the placement of a series of alternating the p/xn-doped layers in the collector-base space charge region and is used to reduce avalanche generation leading to breakdown. An overview of the physics underlying superjunction collector operation is presented, together with TCAD simulations, and a parameterization methodology is developed to explore the limits of the superjunction collector performance. Measured data demonstrate the limitations explored in simulation.
Autors: Brian R. Wier;Uppili S. Raghunathan;Zachary E. Fleetwood;Michael A. Oakley;Alvin J. Joseph;Vibhor Jain;John D. Cressler;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 793 - 797
Publisher: IEEE
 
» Line Balancing Strategy for Re-Entrant Manufacturing
Abstract:
Scheduling in a re-entrant manufacturing environment is a complex task that requires a scheduler to handle a larger number of uncertainties than in a traditional manufacturing environment. Many input control strategies and dispatching rules are applied to re-entrant processes to achieve fast and relatively effective solutions. However, due to the complexity of these processes, the dispatching rules currently employed in general flow shops do not guarantee the consistency of results despite the benefits of these rules. To address this issue, an extremely robust drum-buffer-rope-based releasing and holding scheduling method is proposed in this paper. An overview of the proposed method is presented, including the process by which the re-entrant process is reconfigured into independent flow shops and the balancing of the production loads among individual loops. Nine scheduling scenarios comprising different combinations of three loop load measurement parameters and three loop-balancing methods are employed to test the applicability and performance of the proposed method.
Autors: Sungwook Yoon;Sukjae Jeong;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 42 - 51
Publisher: IEEE
 
» Linear Size Constant-Composition Codes Meeting the Johnson Bound
Abstract:
The Johnson-type upper bound on the maximum size of a code of length , distance , and constant composition is , where is the total weight and is the largest component of . Recently, Chee et al. proved that this upper bound can be achieved for all constant-composition codes of sufficiently large lengths. Let be the smallest such length. The determination of is trivial for binary codes. This paper provides a lower bound on , which is shown to be tight for all ternary and quaternary codes by giving new combinatorial constructions. Consequently, by the refining method, we determine the values of , for all -ary constant-composition codes, provided that with finite possible exceptions.
Autors: Yeow Meng Chee;Xiande Zhang;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 909 - 917
Publisher: IEEE
 
» Linearized DC-MMC Models for Control Design Accounting for Multifrequency Power Transfer Mechanisms
Abstract:
The dc-modular multilevel converter (DC-MMC) is one of a new class of single-stage modular multilevel dc–dc converters that has recently emerged for high-voltage dc applications. This paper presents the first small-signal state-space model for the DC-MMC that is able to account for the multifrequency power transfer mechanisms within the converter. Derived from a dynamic phasor model representation of the DC-MMC, the developed model is linear time-invariant (LTI), allowing for the application of conventional LTI tools for both analysis and design. The small-signal dynamics are validated by simulation results from a full switched model demonstrating its accuracy. A simplified model derived from the full LTI system is presented that readers can utilize to develop dynamic controls for the DC-MMC. As a case study, this benchmark model is leveraged to propose a dynamic controller that regulates dc power transfer between networks and balances the capacitor voltages. Control block diagrams are also provided that enable systematic control design of the DC-MMC via standard linear methods. Case study simulations verify the efficacy of the developed controls for dc network applications. The presented small-signal modeling and control design methodology can be readily applied to any MMC-based topology.
Autors: Gregory J. Kish;Peter W. Lehn;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 271 - 281
Publisher: IEEE
 
» Liquid Sound Velocity and Density Decoupling on a Compact Lamb Wave Sensor by a Two-Port Local Resonating Method
Abstract:
A two-port local resonating (TPLR) method for thin-film Lamb wave sensor is proposed. Based on properties of multi-modes analyzed by numerical simulation and experimental measurement, the TPLR method is able to generate the second-order flexural mode (, ). Density and sound velocity of liquid solutions can be decoupled based on the first-order flexural mode (, ) and the mode, and solutions with the same density, such as CH3CH2OH and CH3OH, can be successfully distinguished on a single Lamb wave device. When the phase velocity of mode is close to the sound velocity of liquid, compared with the traditional delay-line configuration, smaller period of interdigital transducers and device miniaturization by the TPLR method can be realized. Generation of new modes with the TPLR method demonstrates an alternative for multi-parameters sensing of Lamb wave sensors.
Autors: Chuanyu Li;Hui Kong;Yuguo Tang;Jean-François Manceau;François Bastien;Lianqun Zhou;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1384 - 1389
Publisher: IEEE
 
» Lithium Niobate Electro-Optic Racetrack Modulator Etched in Y-Cut LNOI Platform
Abstract:
An electro-optic modulator (EOM) based on a racetrack resonator coupled to a waveguide using butterfly multi-mode interference (MMI) coupler is fabricated on Y-cut lithium niobate (LN) thin film. This is the first demonstration of a LN EOM in which the thin film of LN is etched in a Y-cut substrate using chlorine-based inductively coupled plasma reactive ion etching, a process, which is readily compatible with semiconductor fabrication facility. The Y-cut LNOI platform is interesting for the integration of electro-optic and acousto-optic components, since differently from any other LN cut it facilitates taking advantage of the maximum electro-optic and piezoelectric coefficients of LN. Coupling to the racetrack was enabled using a butterfly MMI coupler, which offered operation near the critical coupling condition, hence increasing the extinction ratio (ER) of the modulator. An unloaded quality factor of 1.3 × 105 was extracted for this device, which is equivalent to a propagation loss of 2.3 dB/cm. Modulation bandwidth of 4 GHz, wavelength tuning rate of 0.32 pm/V, and an ER of more than 10 dB were experimentally measured for the EOM.
Autors: Mohamed Mahmoud;Lutong Cai;Christian Bottenfield;Gianluca Piazza;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 10
Publisher: IEEE
 
» LLR-Based SC Decoding of Polar Codes for Two-User Binary-Input MAC
Abstract:
This letter considers a hardware-friendly log-likelihood ratio (LLR)-based successive cancellation (SC) decoding of polar codes for two-user binary-input multiple access channels. Based on the known recursive equations in the likelihood domain, we obtain LLR-based recursive equations for the SC decoding. An approximate LLR-based decoding is also introduced, which shows small performance loss at high error rate, but has significantly low complexity compared with the previous likelihood-based decoding.
Autors: Jong-Hwan Kim;Yeon Joon Choi;Sang-Hyo Kim;Keunyoung Kim;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 256 - 259
Publisher: IEEE
 
» Loading the Third Harmonic: A Linear and Efficient Post-Matching Doherty PA
Abstract:
Among the most exciting parts of the IEEE Microwave Theory and Techniques Society (MTT-S) 2017 International Microwave Symposium (IMS2017) was the "High-Efficiency Power Amplifier" Student Design Competition (SDC) sponsored by Technical Coordinating Committee MTT-5. This competition focuses on RF power amplifiers (PAs) having both high efficiency and linearity. Competitors are required to design, construct, and measure a high-efficiency PA with a specified linearity at a frequency of their choice between 1 and 10 GHz. The winner is determined by a figure of merit (FOM), with other requirements [1] that must also be satisfied.
Autors: Xin Yu Zhou;Wing Shing Chan;Derek Ho;Shao Yong Zheng;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 99 - 105
Publisher: IEEE
 
» Local Binary Pattern-Based Hyperspectral Image Classification With Superpixel Guidance
Abstract:
Since it is usually difficult and time-consuming to obtain sufficient training samples by manually labeling, feature extraction, which investigates the characteristics of hyperspectral images (HSIs), such as spectral continuity and spatial locality of surface objects, to achieve the most discriminative feature representation, is very important for HSI classification. Meanwhile, due to the spatial regularity of surface materials, it is desirable to improve the classification performance of HSIs from the superpixel viewpoint. In this paper, we propose a novel local binary pattern (LBP)-based superpixel-level decision fusion method for HSI classification. The proposed framework employs uniform LBP (ULBP) to extract local image features, and then, a support vector machine is utilized to formulate the probability description of each pixel belonging to every class. The composite image of the first three components extracted by a principal component analysis from the HSI data is oversegmented into many homogeneous regions by using the entropy rate segmentation method. Then, a region merging process is applied to make the superpixels obtained more homogeneous and agree with the spatial structure of materials more precisely. Finally, a probability-oriented classification strategy is applied to classify each pixel based on superpixel-level guidance. The proposed framework “ULBP-based superpixel-level decision fusion framework” is named ULBP-SPG. Experimental results on two real HSI data sets have demonstrated that the proposed ULBP-SPG framework is more effective and powerful than several state-of-the-art methods.
Autors: Sen Jia;Bin Deng;Jiasong Zhu;Xiuping Jia;Qingquan Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 749 - 759
Publisher: IEEE
 
» Local Deep Field for Electrocardiogram Beat Classification
Abstract:
To reduce the high mortality rate among heart patients, electrocardiogram (ECG) beat classification plays an important role in computer aided diagnosis system, but this issue is challenging because of the complex variations of data. Since ECG beat data lie on high-dimension manifold, we propose a novel method, named “local deep field”, in purpose of capturing the devil in the details of such data manifold. This method learns different deep models within the local manifold charts. Local regionalization can help models focus on the particularity of local variations, while deep architecture can disentangle the hidden class information within local distributions. The advantage of the proposed method has been experimentally demonstrated in terms of MIT-BIH Arrhythmia database.
Autors: Wei Li;Jianqing Li;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1656 - 1664
Publisher: IEEE
 
