Electrical and Electronics Engineering publications abstract of: 09-2017 sorted by title, page: 11

» Investigation on Passive Booster for Improving Magnetic Coupling of Metal Mounted Proximity Range HF RFIDs
Abstract:
In this paper, the design methodology, fabrication, and measurement of a passive circuit for increasing the read range of the near-field-communications (NFCs) gadget in handheld devices to read miniature metal mounted radio-frequency identification (RFID) are discussed. Since, the impedances at source and load are unknown, the conventional methods are not helpful for designing a proper communication. The proposed circuit is fabricated on thin flexible polyimide film hence; it can be simply attached to the back of handheld devices with arbitrary shape. Having only one discrete component in the circuit is another step toward low-cost devices. The magnetic coupling between the small metal mounted high-frequency (HF) RFID and the NFC coil are improved by adding two coils connected in parallel to each other resonating at 13.56 MHz. One coil is designed to be coupled to the NFC coil and the other one to the HF RFID. The operability of the system is investigated not only by standard measurement equipment like vector network analyzer but also utilizing different smartphones. The agreement between the simulation and practical results shows that the booster improves the read range significantly.
Autors: Hossein Saghlatoon;Rashid Mirzavand;Mohammad Mahdi Honari;Pedram Mousavi;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Sep 2017, volume: 65, issue:9, pages: 3401 - 3408
Publisher: IEEE
 
» Investigation on Self-Adjust Conductivity Modulation SOI-LIGBT Structure (SCM-LIGBT) for Monolithic High-Voltage IC
Abstract:
A novel composite device structure named self-adjust conductivity modulation lateral insulated gate bipolar transistor (SCM-LIGBT), including normal LIGBT region (NLT region), the EM-nMOS region (ENM region), and the series diode region (DIO region), is proposed in this paper. By adding the enhanced-mode nMOS region and the series diodes region, the parasitic NPN transistor (NPN) bipolar structure in the normal LIGBT structure can be triggered in on-state and the conductivity modulation is dramatically enhanced, which leads to the improvement on the current capability and the forward voltage. In addition, due to the base voltage of the parasitic NPN bipolar structure in the proposed device can be clamped at the forward threshold of the series diodes, therefore the latch-up issues can be immunized to guarantee the forward-biased safe operating area. Numerous simulations and measurements are presented to investigate the electrical characteristics of the proposed structure. The length of the fabrication SCM-LIGBT is , and the width of the DIO and NLT is 830 , while the width of the ENM is . The results demonstrate that the proposed SCM-LIGBT achieves a high-current capability ( of 2428 A/cm2 at V, a low on-state voltage drop of 1.15 V at A/cm2 with its breakdown voltage of 590 V.
Autors: Weifeng Sun;Zhuo Yang;Jing Zhu;Fangjuan Bian;Siyang Liu;Jian Chen;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3762 - 3767
Publisher: IEEE
 
» Investigation on the Worst Read Scenario of a ReRAM Crossbar Array
Abstract:
This paper disproves the worst read scenario of a ReRAM crossbar array. If the previously believed worst read scenario is not the worst one, the read margin evaluated based on the scenario can be incorrect. We explored for read scenario worse than the previously believed worst scenario by wisely sampling scenarios and iteratively searching for the worse one. In experiment, our algorithm successfully found the scenario worse than the previously believed one, disproving the previously believed worst read scenario. Our results show that the sensing window estimated by the incorrect previously believed worst scenario is 14 times as large as the estimation by the worst scenario found by our algorithm.
Autors: Yelim Youn;Kwangmin Kim;Jae-Yoon Sim;Hong-June Park;Byungsub Kim;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Sep 2017, volume: 25, issue:9, pages: 2402 - 2410
Publisher: IEEE
 
» Investigations of the Influence of PMSM Parameter Variations in Optimal Stator Current Design for Torque Ripple Minimization
Abstract:
Optimal stator current design has been widely investigated for torque ripple minimization of permanent magnet synchronous machines (PMSMs). The optimal current design requires accurate machine parameters including the permanent magnet flux and dq-axis inductances, which are varying during machine operation due to machine uncertainty. Therefore, this paper investigates how these machine parameter variations influence the optimal stator current design, and hence the torque ripple minimization performance. At first, torque ripple model-based analytical solution for optimal current design is introduced in this paper, which can theoretically reduce the torque ripple to zero. Then, machine parameter variations of a laboratory interior PMSM are tested and analyzed. It is found that the magnet flux under no load can be reduced by more than 10% from room temperature to the maximal operation temperature, and the inductance term (- ) can be reduced by more than 50% from no load to full load. Afterwards, analytical equations are derived to quantify the resultant torque ripples due to the variations of magnet flux, dq-axis inductances, and the cogging torque. Finally, the numerical and experimental studies are conducted to investigate the resultant torque ripples under different percentages of parameter variations.
Autors: Chunyan Lai;Guodong Feng;Kaushik Mukherjee;Narayan C. Kar;
Appeared in: IEEE Transactions on Energy Conversion
Publication date: Sep 2017, volume: 32, issue:3, pages: 1052 - 1062
Publisher: IEEE
 
» IP Addressing: Problem-Based Learning Approach on Computer Networks
Abstract:
The case study presented in this paper describes the pedagogical aspects and experience gathered while using an e-learning tool named IPA-PBL. Its main purpose is to provide additional motivation for adopting theoretical principles and procedures in a computer networks course. In the proposed model, the sequencing of activities of the learning process is grouped into three phases based on educational goals. In this way, the same tool is used on several courses with different curricula. In IPA-PBL, problem-based learning (PBL) is applied as a pedagogical strategy, as well as a set of concrete methods implemented in the software. Together with the pedagogical model, specific domain ontology is designed. In this way, the learner's knowledge can be analyzed in order to collect data necessary for the dynamic adaptation of system behavior. The results collected while using IPA-PBL are compared to those obtained without using the system. Statistical analysis, together with pertaining considerations and conclusions, are also presented in the paper.
Autors: Aleksandar Jevremovic;Goran Shimic;Mladen Veinovic;Nenad Ristic;
Appeared in: IEEE Transactions on Learning Technologies
Publication date: Sep 2017, volume: 10, issue:3, pages: 367 - 378
Publisher: IEEE
 
» Iron Losses Calculation of an Axial Flux Machine Based on Three-Dimensional FEA Results Corresponding to One-Sixth Electrical Period
Abstract:
This paper describes the iron losses calculation of an axial flux machine with yokeless and segmented armature structure based on the limited three-dimensional (3-D) finite element analysis (FEA) results corresponding to one-sixth electrical period. Considering, the 3-D magnetic flux in both stator segments and rotor yoke, soft magnetic composites are used to manufacture the soft magnetic components. Furthermore, time-consuming 3-D FEA is necessary to evaluate the performance of the machine accurately. Due to the magnetic periodicity, most of the characteristics of the machine can be easily determined through averaging the limited 3-D FEA results. However, in some models the calculation of iron losses requires always the flux density waveform in each soft magnetic composites (SMC) element of the FEA model for an entire electrical period, especially when the losses resulted by minor loops should also be taken into account. Therefore, a general method to reconstruct the complete flux density waveform in each SMC component of the FEA model based on limited 3-D FEA results is suggested in this paper. Subsequently, the iron losses can be calculated with various models in time or frequency domain. Finally, the suggested method is validated by comprising the measurement of a prototype with the calculated iron losses based on the classical Bertotti formula.
Autors: B. Zhang;M. Doppelbauer;
Appeared in: IEEE Transactions on Energy Conversion
Publication date: Sep 2017, volume: 32, issue:3, pages: 1023 - 1030
Publisher: IEEE
 
» Irregular Phased Array Tiling by Means of Analytic Schemata-Driven Optimization
Abstract:
The design of subarrayed planar phased arrays characterized by an irregular organization of domino-shaped tiles is addressed. Starting from optimal tiling theorems drawn from mathematical theory, an enumerative approach able to retrieve the optimal clustering providing the maximum aperture coverage and the best radiation performance is proposed to deal with the synthesis of low-/medium-size rectangular arrays. Based on the same optimal theorems and still exploiting the algorithmic procedures at the basis of the enumerative approach, an innovative schemata-based optimization method is introduced for designing large arrays, as well. A set of representative results, concerned with ideal as well as real radiating elements, is reported and discussed to highlight the features and the potentialities of the proposed analytically based design framework.
Autors: Nicola Anselmi;Paolo Rocca;Marco Salucci;Andrea Massa;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Sep 2017, volume: 65, issue:9, pages: 4495 - 4510
Publisher: IEEE
 
» Is it time to become a blockchain developer? [Resources_Careers]
Abstract:
Blockchains-the cryptographically assured ledgers at the heart of cryptocurrencies like Bitcoin-have been suggested as a platform for all kinds of financial instruments. But has the technology matured to the point where there's a significant market for developers who specialize in building on a blockchain? Signs suggest yes, based on what I saw and heard when hundreds of financiers, Wall Street analysts, and C-suite executives gathered in New York City in June. They were there to peer into the future of finance at the CB Insights' Future of Fintech conference, including what role blockchains might play.
Autors: Amy Nordrum;
Appeared in: IEEE Spectrum
Publication date: Sep 2017, volume: 54, issue:9, pages: 21 - 21
Publisher: IEEE
 
» Iterative Detection With Amplitude-Phase Demodulator For Dual-Stream CE-OFDM
Abstract:
Dual-stream constant envelope orthogonal frequency division multiplexing (CE-OFDM) is a flexible waveform that can achieve low peak-to-average power ratio and high spectral efficiency. In this letter, a receiver with iterative detection based on amplitude-phase demodulator is proposed for the demodulation of the dual-stream CE-OFDM. Simulation results show that iterative detection with amplitude-phase demodulator outperforms the existing receiver for dual-stream CE-OFDM, especially for high phase-modulation index and high-order modulation constellation.
Autors: Gaofeng Cui;Cheng Wang;Weidong Wang;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 2001 - 2004
Publisher: IEEE
 