» Local Feature-Based Attribute Profiles for Optical Remote Sensing Image Classification
Abstract:
This paper introduces an extension of morphological attribute profiles (APs) by extracting their local features. The so-called local feature-based APs (LFAPs) are expected to provide a better characterization of each APs’ filtered pixel (i.e., APs’ sample) within its neighborhood, and hence better deal with local texture information from the image content. In this paper, LFAPs are constructed by extracting some simple first-order statistical features of the local patch around each APs’ sample such as mean, standard deviation, and range. Then, the final feature vector characterizing each image pixel is formed by combining all local features extracted from APs of that pixel. In addition, since the self-dual APs (SDAPs) have been proved to outperform the APs in recent years, a similar process will be applied to form the local feature-based SDAPs (LFSDAPs). In order to evaluate the effectiveness of LFAPs and LFSDAPs, supervised classification using both the random forest and the support vector machine classifiers is performed on the very high resolution Reykjavik image as well as the hyperspectral Pavia University data. Experimental results show that LFAPs (respectively, LFSDAPs) can considerably improve the classification accuracy of the standard APs (respectively, SDAPs) and the recently proposed histogram-based APs.
Autors: Minh-Tan Pham;Sébastien Lefèvre;Erchan Aptoula;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 1199 - 1212
Publisher: IEEE
 
» Local Inverse Tone Mapping for Scalable High Dynamic Range Image Coding
Abstract:
Tone mapping operators (TMOs) and inverse TMOs (iTMOs) are important for scalable coding of high dynamic range (HDR) images. Because of the high nonlinearity of local TMOs, it is very difficult to estimate the iTMO accurately for a local TMO. In this letter, we present a two-layer local iTMO estimation algorithm using an edge-preserving decomposition technique. The low dynamic range (LDR) image is first linearized and then decomposed into a base layer and a detail layer via a fast edge-preserving decomposition method. The base layer of the HDR image is generated by subtracting the LDR detail layer from the HDR image. An iTMO function is finally estimated by solving a novel quadratic optimization problem formulated on the pair of base layers rather than the pair of HDR and LDR images as in existing methods. Experimental results show that the proposed two-layer iTMO can recover the HDR accurately so that it is possible to use these local TMOs in scalable HDR image coding schemes.
Autors: Zhe Wei;Changyun Wen;Zhengguo Li;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Feb 2018, volume: 28, issue:2, pages: 550 - 555
Publisher: IEEE
 
» Local Stabilization for Continuous-time Takagi–Sugeno Fuzzy Systems With Time Delay
Abstract:
This brief paper investigates the local stabilization for continues-time Takagi–Sugeno fuzzy systems with constant time delay. In order to deal with the time delay, we design a Lyapunov–Krasovskii functional that is dependent on the membership function. Based on the Lyapunov–Krasovskii functional and the analysis of the time derivative of the membership function, less conservative results can be obtained; however, the Lyapunov–Krasovskii functional is designed so complicated that the Lyapunov level set is hard to be measured directly. Alternatively, two sets are obtained to estimate the local stabilization. One set is for the time-varying initial conditions and the other is for the time-invariant initial conditions. The relationship between the two sets are also discussed. In the end, two examples are given to illustrate the effectiveness of the proposed approach.
Autors: Likui Wang;Hak-Keung Lam;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 379 - 385
Publisher: IEEE
 
» Localization of Multiple Underwater Objects With Gravity Field and Gravity Gradient Tensor
Abstract:
We present a novel algorithm to locate multiple underwater objects in real time using gravity field vector and gravity gradient tensor signals. This algorithm formulates the task of localization of multiple underwater objects into a regularized nonlinear problem, which is solved with the standard Levenberg–Marquardt algorithm. The regularization parameters are estimated by cross validation. The initial coordinates and masses of these underwater objects are automatically determined by solving a single-object localization problem. A synthetic navigation model with two underwater objects was adopted to validate the proposed algorithm. The results show that it has good stability and antinoise ability for multiple underwater objects localizations.
Autors: Jingtian Tang;Shuanggui Hu;Zhengyong Ren;Chaojian Chen;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 247 - 251
Publisher: IEEE
 
» Long Period Fiber Grating for Biosensing: An Improved Design Methodology to Enhance Add-Layer Sensitivity
Abstract:
We present our theoretical study on the design of long period fiber grating (LPFG) sensor where its add-layer sensitivity is enhanced. Add-layer sensitivity quantifies the sensitivity of the sensor to the changes taking place within few tens of nanometers around the receptor molecules. Two different methodologies: the use of dual overlay layer and tailoring of the intermodal separation between two cladding modes have been used to enhance the add-layer sensisstivity. Using coupled mode analysis, we compute several examples to carry out a detailed comparative analysis between the results obtained, focusing on the cladding mode near mode transition.
Autors: Sankhyabrata Bandyopadhyay;Ignacio Del Villar;Nandini Basumallick;Palas Biswas;Tanoy Kumar Dey;Somnath Bandyopadhyay;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 1178 - 1184
Publisher: IEEE
 
» Long Period Gratings in Multicore Optical Fibers for Directional Curvature Sensor Implementation
Abstract:
Multicore optical fibers are especially attractive for the fabrication of curvature and shape sensors due to the spatial distribution of the different cores. Fiber Bragg gratings have been used in the past for the implementation of these sensors, however, despite their inherent properties, they have a very limited sensitivity. In this paper, we study the use of long period gratings (LPGs) for the implementation of a directional curvature sensor. We inscribed a set of three different LPGs in a seven core optical fiber using a selective inscription technique. We inscribed a single LPG in the external cores and an array of three LPGs in the central core. We have characterized the proposed sensor for strain, torsion, and curvature magnitude and direction. The proposed sensor shows a linear response for curvature magnitudes from 0 to 1.77 m–1 with a maximum curvature sensitivity of –4.85 nm/m–1 and shows a near sinusoidal behavior in all the cores with curvature directions from 0° to 360°. The sensor shows a good insensitivity to strain. The torsion in the multicore optical fibers can be detected and measured using the maximum attenuation of the LPGs in the external cores.
Autors: David Barrera;Javier Madrigal;Salvador Sales;
Appeared in: Journal of Lightwave Technology
Publication date: Feb 2018, volume: 36, issue:4, pages: 1063 - 1068
Publisher: IEEE
 
» Loop-Free Route Updates for Software-Defined Networks
Abstract:
We consider the fundamental problem of updating arbitrary routes in a software-defined network in a (transiently) loop-free manner. Our objective is to compute fast network update schedules which minimize the number of interactions (i.e., rounds) between the controller and the network nodes. We first prove that this problem is difficult in general: The problem of deciding whether a -round update schedule exists is NP-complete already for , and there are problem instances requiring rounds, where is the network size. Given these negative results, we introduce an attractive, relaxed notion of loop-freedom. We show that relaxed loop-freedom admits for much shorter update schedules (up to a factor in the best case), and present a scheduling algorithm which requires at most rounds.
Autors: Klaus-Tycho Foerster;Arne Ludwig;Jan Marcinkowski;Stefan Schmid;
Appeared in: IEEE/ACM Transactions on Networking
Publication date: Feb 2018, volume: 26, issue:1, pages: 328 - 341
Publisher: IEEE
 
» Lorentz Force Electrical-Impedance Tomography Using Linearly Frequency-Modulated Ultrasound Pulse
Abstract:
Lorentz force electrical-impedance tomography (LFEIT) combines ultrasound stimulation and electromagnetic field detection with the goal of creating a high-contrast and high-resolution hybrid imaging modality. To reduce the peak stimulation power to the ultrasound transducer in LFEIT, linearly frequency-modulated (LFM) ultrasound pulse was investigated in this paper. First, the coherency between LFM ultrasound excitation and the resulting local current density was established theoretically. Then, experiments were done using different agar phantoms of conductivity ranging from 0.2 to 0.5 S/m. The results showed: 1) using electrical signal of peak instantaneous power of 39.54 dBm to the ultrasound transducer, which was 25.5 dB lower than the peak instantaneous power of the high-voltage narrow pulse adopted in traditional LFEIT (65.05 dBm), the LFM ultrasound pulse-based LFEIT can detect the electrical conductivity discontinuity positions precisely; 2) the reconstructed B-scan image of the electrical conductivity discontinuity distribution is comparable to that obtained through LFEIT with high-voltage narrow pulse; and 3) axial resolution of 1 mm was achieved with the experimental setup. The method of LFM ultrasound pulse stimulation and coherent detection initiates an alternative scheme toward the clinical application of LFEIT.
Autors: Zhishen Sun;Guoqiang Liu;Hui Xia;Stefan Catheline;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Feb 2018, volume: 65, issue:2, pages: 168 - 177
Publisher: IEEE
 
» Lossless Compression of Color Filter Array Mosaic Images With Visualization via JPEG 2000
Abstract:
Digital cameras have become ubiquitous for amateur and professional applications. The raw images captured by digital sensors typically take the form of color filter array (CFA) mosaic images which must be “developed” (via digital signal processing) before they can be viewed. Photographers and scientists often repeat the “development process” using different parameters to obtain images suitable for different purposes. Since the development process is generally not invertible it is commonly desirable to store the raw (or undeveloped) mosaic images indefinitely. Uncompressed mosaic image file sizes can be more than 30 times larger than those of developed images stored in JPEG format. Thus data compression is of interest. Several compression methods for mosaic images have been proposed in the literature. However they all require a custom decompressor followed by development-specific software to generate a displayable image. In this paper a novel compression pipeline that removes these requirements is proposed. Specifically mosaic images can be losslessly recovered from the resulting compressed files and more significantly images can be directly viewed (decompressed and developed) using only a JPEG 2000 compliant image viewer. Experiments reveal that the proposed pipeline attains excellent visual quality while providing compression performance competitive to that of state-of-the-art compression algorithms for mosaic images.
Autors: Miguel Hernández-Cabronero;Michael W. Marcellin;Ian Blanes;Joan Serra-Sagristà;
Appeared in: IEEE Transactions on Multimedia
Publication date: Feb 2018, volume: 20, issue:2, pages: 257 - 270
Publisher: IEEE
 
» Low-Complexity MIMO Signal Detection Employing Multistream Constrained Search
Abstract:
This study proposes the multistream constrained search (MSCS) as a low-complexity signal detection method for multiple-input multiple-output (MIMO) communications. MSCS achieves an excellent tradeoff between computational complexity and bit error rate (BER). Based on the maximum a posteriori probability (MAP) estimation, MSCS applies discrete optimization to some streams and continuous optimization to others. First, the discrete optimization constrains some streams to a certain set of modulation symbols. The continuous optimization is then used to identify the optimal continuous values of the other streams under this constrained condition and quantizes the results. A signal candidate comprises the quantized optimal values and constrained streams. Multiple constraint patterns result in multiple signal candidates, and sphere decoding (SD) identifies the detected signal as the one that maximizes the likelihood function. Limiting the number of constrained streams and applying SD can reduce computational complexity. In addition, MSCS selects constrained streams that have large variances of Gaussian distributions obtained from the MAP estimation. As a result of this stream selection method, MSCS can maintain an excellent BER performance even when the constrained streams are few in number. Computer simulations in 8-by-8 MIMO channels with modulation schemes of 16- and 64-QAM demonstrate that MSCS suffers degradation of merely 0.2 dB in average BER performance compared to the maximum likelihood detection (MLD). We also show that MSCS can achieve a similar average BER performance as that of the QR decomposition and M algorithm (QRM-MLD) while requiring less computational complexity. Under uncorrelated channels, the complexity of MSCS is less than 1/2 and 1/4 that of QRM-MLD in the case of 16- and 64-QAM, respectively. By contrast, simulations under channels with transmit-side spatial correlation show that when 16-QAM is used and average <- nline-formula>$E_b/N_0$ is equal to 18 dB, the complexity of MSCS ranges from 3/10 to 2/5 that of QRM-MLD. We also show that the complexity of MSCS ranges from 1/10 to 1/6 that of QRM-MLD when 64-QAM is used and the average is 23 dB.
Autors: Katsuya Kato;Kazuhiko Fukawa;Ryota Yamada;Hiroshi Suzuki;Satoshi Suyama;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Feb 2018, volume: 67, issue:2, pages: 1217 - 1230
Publisher: IEEE
 
» Low-Frequency Eddy-Current Testing for Detection of Subsurface Cracks in CF-188 Stub Flange
Abstract:
The vertical stub flanges on the CF-188 Hornet fighter aircraft are responsible for linking two vertical stabilizers to the fuselage. Repeated stresses due to dynamic loads on aircraft structure during flight may cause eyebrow cracks on the flange around fastener holes. Prevention of failure of the flange structure involves early detection before cracks grow to a critical length. Low-frequency eddy-current (LFEC) techniques have been applied to inspect thick conducting aircraft structures. However, in the case of the stub flange, LFEC is challenged by component geometry. In particular, the surface containing cracks is not parallel to the surface that is accessible for scanning. The bolts are perpendicular to the face with cracks but are almost at 85° to the scanning surface. A novel conical probe is designed to use the bolt as a core for the excitation (driver) coil, thereby increasing driving flux density, and to constrain probe positioning as it is swept around the bolt. Finite-element simulations are used to investigate influence of different parameters on LFEC impedance plane response. These include slope of the slanted surface, sample thickness, operating frequency, crack size, and edge effect for two different component edge shapes. Experimental measurements carried out at different frequencies on test samples, prepared with the same dimensions as actual flanges, were found to be in good agreement with computational models. Results indicate that LFEC is significantly affected by surrounding geometries, which therefore, need to be taken into account when inspecting for cracks.
Autors: Natheer Alatawneh;Peter Ross Underhill;Thomas W. Krause;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1568 - 1575
Publisher: IEEE
 
» Low-Frequency Noise in Hybrid-Phase- Microstructure ITO-Stabilized ZnO Thin-Film Transistors
Abstract:
Low-frequency noise (LFN) in hybrid-phase-microstructure ITO-stabilized ZnO thin-film transistors is investigated. The measured drain current noise power spectral densities obey the classical 1/ noise theory, with about 0.9. When - is low, the gate voltage dependent noise data closely follow the carrier number with correlated mobility fluctuation () model, and the average Hooge’s parameter in the channel is extracted to be about . Moreover, the contribution of contact resistance to LFN is further studied. Dominated by the channel and the contact, the normalized noise varies with two slopes (.x and 0) with an increase of the effective gate voltage. Finally, the normalized noise versus drain current results are simulated by considering contact resistance.
Autors: Yuan Liu;Sunbin Deng;Rongsheng Chen;Bin Li;Yun-Fei En;Yiqiang Chen;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 200 - 203
Publisher: IEEE
 
» Low-Frequency SAR Radiometric Calibration and Antenna Pattern Estimation by Using Stable Point Targets
Abstract:
In this paper, the synthetic aperture radar (SAR) calibration for low-frequency missions by means of stable point targets is presented. Calibration at low frequency involves the absolute radiometric calibration, the antenna pattern and pointing characterization and validation, and the distortion system parameters’ estimation. The use of traditional instrumentation, such as a polarimetric active radar calibrator, a corner reflector, or an active transponder, may be costly and can reduce the time the instrument is used for operational acquisitions. The purpose of this paper is to evaluate the potentiality in calibration of point targets for which the radar cross section and the time stability have been characterized. Given a calibration site, once that a set of the stable point targets have been detected by the analysis of an interferometric stack of SAR acquisitions, they may be used as passive calibrators for the validation of radiometry, elevation antenna pattern, and pointing estimation. We show that, although less targets are expected to be found in P- or L- band than in C- or X-band, a sufficient amount (about 250 targets per acquisition) can provide an accuracy in antenna pattern estimation of about 0.04 dB, if the target accuracy is 0.1 dB at .
Autors: Pietro Guccione;Michele Scagliola;Davide Giudici;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 635 - 646
Publisher: IEEE
 
» Low-Profile Spoof Surface Plasmon Polaritons Traveling-Wave Antenna for Near-Endfire Radiation
Abstract:
This letter proposes a low-profile and highly efficient endfire radiating traveling-wave antenna based on spoof surface plasmon polaritons (SSPPs) transmission line. The aperture is approximately , where is the space wavelength at the operational frequency 8 GHz. This antenna generates near-endfire radiation beams within 7.5–8.5 GHz. The maximum gain and total efficiency reach 9.2 dBi and , respectively. Measurement results are finally given to validate the proposed SSPPs antenna.
Autors: Abhishek Kandwal;Qingfeng Zhang;Xiao-Lan Tang;Louis Wy Liu;Ge Zhang;
Appeared in: IEEE Antennas and Wireless Propagation Letters
Publication date: Feb 2018, volume: 17, issue:2, pages: 184 - 187
Publisher: IEEE
 
» LRAGE: Learning Latent Relationships With Adaptive Graph Embedding for Aerial Scene Classification
Abstract:
The performance of scene classification relies heavily on the spatial and structural features that are extracted from high spatial resolution remote-sensing images. Existing approaches, however, are limited in adequately exploiting latent relationships between scene images. Aiming to decrease the distances between intraclass images and increase the distances between interclass images, we propose a latent relationship learning framework that integrates an adaptive graph with the constraints of the feature space and label propagation for high-resolution aerial image classification. To describe the latent relationships among scene images in the framework, we construct an adaptive graph that is embedded into the constrained joint space for features and labels. To remove redundant information and improve the computational efficiency, subspace learning is introduced to assist in the latent relationship learning. To address out-of-sample data, linear regression is adopted to project the semisupervised classification results onto a linear classifier. Learning efficiency is improved by minimizing the objective function via the linearized alternating direction method with an adaptive penalty. We test our method on three widely used aerial scene image data sets. The experimental results demonstrate the superior performance of our method over the state-of-the-art algorithms in aerial scene image classification.
Autors: Yuebin Wang;Liqiang Zhang;Xiaohua Tong;Feiping Nie;Haiyang Huang;Jie Mei;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 621 - 634
Publisher: IEEE
 
» LTE Multimedia Broadcast Multicast Service Provisioning Based on Robust Header Compression
Abstract:
One important issue that confronts network service providers is the need to provide reliable multimedia data service efficiently over cellular networks for a large number of subscribers under dynamic channel conditions. In long term evolution (LTE) networks, multimedia broadcast multicast service (MBMS) is a bandwidth efficient data service to simultaneously support multiple users at high bandwidth efficiency. In this paper, instead of considering spectrum resource allocation, we investigate MBMS provisioning for each mobile user based on the higher layer robust header compression (ROHC) consideration in response to user channel quality to reduce packet losses. We formulate a profit maximization problem for two different MBMS channel models and further propose a new MBMS assignment scheme for each user to be assigned a target MBMS with optimal ROHC parameters. We further develop a dynamic programming algorithm for user assignment and ROHC parameters optimization to achieve maximal profit with high spectrum resource utility. Our numerical results demonstrate substantial profit gain achieved by the proposed method in LTE systems.
Autors: Chen Jiang;Wenhao Wu;Zhi Ding;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1161 - 1172
Publisher: IEEE
 