» Iterative Frequency-Domain Joint Channel Estimation and Data Detection of Faster-Than-Nyquist Signaling
Abstract:
In this paper, we propose semi-blind iterative frequency domain joint channel estimation (CE) and data detection (DD) of faster-than-Nyquist signaling (FTNS). The proposed scheme achieves low-complexity operation, while maintaining a performance close to that of the perfect channel state information scenario. More specifically, we derive low-complexity frequency-domain CE for the faster-than-Nyquist pilot (FTNP) transmission scenario, where the symbol duration of a pilot block is lower than the Nyquist-criterion-based pilot transmission. Moreover, we propose a serially concatenated channel-encoded FTNS transceiver that takes into account FTNS-specific colored noise effects. The proposed low-complexity receiver carries out soft-decision frequency-domain equalization with the aid of the minimum-mean square error criterion while whitening the colored noise. As explicit benefits of the proposed frequency-domain CE for the FTNP, the demodulated FTNS data block can also be used as a long pilot block, so the iterative joint CE and DD becomes realistic. Simulation results demonstrate that the proposed two-stage-concatenated FTNS system relying on binary phase-shift keying-based FTNP and FTNS-data symbols achieves a better error-ratio performance than previous systems that do not consider colored noise effects in the high-symbol-packing FTNS regime.
Autors: Takumi Ishihara;Shinya Sugiura;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6221 - 6231
Publisher: IEEE
 
» Iterative IQ Imbalance Compensation Receiver for Single Carrier Transmission
Abstract:
It is well known that low-cost RF front-end implementation such as direct conversion transmitter suffers from serious in-phase/quadrature phase (IQ) imbalance. Most existing works in single carrier transmission employ linear compensation methods, such as Least Square and minimum mean square error, to combat the interference caused by IQ imbalance. Actually, for single carrier transmission, it is possible for the receivers to adopt advanced nonlinear compensation methods to improve the system performance under IQ imbalance. In this paper, we design a new iterative decision feedback receiver to compensate the IQ imbalance caused by unideal radio front end for single carrier frequency domain equalization (SC-FDE). Numerical results shows that, compared with the conventional linear method, our proposed iterative IQ imbalance compensation can significantly improve the performance of SC-FDE system under IQ imbalance.
Autors: Xiaohui Zhang;Hongxiang Li;Wenqi Liu;Junling Qiao;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8238 - 8248
Publisher: IEEE
 
» Joint Adaptive Rate and Scheduling for Unicasting Video Streams in Cellular Wireless Networks
Abstract:
We develop and study adaptive rate scheduling mechanisms over cellular wireless networks, as used for the unicast provision of video streams to client mobiles at variable quality of experience (QoE) levels. Under service type I, mobile users receive video streams at a QoE level that is not lower than a specified value. In addition, mobile users that experience sufficiently high communications channel quality levels may be provided video streams at higher video quality levels. Under service type II, mobile clients receive their video streams at QoE levels that are based on their recorded signal to noise and interference levels. Resource allocations among mobiles are, however, subjected to absolute and proportional fairness objectives. We employ a proxy video manager and resource controller that is located at (or associated with) the base station node. The manager intercepts a channel quality indicator message reported by a mobile client, using it to determine the QoE level at which a requested video stream will be provided. It then selects the proper source and channel encoding schemes to be used for producing and transmitting a compressed version of the stream. To regulate inter-cell signal interference, we examine the joint employment of a number of different spectral-reuse and fractional frequency reuse (FFR) scheduling schemes. To illustrate the use of our models to configure system parameters, we consider a performance metric that incorporates a will-to-pay utility function. We develop analytical techniques for the modeling, analyzing, and designing of such systems. We confirm the precision of these models through the conduct of simulation analyses. Also, we show that, under certain system configurations, FFR-based schemes can lead to substantial enhancement of the system's performance behavior.
Autors: Hung-Bin Chang;Izhak Rubin;Stefania Colonnese;Francesca Cuomo;Ofer Hadar;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8398 - 8412
Publisher: IEEE
 
» Joint Channel Estimation and Impulsive Noise Mitigation in Underwater Acoustic OFDM Communication Systems
Abstract:
Impulsive noise occurs frequently in underwater acoustic (UA) channels and can significantly degrade the performance of UA orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we propose two novel compressed sensing based algorithms for joint channel estimation and impulsive noise mitigation in UA OFDM systems. The first algorithm jointly estimates the channel impulse response and the impulsive noise by utilizing pilot subcarriers. The estimated impulsive noise is then converted to the time domain and removed from the received signals. We show that this algorithm reduces the system bit-error-rate through improved channel estimation and impulsive noise mitigation. In the second proposed algorithm, a joint estimation of the channel impulse response and the impulsive noise is performed by exploiting the initially detected data. Then, the estimated impulsive noise is removed from the received signals. The proposed algorithms are evaluated and compared with existing methods through numerical simulations and on real data collected during a UA communication experiment conducted in the estuary of the Swan River, WA, Australia, during December 2015. The results show that the proposed approaches consistently improve the accuracy of channel estimation and the performance of impulsive noise mitigation in UA OFDM communication systems.
Autors: Peng Chen;Yue Rong;Sven Nordholm;Zhiqiang He;Alexander J. Duncan;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6165 - 6178
Publisher: IEEE
 
» Joint Load Balancing and Interference Mitigation in 5G Heterogeneous Networks
Abstract:
We study the problem of joint load balancing and interference mitigation in heterogeneous networks in which massive multiple-input multiple-output macro cell base station (BS) equipped with a large number of antennas, overlaid with wireless self-backhauled small cells (SCs), is assumed. Self-backhauled SC BSs with full-duplex communication employing regular antenna arrays serve both macro users and SC users by using the wireless backhaul from macro BS in the same frequency band. We formulate the joint load balancing and interference mitigation problem as a network utility maximization subject to wireless backhaul constraints. Subsequently, leveraging the framework of stochastic optimization, the problem is decoupled into dynamic scheduling of macro cell users, backhaul provisioning of SCs, and offloading macro cell users to SCs as a function of interference and backhaul links. Via numerical results, we show the performance gains of our proposed framework under the impact of SCs density, number of BS antennas, and transmit power levels at low and high frequency bands. It is shown that our proposed approach achieves a 5.6 times gain in terms of cell-edge performance as compared with the closed-access baseline in ultra-dense networks with 350 SC BSs per .
Autors: Trung Kien Vu;Mehdi Bennis;Sumudu Samarakoon;Mérouane Debbah;Matti Latva-aho;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6032 - 6046
Publisher: IEEE
 
» Joint Scheduling and Transmission Power Control in Wireless Ad Hoc Networks
Abstract:
In this paper, we study how to determine concurrent transmissions and the transmission power level of each link to maximize the spectrum efficiency and minimize energy consumption in a wireless ad hoc network. The optimal joint transmission packet scheduling and power control strategy is determined when the node density goes to infinity and the network area is unbounded. Based on the asymptotic analysis, we determine the fundamental capacity limits of a wireless network, subject to an energy consumption constraint. We propose a scheduling and transmission power control mechanism to approach the optimal solution to maximize spectrum and energy efficiencies in a practical network. The distributed implementation of the proposed scheduling and transmission power control scheme is presented based on our medium access control (MAC) framework proposed by Rahimi Malekshan. Simulation results demonstrate that the proposed scheme achieves 40% higher throughput than the existing schemes. In addition, the energy consumption using the proposed scheme is about 20% of the energy consumed using existing power saving MAC protocols.
Autors: Kamal Rahimi Malekshan;Weihua Zhuang;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 5982 - 5993
Publisher: IEEE
 
» Joint State Estimation and Delay Identification for Nonlinear Systems With Delayed Measurements
Abstract:
The problem of state estimation for nonlinear systems with unknown state or measurement delays is still an open problem. In this paper, we consider the case of measurement delay and propose an approach that combines a delay identifier with a suitable high-gain observer in order to achieve simultaneous estimation of state and delay. We provide sufficient conditions that guarantee the exponential convergence to zero of the errors, globally with respect to the system variables and locally with respect to the delay estimation. We validate the method through an example concerning population models.
Autors: Filippo Cacace;Francesco Conte;Alfredo Germani;Giovanni Palombo;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4848 - 4854
Publisher: IEEE
 
» Joint Traffic Scheduling and Resource Allocations for Traffic Offloading With Secrecy Provisioning
Abstract:
The recent paradigm of small cell dual-connectivity (DC) provides a promising solution to facilitate mobile users’ (MUs’) traffic offloading in heterogeneous networks. With DC, an MU can flexibly schedule its traffic to macrocell base station (mBS) and offload data to small-cell access point (sAP). However, a malicious node might intentionally eavesdrop the MU's offloaded data, which could lead to the secrecy exposure. In this paper, we investigate the optimal resource allocation for the MUs’ traffic offloading via DC with guaranteed secrecy. First, we study a single-MU single-sAP case and formulate a joint optimization of the MU's traffic scheduling, power allocation, and bandwidth usage for traffic offloading, which aims to minimize the MU's overall resource usage including the power consumption and bandwidth usage. Although the joint optimization problem is nonconvex, we propose an efficient algorithm to obtain the optimal offloading solution. Second, by using the single-MU's optimal offloading solution, we study the multi-MU multi-sAP case and formulate an optimal offloading-selection problem that aims to maximize the overall served MUs’ throughput with guaranteed secrecy, while taking into account the mBS's and sAPs’ limited bandwidths and the sAPs’ limited backhaul capacities. Despite the NP-hardness of the formulated offloading-selection problem, we propose an efficient heuristic algorithm to achieve the offloading-selection solution. Numerical results are provided to validate the performance gain of the proposed traffic offloading schemes with guaranteed secrecy.
Autors: Yuan Wu;Jianchao Zheng;Kuanyang Guo;Li Ping Qian;Xuemin Shen;Yueming Cai;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8315 - 8332
Publisher: IEEE
 