» Luminous Flux and CCT Stabilization of White LED Device With a Bilevel Driver
Abstract:
The optical, color, electrical, and thermal properties of an LED devices are highly dependent on one another. The luminous flux variation and correlated color temperature (CCT) shifting of white LED sources is attributed to luminous efficacy and emission spectrum shifting with the electrical power and heat-dissipation power. An analysis model that includes the luminous flux, CCT, electrical power, and junction temperature of the white LED sources with bilevel driver is proposed in this paper. The proposed model can descript that the stablized luminous flux and CCT of the white LED system with bilevel driver is a result of the complex interactions among the given electrical power of bilevel, duty cycle, thermal resistances, junction temperature, and the physical parameters of the LED sources. Reduction variation of CCT and luminous flux of the white LED device with bilevel driver over a dimming range has been practically achieved. The proposed method can be easily adopted for improving the CCT and luminous flux stabilization of the white LED device with a bilevel driver.
Autors: Huanting Chen;Xiaofang Zhou;Shuo Lin;Jinhai Liu;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 10
Publisher: IEEE
 
» Machine Learned Replacement of N-Labels for Basecalled Sequences in DNA Barcoding
Abstract:
This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to replace with basecalls (A,C,G,T). An N-label correction is defined given an additional read of the same sequence, and a human finished sequence. Corrections are added to the dataset when an alignment determines the additional read and human agree on the identity of the N-label. KB must also rate the replacement with quality value of in the additional read. Corrections are only available during system training. Developing the system, nearly 850,000 N-labels are obtained from Barcode of Life Datasystems, the premier database of genetic markers called DNA Barcodes. Increasing the number of correct bases improves reference sequence reliability, increases sequence identification accuracy, and assures analysis correctness. Keeping with barcoding standards, our system maintains an error rate of percent. Our system only applies corrections when it estimates low rate of error. Tested on this data, our automation selects and recovers: 79 percent of N-labels from COI (animal barcode); 80 percent from matK and rbcL (plant barcodes); and 58 percent from non-protein-coding sequences (across eukaryotes).
Autors: Eddie Y. T. Ma;Sujeevan Ratnasingham;Stefan C. Kremer;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Feb 2018, volume: 15, issue:1, pages: 191 - 204
Publisher: IEEE
 
» Machine Learning for Performance Prediction in Mobile Cellular Networks
Abstract:
In this paper, we discuss the application of machine learning techniques for performance prediction problems in wireless networks. These problems often involve using existing measurement data to predict network performance where direct measurements are not available. We explore the performance of existing machine learning algorithms for these problems and propose a simple taxonomy of main problem categories. As an example, we use an extensive real-world drive test data set to show that classical machine learning methods such as Gaussian process regression, exponential smoothing of time series, and random forests can yield excellent prediction results. Applying these methods to the management of wireless mobile networks has the potential to significantly reduce operational costs while simultaneously improving user experience. We also discuss key challenges for future work, especially with the focus on practical deployment of machine learning techniques for performance prediction in mobile wireless networks.
Autors: Janne Riihijarvi;Petri Mahonen;
Appeared in: IEEE Computational Intelligence Magazine
Publication date: Feb 2018, volume: 13, issue:1, pages: 51 - 60
Publisher: IEEE
 
» Machine Learning Techniques for Coherent CFAR Detection Based on Statistical Modeling of UHF Passive Ground Clutter
Abstract:
Ultra high frequency (UHF) passive ground clutter statistical models were determined from real data acquired by a passive radar for the design of approximations to the Neyman–Pearson detector based on machine learning techniques. The cross-ambiguity function was the input space without any preprocessing. The Gaussian model was proved to be suitable for high Doppler values. Other models were proposed for Doppler close to zero, where ground clutter and low bistatic Doppler targets concentrate. Likelihood ratio detectors were built for this Doppler region, and a neural-network-based adaptive threshold technique was designed for fulfilling false alarm requirements throughout all the input space. The proposed scheme outperformed a conventional passive radar one and could be used as a reference for future designs.
Autors: Nerea del-Rey-Maestre;María-Pilar Jarabo-Amores;David Mata-Moya;José-Luis Bárcena-Humanes;Pedro Gómez del Hoyo;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Feb 2018, volume: 12, issue:1, pages: 104 - 118
Publisher: IEEE
 
» Machine Learning-Based Temperature Prediction for Runtime Thermal Management Across System Components
Abstract:
Elevated temperatures limit the peak performance of systems because of frequent interventions by thermal throttling. Non-uniform thermal states across system nodes also cause performance variation within seemingly equivalent nodes leading to significant degradation of overall performance. In this paper we present a framework for creating a lightweight thermal prediction system suitable for run-time management decisions. We pursue two avenues to explore optimized lightweight thermal predictors. First, we use feature selection algorithms to improve the performance of previously designed machine learning methods. Second, we develop alternative methods using neural network and linear regression-based methods to perform a comprehensive comparative study of prediction methods. We show that our optimized models achieve improved performance with better prediction accuracy and lower overhead as compared with the Gaussian process model proposed previously. Specifically we present a reduced version of the Gaussian process model, a neural network–based model, and a linear regression–based model. Using the optimization methods, we are able to reduce the average prediction errors in the Gaussian process from C to C. We also show that the newly developed models using neural network and Lasso linear regression have average prediction errors of C and C respectively. The prediction overheads are 0.22, 0.097, and 0.026 ms per prediction for reduced Gaussian process, neural network, and Lasso linear regression models, respectively, compared with 0.57 ms per prediction for the previous Gaussian process model. We have implemented our proposed thermal prediction models on a two-node system configuration to help identify the optimal task placement. The task placement identified by the models reduces the average system temperature by up to C without any performance degradation. Furthermore, these models respectively achieve 75, 82.5, and 74.17 percent success rates in correctly pointing to those task placements with better thermal response, compared with 72.5 percent success for the original model in achieving the same objective. Finally, we extended our analysis to a 16-node system and we were able to train models and execute them in real time to guide task migration and achieve on average 17 percent reduction in the overall system cooling power.
Autors: Kaicheng Zhang;Akhil Guliani;Seda Ogrenci-Memik;Gokhan Memik;Kazutomo Yoshii;Rajesh Sankaran;Pete Beckman;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Feb 2018, volume: 29, issue:2, pages: 405 - 419
Publisher: IEEE
 
» Machine-learning method for quality of transmission prediction of unestablished lightpaths
Abstract:
Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of capital importance for an optimized design of optical networks. Due to the continuous advances in optical transmission, the number of design parameters available to system engineers (e.g., modulation formats, baud rate, code rate, etc.) is growing dramatically, thus significantly increasing the alternative scenarios for lightpath deployment. As of today, existing (pre-deployment) estimation techniques for light-path QoT belong to two categories: “exact” analytical models estimating physical-layer impairments, which provide accurate results but incur heavy computational requirements, and margined formulas, which are computationally faster but typically introduce high link margins that lead to underutilization of network resources. In this paper, we explore a third option, i.e., machine learning (ML), as ML techniques have already been successfully applied for optimization and performance prediction of complex systems where analytical models are hard to derive and/ or numerical procedures impose high computational burden. We investigate a ML classifier that predicts whether the bit error rate of unestablished lightpaths meets the required system threshold based on traffic volume, desired route, and modulation format. The classifier is trained and tested on synthetic data and its performance is assessed over different network topologies and for various combinations of classification features. Results in terms of classifier accuracy are promising and motivate further investigation over real field data.
Autors: Cristina Rottondi;Luca Barletta;Alessandro Giusti;Massimo Tornatore;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Feb 2018, volume: 10, issue:2, pages: A286 - A297
Publisher: IEEE
 
» Macrodiversity in Cellular Networks With Random Blockages
Abstract:
Blocking objects (blockages) between a transmitter and receiver cause wireless communication links to transition from line-of-sight (LOS) to non-LOS propagation, which can greatly reduce the received power, particularly at the higher frequencies such as millimeter wave. We consider a cellular network in which a mobile user attempts to connect to two or more base stations (BSs) simultaneously, to increase the probability of at least one LOS link, which is a form of macrodiversity. We develop a framework for determining the LOS probability as a function of the number of BSs, when taking into account the correlation between blockages: for example, a single blockage close to the device—including the user’s own body—could block multiple BSs. We consider the impact of the size of blocking objects on the system’s th order LOS probability and show that macrodiversity gains are higher when the blocking objects are small. We also show that the BS density must scale as the square of the blockage density to maintain a given level of LOS probability.
Autors: Abhishek K. Gupta;Jeffrey G. Andrews;Robert W. Heath;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 996 - 1010
Publisher: IEEE
 
» MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention
Abstract:
Android users are constantly threatened by an increasing number of malicious applications (apps), generically called malware. Malware constitutes a serious threat to user privacy, money, device and file integrity. In this paper we note that, by studying their actions, we can classify malware into a small number of behavioral classes, each of which performs a limited set of misbehaviors that characterize them. These misbehaviors can be defined by monitoring features belonging to different Android levels. In this paper we present MADAM, a novel host-based malware detection system for Android devices which simultaneously analyzes and correlates features at four levels: kernel, application, user and package, to detect and stop malicious behaviors. MADAM has been specifically designed to take into account those behaviors that are characteristics of almost every real malware which can be found in the wild. MADAM detects and effectively blocks more than 96 percent of malicious apps, which come from three large datasets with about 2,800 apps, by exploiting the cooperation of two parallel classifiers and a behavioral signature-based detector. Extensive experiments, which also includes the analysis of a testbed of 9,804 genuine apps, have been conducted to show the low false alarm rate, the negligible performance overhead and limited battery consumption.
Autors: Andrea Saracino;Daniele Sgandurra;Gianluca Dini;Fabio Martinelli;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Feb 2018, volume: 15, issue:1, pages: 83 - 97
Publisher: IEEE
 
» Magic Train: Design of Measurement Methods against Bandwidth Inflation Attacks
Abstract:
Bandwidth measurement is important for many network applications and services, such as peer-to-peer networks, video caching and anonymity services. To win a bandwidth-based competition for some malicious purpose, adversarial Internet hosts may falsely announce a larger network bandwidth. Some preliminary solutions have been proposed to this problem. They can either evade the bandwidth inflation by a consensus view (i.e., opportunistic bandwidth measurements) or detect bandwidth frauds via forgeable tricks (i.e., detection through bandwidth's CDF symmetry). However, smart adversaries can easily remove the forgeable tricks and report an equally larger bandwidth to avoid the consensus analyses. To defend against the smart bandwidth inflation frauds, we design magic train, a new measurement method which combines an unpredictable packet train with estimated round-trip time (RTT) for detection. The inflation behaviors can be detected through highly contradictory bandwidth results calculated using different magic trains or a train's different segments, or large deviation between the estimated RTT and the RTT reported by the train's first packet. Being an uncooperative measurement method, magic train can be easily deployed on the Internet. We have implemented the magic train using RAW socket and LibPcap, and evaluated the implementation in a controlled testbed and the Internet. The results have successfully confirmed the effectiveness of magic train in detecting and preventing smart bandwidth inflation attacks.
Autors: Peng Zhou;Rocky K. C. Chang;Xiaojing Gu;Minrui Fei;Jianying Zhou;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Feb 2018, volume: 15, issue:1, pages: 98 - 111
Publisher: IEEE
 
» Magnet-Less Circulators Based on Spatiotemporal Modulation of Bandstop Filters in a Delta Topology
Abstract:
In this paper, we discuss the design rationale and guidelines to build magnet-less circulators based on spatiotemporal modulation of resonant junctions consisting of first-order bandstop filters connected in a delta topology. Without modulation, the junction does not allow transmission between its ports; however, when the natural oscillation frequencies of the constituent filters are modulated in time with a suitable phase pattern, a synthetic angular-momentum bias can be effectively imparted to the junction and a transmission window opens at one of the output ports, thus realizing a circulator. We develop a rigorous small-signal linear model and find analytical expressions for the harmonic -parameters of the proposed circuit, which significantly facilitate the design process. We validate the theory with simulations and further discuss the large-signal response, including power handling, nonlinearity, and noise performance. Finally, we present measured results with unprecedented performance in all metrics for a printed circuit board prototype using off-the-shelf discrete components.
Autors: Ahmed Kord;Dimitrios L. Sounas;Andrea Alù;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 911 - 926
Publisher: IEEE
 
» Magnetic Field-Assisted Radiation Enhancement From a Large Aperture Photoconductive Antenna
Abstract:
The generation of terahertz radiation using photoconductive antennas is becoming very popular. Several experimental and simulation studies have been performed to study the characteristics of the photoconductive antenna (PCA). Although various methods have been proposed to increase the radiated power from it, the radiated power remains very low. In this paper, we present an analytical study of improving the radiated power from a large aperture PCA using an external magnetic field source. The transit time behavior of the carriers is computed using the basic semiconductor carrier dynamics model, including the transient mobilities with the dependencies on the electric field and carrier’s concentration. Analytical studies show that substantial enhancement in the radiated field can be achieved when such external magnetic field is applied. Furthermore, the polarity of the radiated field depends on the orientation of the applied magnetic field. The results obtained from analytical calculations exhibit similar behavior as reported in some experimental results.
Autors: Jitendra Prajapati;Mrinmoy Bharadwaj;Amitabh Chatterjee;Ratnajit Bhattacharjee;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 678 - 687
Publisher: IEEE
 
» Magnetic hammer propels tiny medical bot
Abstract:
A tiny robot that jackhammers its way through the body sounds like the stuff of science fiction nightmares. But such a robot exists, and it could play an important role in the future of medicine.
Autors: Jeremy Hsu;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 10 - 11
Publisher: IEEE
 
» Magnetic Nanoparticle-Based Nano-Grating Guided-Mode Resonance Biosensors
Abstract:
Biomolecular detection systems based on monitoring changes in the refractive indices of functionalized surfaces are promising for applications as chemical and biological sensors. Here, we describe the design and figures of merit of our refractive index-based guided-mode resonance (GR) biosensor consisting of thin film silicon nitride sub-wavelength nano-gratings. The sensitivity of our nano-grating GR sensor was experimentally determined to be 59.3 nm per refractive index unit. We describe how the wavelength for maximum intensity of diffraction (peak wavelength) of nano-gratings was affected when functionalized magnetic nanoparticles (MNPs) were attached onto GR sensor surfaces. Moreover, we demonstrate with avidin-biotin model experiments that attaching MNPs to sensor surfaces enhances the dynamic range of detection of the GR system detection. The peak wavelength value (PWV) shifted by 0.35 nm in the case of avidin with a concentration of avidin 400 nmol/L immobilized on the sensor surface. In contrast, we achieved a 1.41 nm PWV shift after adding 5% MNPs to the solution of avidin. Not only did the MNPs enhance the dynamic range of detection, but also magnetically induced interaction of avidin-biotin significantly reduced the detection time.
Autors: Ryoji Yukino;Jaiyam Sharma;Tsukasa Takamura;Joby Joseph;Adarsh Sandhu;
Appeared in: IEEE Transactions on Magnetics
Publication date: Feb 2018, volume: 54, issue:2, pages: 1 - 6
Publisher: IEEE
 
» Magnetic Resonance Mediated Radiofrequency Ablation
Abstract:
To introduce magnetic resonance mediated radiofrequency ablation (MR-RFA), in which the MRI scanner uniquely serves both diagnostic and therapeutic roles. In MR-RFA scanner-induced RF heating is channeled to the ablation site via a Larmor frequency RF pickup device and needle system, and controlled via the pulse sequence. MR-RFA was evaluated with simulation of electric and magnetic fields to predict the increase in local specific-absorption-rate (SAR). Temperature-time profiles were measured for different configurations of the device in agar phantoms and ex vivo bovine liver in a 1.5 T scanner. Temperature rise in MR-RFA was imaged using the proton resonance frequency method validated with fiber-optic thermometry. MR-RFA was performed on the livers of two healthy live pigs. Simulations indicated a near tenfold increase in SAR at the RFA needle tip. Temperature-time profiles depended significantly on the physical parameters of the device although both configurations tested yielded temperature increases sufficient for ablation. Resected livers from live ablations exhibited clear thermal lesions. MR-RFA holds potential for integrating RF ablation tumor therapy with MRI scanning. MR-RFA may add value to MRI with the addition of a potentially disposable ablation device, while retaining MRI’s ability to provide real time procedure guidance and measurement of tissue temperature, perfusion, and coagulation.
Autors: Yik-Kiong Hue;Alexander R. Guimaraes;Ouri Cohen;Erez Nevo;Abraham Roth;Jerome L. Ackerman;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 417 - 427
Publisher: IEEE
 
» Magnetic Resonance RF Pulse Design by Optimal Control With Physical Constraints
Abstract:
Optimal control approaches have proved useful in designing RF pulses for large tip-angle applications. A typical challenge for optimal control design is the inclusion of constraints resulting from physiological or technical limitations that assure the realizability of the optimized pulses. In this paper, we show how to treat such inequality constraints, in particular, amplitude constraints on the B1 field, the slice-selective gradient, and its slew rate, as well as constraints on the slice profile accuracy. For the latter, a pointwise profile error and additional phase constraints are prescribed. Here, a penalization method is introduced that corresponds to a higher order tracking instead of the common quadratic tracking. The order is driven to infinity in the course of the optimization. We jointly optimize for the RF and slice-selective gradient waveform. The amplitude constraints on these control variables are treated efficiently by semismooth Newton or quasi-Newton methods. The method is flexible, adapting to many optimization goals. As an application, we reduce the power of refocusing pulses, which is important for spin echo-based applications with a short echo spacing. Here, the optimization method is tested in numerical experiments for reducing the pulse power of simultaneous multislice refocusing pulses. The results are validated by phantom and in-vivo experiments.
Autors: Armin Rund;Christoph Stefan Aigner;Karl Kunisch;Rudolf Stollberger;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 461 - 472
Publisher: IEEE
 
» Magnetic-Ionic-Liquid-Functionalized Photonic Crystal Fiber for Magnetic Field Detection
Abstract:
A compact optical fiber magnetic field sensor based on a magnetic-ionic-liquid-functionalized photonic crystal fiber (PCF) has been proposed and experimentally demonstrated. The magnetic field sensor was fabricated by splicing an index-guiding PCF having one magnetic-ionic-liquid-infiltrated (MIL-infiltrated) air hole in the innermost layer infiltrated with conventional single-mode fibers. The transmission spectral magnetic response of the proposed sensor have been measured and theoretically analyzed. Owing to the effective interaction between the MIL and transmission light as well as the controllable attenuation property of MIL, the magnetic field sensitivity reaches up to −0.01991 dB/Oe for a relatively linear magnetic intensity range of 0 to 440 Oe.
Autors: Hu Liang;Yange Liu;Hongye Li;Simeng Han;Hongwei Zhang;Yonghua Wu;Zhi Wang;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 359 - 362
Publisher: IEEE
 
» Magnetodynamic Study of Spin Resonances in Cylindrical and Spherical YIG Samples
Abstract:
Rigorous magnetodynamic (MD) study presented in this paper reveals what seems to be the real nature of ferromagnetic resonances occurring in gyromagnetic samples situated in larger resonant cavities. Experiments were performed with cylindrical and spherical YIG samples inserted into either cylindrical dielectric resonator or typical rectangular cavity. It is shown that the dominant mode present in the YIG sample, which was identified as the mode, satisfies the magnetic plasmon resonance condition defined by the effective permeability for cylindrical samples or for spherical samples. Experiments confirmed the existence of surface resonances, identified as magnetic plasmons, and volume resonances. Comparison between the MD model, the quasi-magnetostatic model, and the perturbation theory was performed and limitations of the approximate approaches are shown.
Autors: Jerzy Krupka;Pavlo Aleshkevych;Bartlomiej Salski;Pawel Kopyt;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 803 - 812
Publisher: IEEE
 
» Maintenance of Libration Point Orbit in Elliptic Sun–Mercury Model
Abstract:
The maintenance of the nominal multirevolution elliptic halo orbit, whose special features can benefit mercurial explorations, is first investigated through Monte–Carlo simulations in the elliptic Sun–Mercury model, and then validated in the high-fidelity ephemeris model. The receding horizon control strategy solved by the indirect Radau pseudospectral method demonstrates that the orbit can be maintained robustly with respect to very large initial deviations. Moreover, the result proves that the elliptic Sun–Mercury model is an accurate approximation.
Autors: Hao Peng;Yuxin Liao;Xiaoli Bai;Shijie Xu;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 144 - 158
Publisher: IEEE
 
» Making sleep study instrumentation more unobtrusive
Abstract:
Quality sleep is important for sustenance of good health. With changing life style and work cultures, it is increasingly becoming a prized thing. No wonder, sleep related problems are among the most widely reported health concerns. This is bringing sleep labs, their instrumentation and related matters into the spotlight. The gold standard instrumentation for sleep studies is polysomnography (PSG). It entails recording a multitude of physiological signals, including electroencephalogram (EEG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), respiration, pulse oxygen and limb movement. Apart from system complexity, cost and the operational issues of PSG, patient inconvenience is also a cause of concern and therefore, a fertile avenue for research. Research and developments in various other technologies are being applied to instrumentation for sleep studies. Insights into the complex behavior of physiological systems, applications of advanced computational techniques, shrinking electronics and advanced wireless technologies are being applied to sleep study instrumentation. After a short review of standard polysomnography, this article takes a look at the research directions that promise a new era of patient-friendly sleep study instrumentation.
Autors: Jaspal Singh;R. K. Sharma;
Appeared in: IEEE Instrumentation & Measurement Magazine
Publication date: Feb 2018, volume: 21, issue:1, pages: 50 - 53
Publisher: IEEE
 
» Managing Programmers, with Ron Lichty
Abstract:
Veteran software manager Ron Lichty joins Nate Black to share his insights on managing software engineers. Nate and Ron delve into what about this is hard, how to grow as a manager, and what makes highly performing teams.
Autors: Nate Black;
Appeared in: IEEE Software
Publication date: Feb 2018, volume: 35, issue:1, pages: 117 - 120
Publisher: IEEE
 
» Managing Thermally Derated Torque of an Electrified Powertrain Through LPV Control
Abstract:
Vehicle with electrified powertrains exhibit degraded performance when operated in hot environments. When the operating and surrounding temperatures rise, an electric drive suffers from torque derating as its parameters change. This paper proposes a linear parameter varying (LPV) based observer controller pair to address this problem. The feedback field oriented control (FOC) is the most commonly adopted instantaneous torque control method for an electrified powertrain drive system. The flux and torque performance of a conventional feedback FOC deteriorates under the vast uncertainties in rotor and stator resistance due to temperature variations during electric vehicle (EV) operation. To cater for these uncertain scenarios, a robust closed-loop observer is designed to estimate the thermally derated torque and flux. The stability of the whole LPV scheme is established. The efficacy of the proposed algorithm is demonstrated for an EV operating in federal urban driving schedule with a dynamic temperature profile. The nonlinear simulation results confirm the LPV observer capability to successfully estimate the flux and derated torque in an EV drive system. The proposed technique, after validating in simulation environment, is verified experimentally on an induction machine drive controlled by NI myRIO-1900.
Autors: Athar Hanif;Aamer I. Bhatti;Qadeer Ahmed;
Appeared in: IEEE/ASME Transactions on Mechatronics
Publication date: Feb 2018, volume: 23, issue:1, pages: 364 - 376
Publisher: IEEE
 
» Mapping Double and Single Crop Paddy Rice With Sentinel-1A at Varying Spatial Scales and Polarizations in Hanoi, Vietnam
Abstract:
Paddy Rice is the prevalent land cover in the mosaicked landscape of the Hanoi Capital Region, Vietnam. In this study, we map double and single crop rice in Hanoi using a random forest algorithm and a time-series of Sentinel-1 SAR imagery at 10 and 20 m resolution using VV-only, VH-only, and both polarizations. We compare spatial and areal variation and quantify input band importance, estimate crop growth stages, estimate rice field/collective metrics using Fragstats with image segmentation, and highlight the importance of the results for land use and land cover. Results suggest double crop rice ranged from 208 000 to 220 000 ha with 20-m resolution imagery accounting for the most area in all polarizations. Based on accuracy assessment, we found 10 m data for VV/VH to have highest overall accuracy (93.5%, ±1.33%), while VV at 10 and 20 m had lowest overall accuracies (90.9%, ±1.57; 91.0%, ±2.75). Mean decrease in accuracy suggests for all but VV at 10 m, data from harvest and flooding stages are most critical for classification. Results suggest 20 m data for both VV and VH overestimates rice land cover, however 20 m data may be indicative of rice land use. Analysis of growing season suggests average estimated length of 93–104 days for each season. Commune-level results suggest up to 20% coefficient of variation between VV10m and VH10m with significant spatial variation in rice area. Landscape metrics show rice fields are typically planted in groups of 3–4 fields with over 796 000 collectives and 2.69 million fields estimated in the study area.
Autors: Kristofer Lasko;Krishna Prasad Vadrevu;Vinh Tuan Tran;Christopher Justice;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 498 - 512
Publisher: IEEE
 
» Mapping Monthly Air Temperature in the Tibetan Plateau From MODIS Data Based on Machine Learning Methods
Abstract:
Detailed knowledge of air temperature ( ) is desired for various scientific applications. However, in the Tibetan Plateau (TP), the meteorologically observed is limited due to the low density and uneven distribution of stations. This paper aims to develop a 1-km resolution monthly mean dataset over the TP during 2001–2015 from remote sensing and auxiliary data. 11 environmental variables were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data, Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data and topographic index data. Ten machine learning algorithms were implemented and compared to determine the optimal model for Ta estimation in the TP. The Cubist algorithm outperformed other methods, having the highest accuracy and the lowest sensitivity to cloud contamination. To minimize the overfitting problem, a simple forward variable selection method was introduced and six variables were selected from the original 11 environmental variables. Among these six variables, nighttime land surface temperature (Ts) was the most important predictor, followed by elevation and solar radiance. The seasonal performance of the Cubist model was also assessed. The model had good accuracies in all four seasons, with the highest accuracy in winter (R2 = 0.98 and MAE = 0.63 °C) and the lowest accuracy in summer (R2 = 0.91 and MAE = 0.86 °C). Due to the gaps in MODIS data caused by cloud cover, there were 0.39% missing values in the estimated Ta. To improve the data integrity- Delaunay triangulation interpolation was applied to fill the missing Ta values. The final monthly (2001–2015) Ta dataset had an overall accuracy of RMSE = 1.00 °C and MAE = 0.73 °C. It provides valuable information for climate change assessment and other environmental studies in the TP.
Autors: Yongming Xu;Anders Knudby;Yan Shen;Yonghong Liu;
Appeared in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication date: Feb 2018, volume: 11, issue:2, pages: 345 - 354
Publisher: IEEE
 