» Joint Transceiver Design for Full-Duplex Cloud Radio Access Networks With SWIPT
Abstract:
This paper studies joint transceiver design for a full-duplex (FD) cloud radio access network with simultaneous wireless information and power transfer. In the considered network, a number of FD remote radio heads receive information from uplink users, while transmitting both information and energy to a set of half-duplex (HD) downlink users with power splitting receivers. We aim to minimize the total power consumption with both uplink-downlink quality of service constraints and energy harvesting constraints. The resulting problem is challenging, because various design parameters, such as the transceiver beamformers, the uplink transmit power, and the receive power splitting ratios, are tightly coupled in the constraints. Four different solution approaches are proposed for the joint transceiver design problem, each one leading to a different numerical algorithm. In particular, a block coordinate descent method is proposed, and by exploiting the problem structure, we prove that the algorithm converges to a Karush-Kuhn-Tucker solution, despite the coupling of various design variables in the constraints. Simulation results validate the effectiveness of the proposed algorithms as compared with the traditional HD scheme.
Autors: Ming-Min Zhao;Qingjiang Shi;Yunlong Cai;Min-Jian Zhao;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 5644 - 5658
Publisher: IEEE
 
» Joint Transceiver Design for Secure Downlink Communications Over an Amplify-and-Forward MIMO Relay
Abstract:
This paper addresses joint transceiver design for secure downlink communications over a multiple-input multiple-output relay system in the presence of multiple legitimate users and malicious eavesdroppers. Specifically, we jointly optimize the base station (BS) beamforming matrix, the relay station (RS) amplify-and-forward transformation matrix, and the covariance matrix of artificial noise, so as to maximize the system worst-case secrecy rate in the presence of the colluding eavesdroppers under power constraints at the BS and the RS, as well as quality of service constraints for the legitimate users. This problem is very challenging due to the highly coupled design variables in the objective function and constraints. By adopting a series of transformation, we first derive an equivalent problem that is more tractable than the original one. Then, we propose and fully develop a novel algorithm based on the penalty concave-convex procedure (penalty-CCCP) to solve the equivalent problem, where the difficult coupled constraint is penalized into the objective and the resulting nonconvex problem is solved at each iteration by resorting to the CCCP method. It is shown that the proposed joint transceiver design algorithm converges to a stationary solution of the original problem. Finally, our simulation results reveal that the proposed algorithm achieves better performance than other recently proposed transceiver designs.
Autors: Yunlong Cai;Qingjiang Shi;Benoit Champagne;Geoffrey Ye Li;
Appeared in: IEEE Transactions on Communications
Publication date: Sep 2017, volume: 65, issue:9, pages: 3691 - 3704
Publisher: IEEE
 
» Joint Transceiver Design With Antenna Selection for Large-Scale MU-MIMO mmWave Systems
Abstract:
This paper considers the uplink of large-scale multiple-user multiple-input multiple-output millimeter wave systems, where several mobile stations (MSs) communicate with a single base station (BS) equipped with a large-scale antenna array, for application to fifth generation wireless networks. Within this context, the use of hybrid transceivers along with antenna selection can significantly reduce the implementation cost and energy consumption of analog phase shifters and low-noise amplifiers. We aim to jointly design the MS beamforming vectors, the hybrid receiving matrices (baseband and analog), and the antenna selection matrix at the BS in order to maximize the achievable system sum-rate under a set of constraints. The corresponding optimization problem is nonconvex and difficult to solve, mainly due to the receive antenna selection and constant modulus constraints on the analog receiving matrix. By exploiting the special structure of the problem and linear relaxation, we first convert this problem into three subproblems, which are solved via an alternating optimization method. The latter iteratively updates the antenna selection matrix, the transmit beamforming vectors, and the hybrid receiving matrices by sequentially addressing each subproblem while keeping the other variables fixed. Specifically, the antenna selection matrix is optimized via the concave–convex procedure; the weighted mean-square error minimization approach is used to find the solution for the transmit beamformer; and the hybrid receiver is obtained via manifold optimization. The convergence of the proposed algorithm is analyzed and its effectiveness is verified by simulation.
Autors: Xiongfei Zhai;Yunlong Cai;Qingjiang Shi;Minjian Zhao;Geoffrey Ye Li;Benoit Champagne;
Appeared in: IEEE Journal on Selected Areas in Communications
Publication date: Sep 2017, volume: 35, issue:9, pages: 2085 - 2096
Publisher: IEEE
 
» Joint Uplink Base Station Association and Power Control for Small-Cell Networks With Non-Orthogonal Multiple Access
Abstract:
Since non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) can achieve superior spectral-efficiency and energy-efficiency, the concept of SCN using NOMA with SIC is proposed in this paper. Due to the difference in small-cell base stations’ locations, each mobile user perceives different channel gains to different small-cell base stations. Therefore, it is important to associate a mobile user with the right base station and control its transmit power for the uplink SCN using NOMA with SIC. However, the already-challenging base station association problem is further complicated by the need of transmit power control, which is an essential component to manage co-channel interference. Despite its importance, the joint base station association and power control optimization problem that maximizes the system-wide utility and at the same time minimizes the total transmit power consumption for the maximum utility has remained largely unsolved for the uplink SCN using NOMA with SIC, mainly due to its non-convex and combinatorial nature. To solve this problem, we first present a formulation transformation that captures two interactive objectives simultaneously. Then, we propose a novel algorithm to solve the equivalently transformed optimization problem based on the coalition formation game theory and the primal decomposition theory in the framework of simulated annealing. Finally, theoretical analysis and simulation results are provided to demonstrate that the proposed algorithm is guaranteed to converge to the global optimal solution in polynomial time.
Autors: Li Ping Qian;Yuan Wu;Haibo Zhou;Xuemin Shen;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 5567 - 5582
Publisher: IEEE
 
» Joint Wideband Interference Suppression and SAR Signal Recovery Based on Sparse Representations
Abstract:
The problem of synthetic aperture radar image recovery in the presence of wideband interference (WBI) is investigated. Delayed versions of a transmitted signal are utilized to construct a dictionary in which a signal of interest (SOI) has a sparse representation. In this letter, WBI is sparsely represented by the time-frequency domain. By utilizing the transform domains, a joint estimation approach is devised to simultaneously perform WBI suppression and SOI recovery within an optimization framework. Based on the separability property in the optimization, an alternating direction method of multipliers-based approach is developed to efficiently obtain a solution. Finally, simulation results are presented to demonstrate the superior performance of the joint estimation algorithm.
Autors: Hongqing Liu;Dong Li;Yi Zhou;Trieu-Kien Truong;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Sep 2017, volume: 14, issue:9, pages: 1542 - 1546
Publisher: IEEE
 
» Joint Wireless Positioning and Emitter Identification in DVB-T Single Frequency Networks
Abstract:
Digital television (DTV) signal has been recognized as a promising signal for navigation and positioning. However, due to the single frequency network (SFN) transmission within the European standard digital video broadcasting terrestrial (DVB-T) system, emitter confusion problem occurs in navigation and positioning, resulting in that a receiver is unable to know from which emitter a received signal comes. In this paper, we consider the wireless positioning with emitter confusion problem in DVB-T SFN networks. A joint wireless positioning and emitter identification algorithm is proposed, which is based on the expectation maximization (EM) method. The proposed algorithm is tested in a scenario, where signals are received from three to five emitters. Simulation results show that, relying on more than three emitters used in the tests for 2-D positioning, the EM-assisted positioning algorithm is feasible to achieve accurate positioning results in the existence of the emitter confusion problem. Our studies show that the performance achieved by the proposed algorithm approaches the Cramér-Rao bound. Furthermore, the proposed algorithm is effective to identify the DTV emitters, and the positioning performance is robust to the emitter identification error. Additionally, our methodology is general, and can be employed for time of arrival-based positioning in any SFNs.
Autors: Liang Chen;Lie-Liang Yang;Jun Yan;Ruizhi Chen;
Appeared in: IEEE Transactions on Broadcasting
Publication date: Sep 2017, volume: 63, issue:3, pages: 577 - 582
Publisher: IEEE
 
» Ka-Band Characterization of Binder Jetting for 3-D Printing of Metallic Rectangular Waveguide Circuits and Antennas
Abstract:
The performance of additive manufactured (AM) RF circuits and antennas is continuously improving, and in some cases these AM components are comparable to state-of-the-art circuits made with traditional manufacturing techniques. Medium to high-power waveguides made with AM methods such as copper-plated plastics, selective laser melting (SLM), and copper additive manufacturing (3-D CAM) have shown good performance up to terahertz frequencies. In this paper, binder jetting (BJ) metal printing is characterized using electron beam microscopy [scanning electron microscopy (SEM)] and energy dispersive spectroscopy. The RF performance of the 3-D-printed circuits is benchmarked with Ka-band cavity resonators, waveguide sections, and a filter. An unloaded resonator of 616 is achieved, and the average attenuation of the WR-28 waveguide section is 4.3 dB/m. The BJ technology is tested with a meshed parabolic reflector antenna, where the illuminating horn, waveguide feed, and a filter are printed in a single piece. The antenna shows a peak gain of 24.56 dBi at 35 GHz.
Autors: Eduardo A. Rojas-Nastrucci;Justin T. Nussbaum;Nathan B. Crane;Thomas M. Weller;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Sep 2017, volume: 65, issue:9, pages: 3099 - 3108
Publisher: IEEE
 
» Kernel-Based Reconstruction of Space-Time Functions on Dynamic Graphs
Abstract:
Graph-based methods pervade the inference toolkits of numerous disciplines including sociology, biology, neuroscience, physics, chemistry, and engineering. A challenging problem encountered in this context pertains to determining the attributes of a set of vertices given those of another subset at possibly diffe-rent time instants. Leveraging spatiotemporal dynamics can drastically reduce the number of observed vertices, and hence the sampling cost. Alleviating the limited flexibility of the existing approaches, the present paper broadens the kernel-based graph function estimation framework to reconstruct time-evolving functions over possibly time-evolving topologies. This approach inherits the versatility and generality of kernel-based methods, for which no knowledge on distributions or second-order statistics is required. Systematic guidelines are provided to construct two families of space-time kernels with complementary strengths: the first facilitates judicious control of regularization on a space-time frequency plane, whereas the second accommodates time-varying topologies. Batch and online estimators are also put forth. The latter comprise a novel kernel Kalman filter, developed to reconstruct space-time functions at affordable computational cost. Numerical tests with real datasets corroborate the merits of the proposed methods relative to competing alternatives.
Autors: Daniel Romero;Vassilis N. Ioannidis;Georgios B. Giannakis;
Appeared in: IEEE Journal of Selected Topics in Signal Processing
Publication date: Sep 2017, volume: 11, issue:6, pages: 856 - 869
Publisher: IEEE
 
» Key Technologies for Next-Generation Digital RoF Mobile Fronthaul With Statistical Data Compression and Multiband Modulation
Abstract:
As a counterpart of analog radio-over-fiber technology, digital radio-over-fiber (D-RoF) system, such as common public radio interface (CPRI), is a matured and robust solution to support RF signal delivery in traditional mobile fronthaul networks. In view of recent progresses in delta-sigma modulation, data compression, and advanced error correcting coding, the efficiency of D-RoF is significantly improved, which motivates researchers to re-evaluate the role of D-RoF in future mobile fronthaul networks to support 5G and beyond wireless communications. In this paper, we demonstrate two critical technologies to improve the transmission efficiency and flexibility of D-RoF systems. A fast-statistical-estimation based data compression algorithm is proposed to reduce the number of quantization digits in a D-RoF-based mobile fronthaul with low complexity and high quality. Combined with resampling and advanced modulation formats, data-transmission efficiency of a 25-Gbit/s D-RoF testbed is improved by around five times compared with uncompressed CPRI systems. On the other hand, we also experimentally demonstrate a point-to-multi-point (PTMP) D-RoF system with multiband modulation, which exhibits higher flexibility and better compatibility with multiple services and different radio-access technologies compared to existing schemes based on time interleaving. An experiment of 13.3-Gbit/s 4-band PTMP bidirectional D-RoF MFH is demonstrated. Combined with data compression, error free delivery of 6.4-Gbit/s 1024-QAM 5G-New-Radio-like signals is realized.
Autors: Mu Xu;Feng Lu;Jing Wang;Lin Cheng;Daniel Guidotti;Gee-Kung Chang;
Appeared in: Journal of Lightwave Technology
Publication date: Sep 2017, volume: 35, issue:17, pages: 3671 - 3679
Publisher: IEEE
 
» KiloHertz Bandwidth, Dual-Stage Haptic Device Lets You Touch Brownian Motion
Abstract:
This paper describes a haptic interface that has a uniform response over the entire human tactile frequency range. Structural mechanics makes it very difficult to implement articulated mechanical systems that can transmit high frequency signals. Here, we separated the frequency range into two frequency bands. The lower band is within the first structural mode of the corresponding haptic device while the higher one can be transmitted accurately by a fast actuator operating from conservation of momentum, that is, without reaction forces to the ground. To couple the two systems, we adopted a channel separation approach akin to that employed in the design of acoustic reproduction systems. The two channels are recombined at the tip of the device to give a uniform frequency response from DC to one kHz. In terms of mechanical design, the high-frequency transducer was embedded inside the tip of the main stage so that during operation, the human operator has only to interact with a single finger interface. In order to exemplify the type of application that would benefit from this kind of interface, we applied it to the haptic exploration with microscopic scales objects which are known to behave with very fast dynamics. The novel haptic interface was bilaterally coupled with a micromanipulation platform to demonstrate its capabilities. Operators could feel interaction forces arising from contact as well as those resulting from Brownian motion and could manoeuvre a micro bead in the absence of vision.
Autors: Tianming Lu;Cécile Pacoret;David Hériban;Abdenbi Mohand-Ousaid;Stéphane Régnier;Vincent Hayward;
Appeared in: IEEE Transactions on Haptics
Publication date: Sep 2017, volume: 10, issue:3, pages: 382 - 390
Publisher: IEEE
 
» Kinesthetic Feedback During 2DOF Wrist Movements via a Novel MR-Compatible Robot
Abstract:
We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar deviation axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius. Via dynamic characterization, we demonstrate capability for transparent operation with low (10% of maximum torque output) backdrivability torques at nominal speeds. Moreover, we demonstrate a 5.5 Hz stiffness control bandwidth for a 14 dB range of virtual stiffness values, corresponding to 25%–125% of the device’s physical reflected stiffness in the nominal configuration. We finally validate the possibility of operation during fMRI via a case study involving one healthy subject. Our validation experiment demonstrates the capability of the device to apply kinesthetic feedback to elicit distinguishable kinetic and neural responses without significant degradation of image quality or task-induced head movements. With this study, we demonstrate the feasibility of MR-compatible devices like the MR-SoftWrist to be used in support of motor control experiments investigating wrist pointing under robot-applied force fields. Such future studies may elucidate fundamental neural mechanisms enabling robot-assisted motor skill learning, which is crucial for robot-aided neurorehabilitation.
Autors: Andrew Erwin;Marcia K. O’Malley;David Ress;Fabrizio Sergi;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Sep 2017, volume: 25, issue:9, pages: 1489 - 1499
Publisher: IEEE
 
» L-Band Microwave Emission of Soil Freeze–Thaw Process in the Third Pole Environment
Abstract:
Soil freeze–thaw transition monitoring is essential for quantifying climate change and hydrologic dynamics over cold regions, for instance, the Third Pole. We investigate the L-band (1.4 GHz) microwave emission characteristics of soil freeze–thaw cycle via analysis of tower-based brightness temperature () measurements in combination with simulations performed by a model of soil microwave emission considering vertical variations of permittivity and temperature. Vegetation effects are modeled using Tor Vergata discrete emission model. The ELBARA-III radiometer is installed in a seasonally frozen Tibetan grassland site to measure diurnal cycles of L-band every 30 min, and supporting micrometeorological as well as volumetric soil moisture () and temperature profile measurements are also conducted. Soil freezing/thawing phases are clearly distinguished by using measurements at two polarizations, and further analyses show that: 1) the four-phase dielectric mixing model is appropriate for estimating permittivity of frozen soil; 2) the soil effective temperature is well comparable with the temperature at 25 cm depth when soil liquid water is freezing, while it is closer to the one measured at 5 cm when soil ice is thawing; and 3) the impact on caused by diurnal changes of ground permittivity is dominating the impact of changing ground temperature. Moreover, the simulations performed with the integrated Tor Vergata emission model an- Noah land surface model indicate that the signatures of diurnal soil freeze–thaw cycle is more sensitive to the liquid water content of the soil surface layer than the in situ measurements taken at 5 cm depth.
Autors: Donghai Zheng;Xin Wang;Rogier van der Velde;Yijian Zeng;Jun Wen;Zuoliang Wang;Mike Schwank;Paolo Ferrazzoli;Zhongbo Su;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Sep 2017, volume: 55, issue:9, pages: 5324 - 5338
Publisher: IEEE
 
» Laboratory Education of Modern Power Systems Using PHIL Simulation
Abstract:
Power hardware-in-the-loop (PHIL) simulation allows the connection of a physical power component (e.g., photovoltaic inverter) to a real-time simulated network. In this paper, PHIL simulation is used for laboratory education in a systematic way for the first time. Four important topics for the understanding of power system operation are selected and laboratory exercises are designed, respectively. The topics focus on the effects of increased integration of distributed generation (DG), namely, power sharing between synchronous generators and DG, voltage control with on load tap changer and DG, short circuits with inverter-based DG, and microgrid operation. The exercises start from the operation of the traditional power system and gradually incorporate DG-related topics that show both benefits and challenges. A hands-on approach is supported by the appropriate lab configuration consisting of two independent PHIL setups. The assessment of the laboratory exercises by the students is clearly positive underlining the value of PHIL simulation for power system education.
Autors: Panos C. Kotsampopoulos;Vasilis A. Kleftakis;Nikos D. Hatziargyriou;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 3992 - 4001
Publisher: IEEE
 
» Lagrangian Detection for Generalized Space-Shift Keying MIMO Systems
Abstract:
Generalized space-shift keying (GSSK) has recently established itself as a promising technology for massive multiple-input multiple-output (MIMO) systems. However, the computational complexity of maximum likelihood (ML) detection is too high, and it increases significantly as the number of transmit antennas and active antennas increases. In this correspondence, we propose a low-complexity suboptimal detection for massive GSSK-MIMO systems. The ML detection of GSSK can be posed as a 0–1 quadratic programming with an equality constraint. First, we employ the Lagrange multiplier to transform the 0–1 quadratic programming with a linear equality constraint into a standard 0–1 quadratic programming. Most of the conventional methods for determining the Lagrange multiplier are derived from Karush–Kuhn–Tucker (KKT) conditions, which are usually valid for continuous variable programming rather than the discrete one. However, in our problem, the optimization variables are binary. Therefore, we propose a theorem that can determine the Lagrange multiplier iteratively by an 1-D binary search rather than KKT conditions and, finally, detect the GSSK transmission symbols. Simulation results demonstrate that the proposed method can achieve an excellent signal detection performance for massive GSSK-MIMO systems with low computational complexity.
Autors: Wenlong Liu;Ying Zhang;Minglu Jin;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8585 - 8589
Publisher: IEEE
 