» Mapping the Spatiotemporal Dynamics of Europe’s Land Surface Temperatures
Abstract:
The land surface temperature (LST) drives many terrestrial biophysical processes and varies rapidly in space and time primarily due to the earth’s diurnal and annual cycles. Models of the diurnal and annual LST cycle retrieved from satellite data can be reduced to several gap-free parameters that represent the surface’s thermal characteristics and provide a generalized characterization of the LST temporal dynamics. In this letter, we use such an approach to map Europe’s annual and diurnal LST dynamics. In particular, we reduce a five-year time series (2009–2013) of diurnal LST from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to 48 sets of half-hourly annual cycle parameters (ACPs), namely, the mean annual LST, the yearly amplitude of LST, and the LST phase shift from the spring equinox. The derived data provide a complete representation of how mainland Europe responds to the heating of the sun and the nighttime LST decay and reveal how Europe’s biogeographic regions differ in that respect. We further argue that the SEVIRI ACP can provide an observation-based spatially consistent background for studying and characterizing the thermal behavior of the surface and also a data set to support climate classification at a finer spatial resolution.
Autors: Panagiotis Sismanidis;Benjamin Bechtel;Iphigenia Keramitsoglou;Chris T. Kiranoudis;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 202 - 206
Publisher: IEEE
 
» Maritime Moving Target Indication Using Passive GNSS-Based Bistatic Radar
Abstract:
This paper is a first introduction to the concept of using global navigation satellite systems (GNSS) as illuminators of opportunity in a passive bistatic real-time radar system for maritime target indication applications. An overview of the system concept and the signal processing algorithms for moving target indication is provided. To verify the feasibility of the system implementation as well as test the developed signal processing algorithms, an experimental test bed was developed and the appropriate experimental campaign with the new Galileo satellites and a ferry as the target was carried out. The results confirm the system concept and its potential for multistatic operation, with the ferry being detected simultaneously by two satellites.
Autors: Hui Ma;Michail Antoniou;Debora Pastina;Fabrizio Santi;Federica Pieralice;Marta Bucciarelli;Mikhail Cherniakov;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 115 - 130
Publisher: IEEE
 
» Max–Min Fair Transmit Precoding for Multi-Group Multicasting in Massive MIMO
Abstract:
This paper considers the downlink precoding for physical layer multicasting in massive multiple-input multiple-output (MIMO) systems. We study the max–min fairness (MMF) problem, where channel state information at the transmitter is used to design precoding vectors that maximize the minimum spectral efficiency (SE) of the system, given fixed power budgets for uplink training and downlink transmission. Our system model accounts for channel estimation, pilot contamination, arbitrary path-losses, and multi-group multicasting. We consider six scenarios with different transmission technologies (unicast and multicast), different pilot assignment strategies (dedicated or shared pilot assignments), and different precoding schemes (maximum ratio transmission and zero forcing), and derive achievable spectral efficiencies for all possible combinations. Then, we solve the MMF problem for each of these scenarios, and for any given pilot length, we find the SE maximizing uplink pilot and downlink data transmission policies, all in closed forms. We use these results to draw a general guideline for massive MIMO multicasting design, where for a given number of base station antennas, number of users, and coherence interval length, we determine the multicasting scheme that shall be used.
Autors: Meysam Sadeghi;Emil Björnson;Erik G. Larsson;Chau Yuen;Thomas L. Marzetta;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1358 - 1373
Publisher: IEEE
 
» MBSPEX and PEXORNET—Linux Device Drivers for PCIe Optical Receiver DAQ and Control
Abstract:
The GSI PCI express (PCIe) optical receiver (PEXOR) family PCIe boards are used as an interface for data acquisition (DAQ) from various detector front ends, linked by up to four chains of optical fiber connections. Communication with the front-end hardware is handled by the proprietary gigabit optical serial interface protocol. A trigger module trigger for pexor extends the PEXOR by additional signal connections for triggered DAQ. For several years, the PEXOR boards have been used with the DAQ framework multibranch system (MBS). On a Linux x-86 platform, the device driver software mbspex implements concurrent access to the PEXOR front ends from MBS DAQ and from separate control applications, such as the command line tool gosipcmd or hardware specific configuration graphical user interfaces. Besides the established character driver mbspex, a network driver pexornet has been developed to evaluate a lightweight DAQ system with readout from PEXOR via a user datagram protocol (UDP) socket. Therefore, common network tools can be applied for driver configuration and data debugging. Moreover, the gosipcmd tool and its adjusted application programming interface library are fully applicable also for pexornet. A simple example DAQ application with pexornet UDP readout has been implemented with the software framework DAQ backbone core (DABC), delivering the same data file format and online monitoring capabilities as MBS. Readout performance of a test setup has been measured both with MBS/mbspex and with DABC/pexornet.
Autors: Jörn Adamczewski-Musch;Nikolaus Kurz;Sergei Linev;
Appeared in: IEEE Transactions on Nuclear Science
Publication date: Feb 2018, volume: 65, issue:2, pages: 788 - 795
Publisher: IEEE
 
» MDP-Based Model for Interest Scheduling in IoT-NDN Environment
Abstract:
Named data networking (NDN) is a novel paradigm that can acknowledge the unprecedented increase in the volume of global IoT traffic which initiates a new network forwarding plane. We propose and evaluate a Markov decision process (MDP)-based scheduler to forward diverse IoT Interests to fitting interfaces in an NDN router to fetch Data with less round trip time (RTT), to meet latency requisites. Simulation results of our MDP model show scheduling Interests to right interfaces reduce the RTT value by 25–30% than existing forwarding strategies. The delay is around 30 ms for higher density of traffic comparatively less than other existing work.
Autors: Shapna Muralidharan;Abhishek Roy;Navrati Saxena;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 232 - 235
Publisher: IEEE
 
» Measurement of Pressure Drop and Water Holdup in Vertical Upward Oil-in-Water Emulsions
Abstract:
This paper aims to experimentally investigate pressure drop and water holdup in vertical upward oil-in-water emulsions. As a key factor to extract water holdup with differential pressure method, friction factor is complicatedly associated with the Reynolds number of mixed fluid. However, due to the fact that oil and water phase cannot be easily separated in emulsions, the traditional quick-closing valve (QCV) method is incapable of determining water holdup, which is imperative to determine the Reynolds number of mixed fluid. In this paper, regarded as an auxiliary measurement method, an arc type conductivity probe (ATCP) is utilized to derive water holdup parameter. Combining water holdup and differential pressure information, we extract friction factor and analyze its relationship with the Reynolds number of mixed fluid. Besides, drag reduction phenomena in surfactant aqueous solution and oil-in-water emulsions are discussed as well. Finally, water holdup is predicted using differential pressure information and experimental expression of friction factor, the result of which proves the effectiveness of differential pressure method for the measurement of water holdup in oil-in-water emulsions.
Autors: Yunfeng Han;Ningde Jin;Yingyu Ren;Yuansheng He;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1703 - 1713
Publisher: IEEE
 
» Measurements and Analysis of Angular Characteristics and Spatial Correlation for High-Speed Railway Channels
Abstract:
Spatial characteristics of the propagation channel have a vital impact on the application of multi-antenna techniques. This paper analyzes angular characteristics and the spatial correlation for high-speed railway (HSR) channels, based on a novel moving virtual antenna array (MVAA) measurement scheme. The principle of the MVAA scheme is deeply investigated and is further verified by a theoretical geometry-based stochastic model. Using the MVAA scheme, virtual single-input multiple-output (SIMO) channel impulse response data are derived from single-antenna measurements in typical HSR scenarios, involving viaduct, cutting, and station. Based on the SIMO channel data, angle of arrival is extracted according to the unitary estimation of signal parameters by the rotational invariance techniques algorithm, and is compared with the theoretical result. Moreover, power angular spectrum and root mean square (rms) angular spread (AS) are provided, and the rms AS results are statistically modeled and comprehensively compared. In addition, spatial correlation is calculated and analyzed, and a rms AS-dependent spatial correlation model is newly proposed to describe the relationship between the angular dispersion and the spatial correlation. The presented results could be used in multi-antenna channel modeling and will facilitate the assessment of multi-antenna technologies for future HSR mobile communication systems.
Autors: Tao Zhou;Cheng Tao;Sana Salous;Liu Liu;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 357 - 367
Publisher: IEEE
 
» Measuring the Impact of Code Dependencies on Software Architecture Recovery Techniques
Abstract:
Many techniques have been proposed to automatically recover software architectures from software implementations. A thorough comparison among the recovery techniques is needed to understand their effectiveness and applicability. This study improves on previous studies in two ways. First, we study the impact of leveraging accurate symbol dependencies on the accuracy of architecture recovery techniques. In addition, we evaluate other factors of the input dependencies such as the level of granularity and the dynamic-bindings graph construction. Second, we recovered the architecture of a large system, Chromium, that was not available previously. Obtaining the ground-truth architecture of Chromium involved two years of collaboration with its developers. As part of this work, we developed a new submodule-based technique to recover preliminary versions of ground-truth architectures. The results of our evaluation of nine architecture recovery techniques and their variants suggest that (1) using accurate symbol dependencies has a major influence on recovery quality, and (2) more accurate recovery techniques are needed. Our results show that some of the studied architecture recovery techniques scale to very large systems, whereas others do not.
Autors: Thibaud Lutellier;Devin Chollak;Joshua Garcia;Lin Tan;Derek Rayside;Nenad Medvidović;Robert Kroeger;
Appeared in: IEEE Transactions on Software Engineering
Publication date: Feb 2018, volume: 44, issue:2, pages: 159 - 181
Publisher: IEEE
 