» Lane Determination With GPS Precise Point Positioning
Abstract:
Modern intelligent transport solutions can achieve an improvement of traffic flow on motorways. With lane-specific measurements and lane-specific control, more measures are possible. Single frequency precise point positioning (PPP) is a newly developed and affordable technique to achieve an improved position accuracy compared with global positioning system (GPS) standalone positioning. GPS-PPP allows for sub-meter accurate positioning, in real time, of vehicles on a motorway. This paper tests this technique in real life; moreover, it presents a methodology to map the lanes on a motorway using data collected by this technique. The methodology exploits the high accuracy and the fact that the most driving is within a lane. In a field test, a GPS-PPP equipped vehicle drives a specific motorway stretch 100 times, for which the GPS-PPP trajectory data are collected. Using these data, the positions and the widths of different lanes are successfully estimated. Comparison with the ground truth shows a dm accuracy. With the parametrized lanes, vehicles can be tracked down to a lane with the GPS-PPP device.
Autors: Victor L. Knoop;Peter F. de Bakker;Christian C. J. M. Tiberius;Bart van Arem;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Sep 2017, volume: 18, issue:9, pages: 2503 - 2513
Publisher: IEEE
 
» Large Multi-Machine Power System Simulations Using Multi-Stage Adomian Decomposition
Abstract:
Multi-stage Adomian decomposition method (MADM) is a proven semi-analytical approximation solution technique for ordinary differential equations (ODEs), which provides a rapidly convergent series by integrating over multiple time intervals. Applicability of MADM for large nonlinear differential algebraic systems (DAEs) is established for the first time in this paper using the partitioned solution approach. Detailed models of power system components are approximated using MADM models. MADM applicability is verified on 7 widely used test systems ranging from 10 generators, 39 buses to 4092 generators, 13659 buses. Impact of the step size and the number of terms is investigated on the stability and accuracy of the method. An average speed up of 42% and 26% is observed in the solution time of ODEs alone using the MADM when compared to the midpoint-trapezoidal (TrapZ) method and the modified-Euler (ME) method, respectively. MADM accuracy is found to be similar to the ME and comparable to the TrapZ method. MADM stability properties are found to be better than the ME and weaker than the TrapZ method. An average speed up of 13% and 5.85% is observed in the overall solution time using MADM w.r.t. TrapZ and ME methods, respectively.
Autors: Gurunath Gurrala;Disha Lagadamane Dinesha;Aleksandar Dimitrovski;Pannala Sreekanth;Srdjan Simunovic;Michael Starke;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 3594 - 3606
Publisher: IEEE
 
» Large-Scale Location Prediction for Web Pages
Abstract:
Location information of Web pages plays an important role in location-sensitive tasks such as Web search ranking for location-sensitive queries. However, such information is usually ambiguous, incomplete, or even missing, which raises the problem of location prediction for Web pages. Meanwhile, Web pages are massive and often noisy, which pose challenges to the majority of existing algorithms for location prediction. In this paper, we propose a novel and scalable location prediction framework for Web pages based on the query-URL click graph. In particular, we introduce a concept of term location vectors to capture location distributions for all terms and develop an automatic approach to learn the importance of each term location vector for location prediction. Empirical results on a large URL set demonstrate that the proposed framework significantly improves the location prediction accuracy comparing with various representative baselines. We further provide a principled way to incorporate the proposed framework into the search ranking task and experimental results on a commercial search engine show that the proposed method remarkably boosts the ranking performance for location-sensitive queries.
Autors: Yuening Hu;Changsung Kang;Jiliang Tang;Dawei Yin;Yi Chang;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 1902 - 1915
Publisher: IEEE
 
» Large-Scale Power System Robust Stability Analysis Based on Value Set Approach
Abstract:
This paper presents a method for robust stability analysis of large-scale power systems based on the value set approach. The order of the system is first reduced by the dimension reduction and modal truncation to capture the oscillation modes of interest. The characteristic polynomial is then obtained by the diagonal expansion, which allows the structure of coefficient functions to be exploited. The Mikhailov plot is generated with ease using the edge theorem and mapping theorem, and by inspection of the plot, the uncertainty's impact becomes transparent. The performance of the proposed method is tested on a 547-machine 8647-bus model of the actual North China system. The results of several case studies are reported, and related works are reviewed for comparison.
Autors: Jinghao Zhou;Peng Shi;Deqiang Gan;Ying Xu;Huanhai Xin;Changming Jiang;Huan Xie;Tao Wu;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4012 - 4023
Publisher: IEEE
 
» Large-Scale Tracking for Images With Few Textures
Abstract:
Image tracking provides crucial insight for the image motion, which generates essential information for incremental structure-from-motion reconstruction and camera pose estimation. Typical usages, such as 3D reconstruction and visual odometry, all rely on robust and accurate local feature tracking through consecutive images. Current algorithms realize feature tracking through matching features extracted from discriminant textures in the images, for which distinctive image content is required to obtain accurate feature matching. For images with few textures, usually, an insufficient number of features are extracted to perform reliable tracking in a series of sequential images. We propose a method that makes use of a limited number of discriminate features to explore other features without strong discriminant power. We develop a feature integrating surrounding salient points distribution knowledge, raw pixel value, and coordinate information to discover a significant amount of features in weakly textured areas in an image. We also incorporate epipolar geometry in the feature correspondence calculation by taking the distance from the matching candidate to its corresponding point's epipolar line into account. To reduce the number of unreliable features, we project the estimated 3D points back to the images. The reprojection error is standardized according to the 3D point's depth, which reduces the bias introduced by the object distance to the camera. We conduct experiments on a large dataset of Arctic sea ice images, mainly composed by planes of ices and sea water. The experimental results demonstrate that our method can perform fast and accurate tracking in weakly textured images.
Autors: Guoyu Lu;Liqiang Nie;Scott Sorensen;Chandra Kambhamettu;
Appeared in: IEEE Transactions on Multimedia
Publication date: Sep 2017, volume: 19, issue:9, pages: 2117 - 2128
Publisher: IEEE
 
» Layer-Dependent Thermophotovoltaic Energy Conversion in 0.5-eV GaInAsSb Devices
Abstract:
By developing a compact dielectric model for GaInAsSb alloys, performance evaluation of 0.5-eV GaInAsSb diode has been systematically conducted by incorporating energy-dependent optical absorption and normal front-surface reflectivity. It is demonstrated here that, when comparing to that for zero surface reflection, incorporating front-surface reflection mainly results in 40% or so output power or efficiency degradation while shows little perturbation on the optimum device configuration and doping profiles, implying that some meaningful guidelines can still be acquired from device simulations without surface reflection. For the concerned alloy, we show that n+/p structure has a superior power conversion and beyond about cm doping density, the efficiency is insensitive to doping density in the light-doped layer.
Autors: Xiao-Long Zhang;A-Bao Huang;Yu Wang;Yi-Yi Lou;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3706 - 3712
Publisher: IEEE
 
» Learn on Source, Refine on Target: A Model Transfer Learning Framework with Random Forests
Abstract:
We propose novel model transfer-learning methods that refine a decision forest model learned within a “source” domain using a training set sampled from a “target” domain, assumed to be a variation of the source. We present two random forest transfer algorithms. The first algorithm searches greedily for locally optimal modifications of each tree structure by trying to locally expand or reduce the tree around individual nodes. The second algorithm does not modify structure, but only the parameter (thresholds) associated with decision nodes. We also propose to combine both methods by considering an ensemble that contains the union of the two forests. The proposed methods exhibit impressive experimental results over a range of problems.
Autors: Noam Segev;Maayan Harel;Shie Mannor;Koby Crammer;Ran El-Yaniv;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Sep 2017, volume: 39, issue:9, pages: 1811 - 1824
Publisher: IEEE
 
» Learning Bregman Distance Functions for Structural Learning to Rank
Abstract:
We study content-based learning to rank from the perspective of learning distance functions. Standardly, the two key issues of learning to rank, feature mappings and score functions, are usually modeled separately, and the learning is usually restricted to modeling a linear distance function such as the Mahalanobis distance. However, the modeling of feature mappings and score functions are mutually interacted, and the patterns underlying the data are probably complicated and nonlinear. Thus, as a general nonlinear distance family, the Bregman distance is a suitable distance function for learning to rank, due to its strong generalization ability for distance functions, and its nonlinearity for exploring the general patterns of data distributions. In this paper, we study learning to rank as a structural learning problem, and devise a Bregman distance function to build the ranking model based on structural SVM. To improve the model robustness to outliers, we develop a robust structural learning framework for the ranking model. The proposed model Robust Structural Bregman distance functions Learning to Rank (RSBLR) is a general and unified framework for learning distance functions to rank. The experiments of data ranking on real-world datasets show the superiority of this method to the state-of-the-art literature, as well as its robustness to the noisily labeled outliers.
Autors: Xi Li;Te Pi;Zhongfei Zhang;Xueyi Zhao;Meng Wang;Xuelong Li;Philip S. Yu;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 1916 - 1927
Publisher: IEEE
 
» Learning from Near Misses [Electrical Safety]
Abstract:
Examines ways engineers can learn from near-miss accidents. Some near-miss incidents are not reported, perhaps because the culture of the company doesn’t encourage a worker to report a near miss. If we really want to learn from these situations, we could publicize a general definition of a near miss that would include incidents where a worker could have been injured or killed if the work proceeded, and we could encourage prompt reporting so corrections can be made quickly before someone else is hurt or killed.
Autors: Daniel Doan;
Appeared in: IEEE Industry Applications Magazine
Publication date: Sep 2017, volume: 23, issue:5, pages: 6 - 13
Publisher: IEEE
 
» Learning Transportation Modes From Smartphone Sensors Based on Deep Neural Network
Abstract:
In recent years, the importance of user information has increased rapidly for context-aware applications. This paper proposes a deep learning mechanism to identify the transportation modes of smartphone users. The proposed mechanism is evaluated on a database that contains more than 1000 h of accelerometer, magnetometer, and gyroscope measurements from five transportation modes, including still, walk, run, bike, and vehicle. Experimental results confirm the effectiveness of the proposed mechanism, which achieves approximately 95% classification accuracy and outperforms four well-known machine learning methods. Meanwhile, we investigated the model size and execution time of different algorithms to address practical issues.
Autors: Shih-Hau Fang;Yu-Xaing Fei;Zhezhuang Xu;Yu Tsao;
Appeared in: IEEE Sensors Journal
Publication date: Sep 2017, volume: 17, issue:18, pages: 6111 - 6118
Publisher: IEEE
 
» Leveraging SDN and WebRTC for Rogue Access Point Security
Abstract:
Rogue access points (RAPs) are unauthorized devices connected to a network, providing unauthorized wireless access to one or more clients. Such devices pose significant risk to organizations, since they provide a convenient means for hackers and insiders to hide malicious or unsanctioned activities on industry, government, and campus networks. Yet, limitations inherent in traditional networks make detecting and removing such devices expensive, time consuming, and difficult to implement. For software-defined networks (SDNs), the risk of a network compromise due to RAPs is equally concerning, and methods for detecting RAPs within SDN architectures are needed. Hence, this paper leverages the capabilities of an SDN along with a trusted agent to detect and deny RAPs access to networks by using both generic and novel methods with minimal impact to performance. Three other contributions are included in this paper. They include: 1) utilizing an emerging Web architecture to detect hidden subnets; 2) developing the first, security-based, use case for Mininet-WiFi, a software-defined wireless network emulator; and 3) enhancing Ryuretic, a modular programming language for SDN application development.
Autors: Jacob H. Cox;Russell Clark;Henry Owen;
Appeared in: IEEE Transactions on Network and Service Management
Publication date: Sep 2017, volume: 14, issue:3, pages: 756 - 770
Publisher: IEEE
 
» Leveraging Time Prediction and Error Compensation to Enhance the Scalability of Parallel Multi-Core Simulations
Abstract:
Due to synchronization overhead, it is challenging to apply the parallel simulation technique of multi-core processors at larger scales. Although the use of lax synchronization schemes could reduce overhead and balance the load between synchronous points, it introduces timing error and deteriorates simulation accuracy. Through observing the propagation paths of errors, we find that these paths always concentrate on some pivotal events. Based on the observation, we design a delay-calibration mechanism to alleviate errors. We decouple the timing and functional processes of the pivotal events, leveraging prediction technique of delays to connect two categories of the processes. Errors are traced throughout the timing processes of the pivotal events, and are deducted from the predicted delays before the delays are consumed by the functional processes. Therefore, through cleaning the errors at the successive pivot events, the mechanism decreases the simulated time deviations efficiently. Since the prediction and error deduction processes do not have any constraint on synchronizations, our approach largely maintains the scalability of lax synchronization schemes. Furthermore, our proposal is orthogonal to other parallel simulation techniques and can be used in conjunction with them. Experimental results show that error compensation improves the accuracy of lax synchronized simulations by 68 percent and achieves 97.8 percent accuracy when combined with an enhanced lax synchronization.
Autors: Xiaodong Zhu;Junmin Wu;Tao Li;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Sep 2017, volume: 28, issue:9, pages: 2553 - 2566
Publisher: IEEE
 
» Licensing Engineering Professionals [Letter]
Abstract:
Autors: Gerald Aksherian;
Appeared in: IEEE Technology and Society Magazine
Publication date: Sep 2017, volume: 36, issue:3, pages: 10 - 10
Publisher: IEEE
 
» Light Extraction Enhancement of GaN-Based Light-Emitting Diodes With Textured Sidewalls and ICP-Transferred Nanohemispherical Backside Reflector
Abstract:
Textured-sidewall GaN-based light-emitting diodes (LEDs) with convex and 45° patterns and an inductively coupled plasma (ICP)-transferred nanohemispherical backside reflector, formed using an ICP etching process, are fabricated and studied. For devices with textured sidewalls, the scattering probability of photons at the GaN/air interface is increased and the light extraction efficiency is enhanced since photons are allowed to find escape cones in the horizontal direction. With the ICP-transferred nanohemispherical backside reflector, reflected photons can be easily scattered and redirected in arbitrary directions for light extraction and thus have more opportunities to escape the devices. The LED with 45° sidewalls and a backside reflector exhibited the significant improvements of 55.8%, 49.3%, 47.2%, and 55.4% in light output power, luminous flux, external quantum efficiency, and wall-plug efficiency, respectively, compared to those of a conventional LED without these specific designs (Device A). In addition, the higher intensities in a light emission mapping image and improved far-field patterns are obtained for the studied device. The enhanced optical performance is mainly attributed to the increased light extraction in all directions due to a significant reduction in the total internal reflection by the textured sidewalls and a backside reflector. Therefore, textured-sidewall structures and an ICP-transferred nanohemispherical backside reflector are promising for high-power GaN-based LED applications.
Autors: Chun-Yen Chen;Wen-Chau Liu;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3672 - 3677
Publisher: IEEE
 
» Lightweight Hardware Architectures for the Present Cipher in FPGA
Abstract:
In recent years, the study of lightweight symmetric ciphers has gained interest due to the increasing demand for security services in constrained computing environments, such as in the Internet of Things. However, when there are several algorithms to choose from and different implementation criteria and conditions, it becomes hard to select the most adequate security primitive for a specific application. This paper discusses the hardware implementations of Present, a standardized lightweight cipher called to overcome part of the security issues in extremely constrained environments. The most representative realizations of this cipher are reviewed and two novel designs are presented. Using the same implementation conditions, the two new proposals and three state-of-the-art designs are evaluated and compared, using area, performance, energy, and efficiency as metrics. From this wide experimental evaluation, to the best of our knowledge, new records are obtained in terms of implementation size and energy consumption. In particular, our designs result to be adequate in regards to energy-per-bit and throughput-per-slice.
Autors: Carlos Andres Lara-Nino;Arturo Diaz-Perez;Miguel Morales-Sandoval;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Sep 2017, volume: 64, issue:9, pages: 2544 - 2555
Publisher: IEEE
 
» Likelihood Analysis of Power Spectra and Generalized Moment Problems
Abstract:
We develop an approach to the spectral estimation that has been advocated by [A. Ferrante et al., “Time and spectral domain relative entropy: A new approach to multivariate spectral estimation,” IEEE Trans. Autom. Control, vol. 57, no. 10, pp. 2561–2575, Oct. 2012.] and, in the context of the scalar-valued covariance extension problem, by [P. Enqvist and J. Karlsson, “Minimal itakura-saito distance and covariance interpolation,” in Proc. 47th IEEE Conf. Decision Control, 2008, pp. 137–142]. The aim is to determine the power spectrum that is consistent with given moments and minimizes the relative entropy between the probability law of the underlying Gaussian stochastic process to that of a prior. The approach is analogous to the framework of earlier work by Byrnes, Georgiou, and Lindquist and can also be viewed as a generalization of the classical work by Burg and Jaynes on the maximum entropy method. In this paper, we present a new fast algorithm in the general case (i.e., for general Gaussian priors) and show that for priors with a specific structure the solution can be given in closed form.
Autors: Tryphon T. Georgiou;Anders Lindquist;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4580 - 4592
Publisher: IEEE
 
» Limited Feedback Scheme for Device-to-Device Communications in 5G Cellular Networks with Reliability and Cellular Secrecy Outage Constraints
Abstract:
In this paper, we propose a device-to-device (D2D) communication scenario underlaying a cellular network, where both D2D and cellular users (CUs) are discrete power-rate systems with limited feedback from the receivers. It is assumed that there exists an adversary which wants to eavesdrop on the information transmission from the base station to CUs. Since D2D communication shares the same spectrum with cellular network, cross interference must be considered. However, when secrecy capacity is considered, the interference caused by D2D communication can help to improve the secrecy communications by confusing the eavesdroppers. Since both systems share the same spectrum, cross interference must be considered. We formulate the proposed resource allocation into an optimization problem whose objective is to maximize the average transmission rate of D2D pair in the presence of the cellular communications under average transmission power constraint. For the cellular network, we require a minimum average achievable secrecy rate in the absence of D2D communication as well as a maximum secrecy outage probability in the presence of D2D communication which should be satisfied. Due to high complexity convex optimization methods, to solve the proposed optimization problem, we apply particle swarm optimization, which is an evolutionary approach. Moreover, we model and study the error in the feedback channel and the imperfectness of channel distribution information using parametric and nonparametric methods. Finally, the impact of different system parameters on the performance of the proposed scheme is investigated through simulations. The performance of the proposed scheme is evaluated using numerical results for differentu scenarios.
Autors: Faezeh Alavi;Nader Mokari Yamchi;Mohammad R. Javan;Kanapathippillai Cumanan;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8072 - 8085
Publisher: IEEE
 
» Limited-Magnitude Error-Correcting Gray Codes for Rank Modulation
Abstract:
We construct error-correcting codes over permutations under the infinity-metric, which are also Gray codes in the context of rank modulation, i.e., are generated as simple circuits in the rotator graph. These errors model limited-magnitude or spike errors, for which only single-error-detecting Gray codes are currently known. Surprisingly, the error-correcting codes we construct achieve a better asymptotic rate than that of presently known constructions not having the Gray property, and exceed the Gilbert-Varshamov bound. Additionally, we present efficient ranking and unranking procedures, as well as a decoding procedure that runs in linear time. Finally, we also apply our methods to solve an outstanding issue with error-detecting rank-modulation Gray codes (also known in this context as snake-in-the-box codes) under a different metric, the Kendall -metric, in the group of permutations over an even number of elements , where we provide asymptotically optimal codes.
Autors: Yonatan Yehezkeally;Moshe Schwartz;
Appeared in: IEEE Transactions on Information Theory
Publication date: Sep 2017, volume: 63, issue:9, pages: 5774 - 5792
Publisher: IEEE
 