» Mechanical Thermal Noise in Micro-Machined Levitated Two-Axis Rate Gyroscopes
Abstract:
In this paper, mechanical thermal noise in micro-machined levitated two-axis rate gyroscopes (MLG) is comprehensively studied. Taking into account the gyroscopic nature and a type of electromagnetic levitation employed in MLG, effective damping coefficients are obtained for two cases corresponding to positive and negative angular position stiffness. According to obtained coefficients, expressions for the spectral density of the gyroscope noise floor and its angular random walk are derived. Moreover, an investigation of the response of an ideal levitated gyroscope to the fluctuating torque within the entire frequency domain shows a restriction of the detection of the measuring rate in order to preserve the same angular position stiffness. This response, a form of Johnson noise, provides an explanation of the mechanism of constraints in gyroscope resolution, which in turn limits the current performance of levitated gyroscopes. Also, using the Ising criterion, an alternative qualitative means to estimate the resolution is obtained. By joining the Johnson noise and Ising criterion techniques, a confidence range for the gyroscope resolution is proposed.
Autors: Kirill V. Poletkin;Jan G. Korvink;Vlad Badilita;
Appeared in: IEEE Sensors Journal
Publication date: Feb 2018, volume: 18, issue:4, pages: 1390 - 1402
Publisher: IEEE
 
» Mechatronic System to Help Visually Impaired Users During Walking and Running
Abstract:
Ambient assisted living and intelligent transportation systems are becoming strongly coupled. There is the necessity of improving the quality of life by developing inclusive mobility solutions for impaired people. In this paper, we focus on a monocular vision-based system to assist people during walking, jogging, and running in outdoor environments. The impaired user is guided along a path represented by a lane or line on a dedicated runway. We developed a set of image processing algorithms to extract lines/lanes to follow. The embedded system is based on a small camera and a board that is responsible for processing the images and communicating with the developed haptic device. The haptic device is formed by a set of two gloves equipped with vibration motors that drive the user to the right direction. The vibration sequences are generated according to a robotic-like controller, considering the user as a two wheel steering robot, where the rotational and translation velocity can be controlled. The results obtained show that the overall system is able to detect the right path and to provide the right stimuli to the user, by means of the gloves, up to a speed over 10 km/h.
Autors: Adriano Mancini;Emanuele Frontoni;Primo Zingaretti;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 649 - 660
Publisher: IEEE
 
» MECPASS: Distributed Denial of Service Defense Architecture for Mobile Networks
Abstract:
Distributed denial of service is one of the most critical threats to the availability of Internet services. A botnet with only 0.01 percent of the 50 billion connected devices in the Internet of Things is sufficient to launch a massive DDoS flooding attack that could exhaust resources and interrupt any target. However, the mobility of user equipment and the distinctive characteristics of traffic behavior in mobile networks also limit the detection capabilities of traditional anti-DDoS techniques. In this article, we present a novel collaborative DDoS defense architecture called MECPASS to mitigate the attack traffic from mobile devices. Our design involves two filtering hierarchies. First, filters at edge computing servers (i.e., local nodes) seek to prevent spoofing attacks and anomalous traffic near sources as much as possible. Second, global analyzers located at cloud servers (i.e., central nodes) classify the traffic of the entire monitored network and unveil suspicious behaviors by periodically aggregating data from the local nodes. We have explored the effectiveness of our system on various types of application- layer DDoS attacks in the context of web servers. The simulation results show that MECPASS can effectively defend and clean an Internet service provider core network from the junk traffic of compromised UEs, while maintaining the false-positive rate of its detection engine at less than 1 percent.
Autors: Van Linh Nguyen;Po-Ching Lin;Ren-Hung Hwang;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 118 - 124
Publisher: IEEE
 
» Meetings calendar
Abstract:
Provides a listing of future meetings.
Autors: Davide Fabiani;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Feb 2018, volume: 34, issue:1, pages: 68 - 70
Publisher: IEEE
 
» meGautz: A High Capacity, Fault-Tolerant and Traffic Isolated Modular Datacenter Network
Abstract:
The modular datacenter networks (MDCN) comprise inter- and intra-container networks. Although it simplifies the construction and maintenance of mega-datacenters, interconnecting hundreds of containers and supporting online data-intensive services is still challenging. In this paper, we present meGautz, which is the first inter-container network that isolates inter- and intra-container traffic, and it has the following advantages. First, meGautz offers uniform high capacity among servers in the different containers, and balances loads at the container, switch, and server levels. Second, it achieves traffic isolation and allocates bandwidth evenly. Therefore, even under an all-to-all traffic pattern, the inter- and intra-container networks can deal with their own flows without interfering with each other, and both can gain high throughput. meGautz hence improves the performance of both the entire MDCN and individual servers, for there is no performance loss caused by resource competition. Third, meGautz is the first to achieve as graceful performance degradation as computation and storage do. Results from theoretical analysis and experiments demonstrate that meGautz is a high-capacity, fault-tolerant, and traffic isolated inter-container network.
Autors: Feng Huang;Yiming Zhang;Dongsheng Li;Jiaxin Li;Jie Wu;Kaijun Ren;Deke Guo;Xicheng Lu;
Appeared in: IEEE Transactions on Services Computing
Publication date: Feb 2018, volume: 11, issue:1, pages: 117 - 130
Publisher: IEEE
 
» Memory Partitioning for Parallel Multipattern Data Access in Multiple Data Arrays
Abstract:
Memory bandwidth bottlenecks severely restrict parallel access of data elements from data arrays. To realize high throughput out of a relatively low bandwidth, memory partitioning algorithms have been proposed to separate data arrays into multiple memory banks, from which multiple data can be accessed in parallel. However, previous partitioning schemes only considered the case of single-pattern and single-array. In the case of multipattern and multiarray, the previous partitioning schemes will use too much time to find a partition solution and cause excessively high storage overhead. In this paper, we propose an efficient two-step memory partitioning strategy for multipattern data access in multiple arrays. First, a fast, low complexity and low overhead difference-based data splitting algorithm provides a multibank solution for multiple patterns access. Then an area-efficient bank merging algorithm merges those partitioned banks from different arrays which satisfy conflict-free requirement in order to reduce the area overhead caused by partitioning. Experimental results show that our data splitting algorithm saves up to 83.0% in searching time and reduces 39.4% storage overhead compared to the state-of-the-art approaches. With the further optimization of area-efficient bank merging, the memory area overhead are saved up to 18.9% and the total partitioning time are saved up to 45.6%.
Autors: Shouyi Yin;Zhicong Xie;Chenyue Meng;Peng Ouyang;Leibo Liu;Shaojun Wei;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Feb 2018, volume: 37, issue:2, pages: 431 - 444
Publisher: IEEE
 
» Memristor-Based Circuit Design for Multilayer Neural Networks
Abstract:
Memristors are promising components for applications in nonvolatile memory, logic circuits, and neuromorphic computing. In this paper, a novel circuit for memristor-based multilayer neural networks is presented, which can use a single memristor array to realize both the plus and minus weight of the neural synapses. In addition, memristor-based switches are utilized during the learning process to update the weight of the memristor-based synapses. Moreover, an adaptive back propagation algorithm suitable for the proposed memristor-based multilayer neural network is applied to train the neural networks and perform the XOR function and character recognition. Another highlight of this paper is that the robustness of the proposed memristor-based multilayer neural network exhibits higher recognition rates and fewer cycles as compared with other multilayer neural networks.
Autors: Yang Zhang;Xiaoping Wang;Eby G. Friedman;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Feb 2018, volume: 65, issue:2, pages: 677 - 686
Publisher: IEEE
 
» Message Passing Algorithms for Scalable Multitarget Tracking
Abstract:
Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum–product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models. We present message-passing-based multitarget tracking methods for single-sensor and multiple-sensor scenarios, and for a known and unknown number of targets. The presented methods can cope with clutter, missed detections, and an unknown association between targets and measurements. We also discuss the integration of message-passing-based probabilistic data association into existing multitarget tracking methods. The superior performance, low complexity, and attractive scaling properties of the presented methods are verified numerically. In addition to simulated data, we use measured data captured by two radar stations with overlapping fields-of-view observing a large number of targets simultaneously.
Autors: Florian Meyer;Thomas Kropfreiter;Jason L. Williams;Roslyn Lau;Franz Hlawatsch;Paolo Braca;Moe Z. Win;
Appeared in: Proceedings of the IEEE
Publication date: Feb 2018, volume: 106, issue:2, pages: 221 - 259
Publisher: IEEE
 
» Message-Passing Strategy for Joint User Association and Resource Blanking in HetNets
Abstract:
This paper develops a self-organizing approach to joint user association and resource blanking between network-tiers in highly dense heterogeneous networks (HetNets). HetNets that populate many small cells within each macrocell have been studied extensively as a promising solution to exponentially increasing traffic demands. To benefit from small cells, traffic loads are efficiently spread over the network through user association, and strong interference from macrocells are carefully controlled. A simple but very effective solution is resource blanking that partitions time slots into two orthogonal groups and dedicates them to macrocells and small cells exclusively. The underlying challenge is the distributed management of joint user association and resource blanking because a centralized coordination becomes intractable for highly dense HetNets. Unlike existing approaches, this paper aims at developing a distributed solution for this joint optimization task without relaxing nonlinear constraints or decoupling the joint optimization. To this target, a novel message-passing algorithm is developed that enables a fully distributed solution for the joint optimization. The presented approach includes consensus mechanism that determines the optimal macrocell blanking via the negotiation among base stations. Simulation results show that the developed algorithm provides very efficient solutions and outperforms existing techniques consistently.
Autors: Sang Hyun Lee;Illsoo Sohn;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1026 - 1037
Publisher: IEEE
 

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