» Line: Evaluating Software Applications in Unreliable Environments
Abstract:
Cloud computing has paved the way to the flexible deployment of software applications. This flexibility offers service providers a number of options to tailor their deployments to the observed and foreseen customer workloads, without incurring in large capital costs. However, cloud deployments pose novel challenges regarding application reliability and performance. Examples include managing the reliability of deployments that make use of spot instances, or coping with the performance variability caused by multiple tenants in a virtualized environment. In this paper, we introduce Line, a tool for performance and reliability analysis of software applications. Line solves layered queueing network (LQN) models, a popular class of stochastic models in software performance engineering, by setting up and solving an associated system of ordinary differential equations. A key differentiator of Line compared to existing solvers for LQNs is that Line incorporates a model of the environment the application operates in. This enables the modeling of reliability and performance issues such as resource failures, server breakdowns and repairs, slow start-up times, resource interference due to multitenancy, among others. This paper describes the Line tool, its support for performance and reliability modeling, and illustrates its potential by comparing Line predictions against data obtained from a cloud deployment. We also illustrate the applicability of Line with a case study on reliability-aware resource provisioning.
Autors: Juan F. Pérez;Giuliano Casale;
Appeared in: IEEE Transactions on Reliability
Publication date: Sep 2017, volume: 66, issue:3, pages: 837 - 853
Publisher: IEEE
 
» Linear Subspace Ranking Hashing for Cross-Modal Retrieval
Abstract:
Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features’ ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.
Autors: Kai Li;Guo-Jun Qi;Jun Ye;Kien A. Hua;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Sep 2017, volume: 39, issue:9, pages: 1825 - 1838
Publisher: IEEE
 
» Linking Conductive Filament Properties and Evolution to Synaptic Behavior of RRAM Devices for Neuromorphic Applications
Abstract:
We perform a comparative study of HfO2 and Ta2O5 resistive switching memory (RRAM) devices for their possible application as electronic synapses. By means of electrical characterization and simulations, we link their electrical behavior (digital or analog switching) to the properties and evolution of the conductive filament (CF). More specifically, we identify that bias-polarity-dependent digital switching in HfO2 RRAM is primarily related to the creation and rupture of an oxide barrier. Conversely, the modulation of the CF size in Ta2O5 RRAM allows bias-polarity-independent analog switching with multiple states. Therefore, when the Ta2O5 RRAM is used to implement a synapse in multilayer perceptron neural networks operated by back-propagation algorithms, patterns in handwritten digits can be recognized with high accuracy.
Autors: Jiyong Woo;Andrea Padovani;Kibong Moon;Myounghun Kwak;Luca Larcher;Hyunsang Hwang;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1220 - 1223
Publisher: IEEE
 
» Lithium–Sulfur Cell Equivalent Circuit Network Model Parameterization and Sensitivity Analysis
Abstract:
Compared to lithium-ion batteries, lithium–sulfur (Li-S) batteries potentially offer greater specific energy density, a wider temperature range of operation, and safety benefits, making them a promising technology for energy storage systems especially in automotive and aerospace applications. Unlike lithium-ion batteries, there is not a mature discipline of equivalent circuit network (ECN) modelling for Li-S. In this study, ECN modelling is addressed using formal ‘system identification’ techniques. A Li-S cell's performance is studied in the presence of different charge/discharge rates and temperature levels using precise experimental test equipment. Various ECN model structures are explored, considering the tradeoffs between accuracy and speed. It was concluded that a ‘2RC’ model is generally a good compromise, giving good accuracy and speed. Model parameterization is repeated at various state-of-charge (SOC) and temperature levels, and the effects of these variables on Li-S cell's ohmic resistance and total capacity are demonstrated. The results demonstrate that Li-S cell's ohmic resistance has a highly nonlinear relationship with SOC with a break-point around 75% SOC that distinguishes it from other types of battery. Finally, an ECN model is proposed which uses SOC and temperature as inputs. A sensitivity analysis is performed to investigate the effect of SOC estimation error on the model's accuracy. In this analysis, the battery model's accuracy is evaluated at various SOC and temperature levels. The results demonstrate that the Li-S cell model has the most sensitivity to SOC estimation error around the break-point (around 75% SOC) whereas in the middle SOC range, from 20% to 70%, it has the least se- sitivity.
Autors: Abbas Fotouhi;Daniel J. Auger;Karsten Propp;Stefano Longo;Rajlakshmi Purkayastha;Laura O'Neill;Sylwia Waluś;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 7711 - 7721
Publisher: IEEE
 
» Liver Segmentation on CT and MR Using Laplacian Mesh Optimization
Abstract:
Objective: The purpose of this paper is to describe a semiautomated segmentation method for the liver and evaluate its performance on CT-scan and MR images. Methods: First, an approximate 3-D model of the liver is initialized from a few user-generated contours to globally outline the liver shape. The model is then automatically deformed by a Laplacian mesh optimization scheme until it precisely delineates the patient's liver. A correction tool was implemented to allow the user to improve the segmentation until satisfaction. Results: The proposed method was tested against 30 CT-scans from the SLIVER07 challenge repository and 20 MR studies from the Montreal University Hospital Center, covering a wide spectrum of liver morphologies and pathologies. The average volumetric overlap error was 5.1% for CT and 7.6% for MRI and the average segmentation time was 6 min. Conclusion: The obtained results show that the proposed method is efficient, reliable, and could effectively be used routinely in the clinical setting. Significance: The proposed approach can alleviate the cumbersome and tedious process of slice-wise segmentation required for precise hepatic volumetry, virtual surgery, and treatment planning.
Autors: Gabriel Chartrand;Thierry Cresson;Ramnada Chav;Akshat Gotra;An Tang;Jacques A. De Guise;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Sep 2017, volume: 64, issue:9, pages: 2110 - 2121
Publisher: IEEE
 
» Liver Venous Tree Separation via Twin-Line RANSAC and Murray’s Law
Abstract:
It is essential for physicians to obtain the accurate venous tree from abdominal CT angiography (CTA) series in order to carry out the preoperative planning and intraoperative navigation for hepatic surgery. In this process, one of the important tasks is to separate the given liver venous mask into its hepatic and portal parts. In this paper, we present a novel method for liver venous tree separation. The proposed method first concentrates on extracting potential vessel intersection points between hepatic and portal venous systems. Then, the proposed method focuses on modeling the vessel intersection neigh-borhoods with a robust twin-line random sample consensus (RANSAC) shape detector. Finally, the proposed method conducts the venous tree separation based on the results of the twin-line RANSAC as well as physical constraints posed by Murray’s Law. We test our method on 22 clinical CTA series and demonstrate its effectiveness.
Autors: Zixu Yan;Feng Chen;Dexing Kong;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Sep 2017, volume: 36, issue:9, pages: 1887 - 1900
Publisher: IEEE
 
» LMI-Based Robust Predictive Load Frequency Control for Power Systems With Communication Delays
Abstract:
This paper presents a robust predictive load frequency control for power systems with uncertain parameters and time delays in communication networks. The goal of the proposed approach is to achieve good performance for the closed-loop system under practical problems of the network including uncertainties in the dynamic model, time delays in the system, and time-varying model. To this end, a decentralized state-feedback control law is obtained by solving an linear matrix inequality based optimization. The aim of the optimization problem is to regularize the frequency deviation with the minimum control effort. It is shown that the stability of the system is guaranteed with respect to the Lyapunov stability theorem. Moreover, the problem is reformulated as a centralized load frequency control (LFC) approach for single-area power systems, and also as a non-predictive LFC method with lower computational complexity. The performance and robustness of the proposed strategy are studied through simulation results in different cases of uncertain and time-varying single-area and multi-area power systems with time delays.
Autors: Pegah Ojaghi;Mehdi Rahmani;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4091 - 4100
Publisher: IEEE
 
» LMP Revisited: A Linear Model for the Loss-Embedded LMP
Abstract:
In this paper, the concept of locational marginal price (LMP) is revisited by analyzing the Karush–Kuhn–Tucker (KKT) condition of a general optimal power flow (OPF) problem. The impact of losses on LMP is investigated. Several well-known properties and formulations of the LMP are illustrated from a novel perspective. In particular, the special case of the lossless DC OPF model is discussed. Based on this theoretical analysis, a linear model for the loss-embedded LMP is proposed. The influence of losses on the LMP is recovered by solving a system of linear equations. The proposed method does not rely on strong subjective assumptions, such as the selection of reference buses or the determination of the “loss factor.” Case studies show that the proposed method has distinct advantages compared with the method currently practiced in major electricity markets.
Autors: Zhifang Yang;Anjan Bose;Haiwang Zhong;Ning Zhang;Jeremy Lin;Qing Xia;Chongqing Kang;
Appeared in: IEEE Transactions on Power Systems
Publication date: Sep 2017, volume: 32, issue:5, pages: 4080 - 4090
Publisher: IEEE
 
» Local and Remote Cooperation With Virtual and Robotic Agents: A P300 BCI Study in Healthy and People Living With Spinal Cord Injury
Abstract:
The development of technological applications that allow people to control and embody external devices within social interaction settings represents a major goal for current and future brain–computer interface (BCI) systems. Prior research has suggested that embodied systems may ameliorate BCI end-user’s experience and accuracy in controlling external devices. Along these lines, we developed an immersive P300-based BCI application with a head-mounted display for virtual-local and robotic-remote social interactions and explored in a group of healthy participants the role of proprioceptive feedback in the control of a virtual surrogate (Study 1). Moreover, we compared the performance of a small group of people with spinal cord injury (SCI) to a control group of healthy subjects during virtual and robotic social interactions (Study 2), where both groups received a proprioceptive stimulation. Our attempt to combine immersive environments, BCI technologies and neuroscience of body ownership suggests that providing realistic multisensory feedback still represents a challenge. Results have shown that healthy and people living with SCI used the BCI within the immersive scenarios with good levels of performance (as indexed by task accuracy, optimizations calls and Information Transfer Rate) and perceived control of the surrogates. Proprioceptive feedback did not contribute to alter performance measures and body ownership sensations. Further studies are necessary to test whether sensorimotor experience represents an opportunity to improve the use of future embodied BCI applications.
Autors: Emmanuele Tidoni;Mohammad Abu-Alqumsan;Daniele Leonardis;Christoph Kapeller;Gabriele Fusco;Cristoph Guger;Cristoph Hintermüller;Angelika Peer;Antonio Frisoli;Franco Tecchia;Massimo Bergamasco;Salvatore Maria Aglioti;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Sep 2017, volume: 25, issue:9, pages: 1622 - 1632
Publisher: IEEE
 
» Local Condition Based Consensus Filtering With Stochastic Nonlinearities and Multiple Missing Measurements
Abstract:
This paper is concerned with the distributed -consensus filtering problem for a class of discrete time-varying systems with stochastic nonlinearities and multiple missing measurements. The stochastic nonlinearities are formulated by statistical means and the missing measurements are characterized by a set of random variables obeying Bernoulli distribution. A novel -consensus performance index is proposed to measure both the filtering accuracy of every node and the consensus among neighbor nodes. Then, a new concept called stochastic vector dissipativity is proposed wherein the dissipation matrix is formulated by a nonsingular substochastic matrix, which is skillfully constructed by a new defined interval function on the out-degree. A set of local sufficient conditions in terms of the recursive linear matrix inequalities is presented for each node such that the proposed -consensus performance can be guaranteed for the local augmented dynamics over the finite horizon. Furthermore, a novel algorithm proposed here can be implemented on each node. Finally, an illustrative simulation is presented to demonstrate the effectiveness and applicability of the proposed algorithm.
Autors: Fei Han;Guoliang Wei;Derui Ding;Yan Song;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4784 - 4790
Publisher: IEEE
 
» Local Fringe Frequency Estimation Based on Multifrequency InSAR for Phase-Noise Reduction in Highly Sloped Terrain
Abstract:
The interferometric phases in highly sloped terrain have the characteristics of large fringe density, narrow width, low correlation, and under-sampling. The local fringe frequ- ency (LFF) is a criterion to evaluate the trend and magnitude of the local terrain gradient and can be employed to improve the quality of interferograms. The results of the traditional LFF estimation method can be affected by phase noise, and sometimes the phase unwrapping (PU) operation is also required for some local regions. When it comes to highly sloped terrain, the phenomenon of phase under-sampling may cause incorrectness in the absolute interferometric phase during the operation of PU and may then influence the accuracy of the whole estimation. In order to solve this problem, this letter proposes an extended maximum-likelihood method for LFF estimation based on the multifrequency interferometric synthetic aperture radar (InSAR) data. Through the differences in the LFF between the different frequency InSAR data, the estimation quality map is introduced to modify the large error in certain regions by local 2-D fitting and thus achieves a accurate estimation of LFF in highly sloped terrain. Finally, the estimated results of LFF are used to guide the process of phase filtering. Simulated data and real airborne dual-frequency InSAR data are both employed to validate this proposed method.
Autors: Zegang Ding;Zhen Wang;Sheng Lin;Tiandong Liu;Qi Zhang;Teng Long;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Sep 2017, volume: 14, issue:9, pages: 1527 - 1531
Publisher: IEEE
 
» Localized Mobility Management for 5G Ultra Dense Network
Abstract:
It is commonly agreed that the ultra dense network (UDN) will be a key technology to face extremely dense traffic and high-speed data rate in the fifth-generation (5G) network. However, due to its new characteristics such as high dense small cells, fast and flexible deployment of small cell access points, and flexible backhaul connectivity, how to enable mobility support is becoming a great challenge. In this paper, based on newly proposed network architectures for UDN, we present two efficient localized mobility management schemes considering small cell deployments and backhaul topology. The first one centralizes mobility management control from small cell access points into a local access server (LAS) closing to radio access network. Another one allows individual small cell access points to handle mobility events, but still requires the LAS to act as mobility anchor. According to the performance evaluation results of the proposed schemes by using numerical analysis and simulation, respectively, including average handover signaling cost, average packet delivery cost, average handover latency, and average signaling load to the core network, the localized mobility management with centralized control scheme has the best performance, and the other one has less handover signaling cost, but higher handover latency than the third-generation partnership project (3GPP) scheme.
Autors: Hucheng Wang;Shanzhi Chen;Ming Ai;Hui Xu;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8535 - 8552
Publisher: IEEE
 
» Log-Normal Statistics in Filamentary RRAM Devices and Related Systems
Abstract:
We present a phenomenological theory of the log-normal statistics commonly observed in filamentary resistive memory and related devices. Based on the central limit theorem that statistics are shown to emerge regardless of the underlying material properties when the processes are dominated by thermal activation or tunneling. That takes place in particular for the read-out resistances in the high-resistive (OFF) state, and the random telegraph noise amplitudes, but can be observed in the low-resistive (ON) state as well. We show that the statistics of switching times becomes log-normal when the switching is due to the field induced nucleation.
Autors: V. G. Karpov;D. Niraula;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1240 - 1243
Publisher: IEEE
 
» Lookup: Robust and Accurate Indoor Localization Using Visible Light Communication
Abstract:
A novel indoor localization system is presented, where LED beacons are utilized to determine the position of the target sensor, including a camera, an inclinometer, and a magnetometer. The beacons, which can be a part of the existing lighting infrastructure, transmit their identifiers for long distances using visible light communication techniques. The sensor is able to sense and detect the high-frequency (flicker free) code by properly undersampling the transmitted signal. The localization is performed using novel geometric and consensus-based techniques, which tolerate well measurement inaccuracies and sporadic outliers. The performance of the system is analyzed using simulations and real measurements. According to large-scale tests in realistic environments, the accuracy of the proposed system is in the low decimeter range.
Autors: Gyula Simon;Gergely Zachár;Gergely Vakulya;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Sep 2017, volume: 66, issue:9, pages: 2337 - 2348
Publisher: IEEE
 
» Loss and Noise Analysis of Transformer ComprisingGrooved Grain-Oriented Silicon Steel
Abstract:
For the reduction of transformer noise and efficient use of energy, we developed a domain-refined highly grain-oriented silicon steel with a linearly grooved surface by an electrolytic etching method. The steel showed very low iron loss even after a high-temperature annealing process, such as stress relief annealing, while magnetic flux density at 800 A/m, which is one of the very fundamental evaluation criteria for grain-oriented silicon steel, was lower than that without grooves. In light of our previous study, steels with a low flux density are disadvantageous for lowering transformer noise, but there have been no reports on the detailed noise property of this grooved grain-oriented silicon steel. In this paper, we investigated transformer noise as well as the transformer loss for the first time by fabricating three model transformers, each of which comprised one of the following grain-oriented electrical steels: grooved grain-oriented silicon steel having flux density of 1.90 T at 800 A/m, non-grooved grain-oriented silicon steel having flux density of 1.93 T at 800 A/m, and non-grooved grain-oriented silicon steel having flux density of 1.90 T at 800 A/m. As a result, transformer loss exhibited a tendency similar to the loss of a single sheet, and the grooved grain-oriented silicon steel showed the lowest loss. As for noise, even with the lower flux density, the grooved grain-oriented silicon steel showed a very low noise level equivalent to that of the non-grooved grain-oriented silicon steel with the high flux density, while the non-grooved grain-oriented silicon steel with the low flux density showed the largest noise level. From the results of magnetostriction measurements and dynamic domain observation by a newly developed method, it was found that the grooves had little influence on the generation of magnetic domains, which increased magnetostriction and transformer noise. Thus, we confirmed that low noise and low loss properties of the transformer were - oth realized by the application of the grooved silicon steel.
Autors: S. Takajo;T. Ito;T. Omura;S. Okabe;
Appeared in: IEEE Transactions on Magnetics
Publication date: Sep 2017, volume: 53, issue:9, pages: 1 - 6
Publisher: IEEE
 
» Loss Function Modeling of Efficiency Maps of Electrical Machines
Abstract:
This paper presents a novel approach in the modeling of efficiency maps for electrical machines. It is based on using the sum of terms in the form of kmnTmωn to represent the variation of the stator and rotor copper, iron, and magnet losses with torque and speed. The effect of each term on the shape of the efficiency map is explored. Analysis is performed on the calculated efficiency and loss maps of an induction, an interior permanent magnet, and a surface permanent magnet machine to demonstrate the validity of the approach.
Autors: Amin Mahmoudi;Wen L. Soong;Gianmario Pellegrino;Eric Armando;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Sep 2017, volume: 53, issue:5, pages: 4221 - 4231
Publisher: IEEE
 
» Loss of low-frequency data in on- line frequency response analysis of transformers
Abstract:
Power transformers are a key component of the electricity supply grid. Monitoring and assessment of their condition has always been of great concern [1]. In critical situations, transformer failures can cause irreversible damage and considerable financial loss to the grid stakeholders or even the end-users [2], [3]. In this regard, mechanical defects are considered a major problem in distribution and power transformers [4]. Consequently various diagnostic techniques have been developed to identify transformer mechanical defects and winding deformation.
Autors: Mehdi Bagheri;Svyatoslav Nezhivenko;B. T. Phung;
Appeared in: IEEE Electrical Insulation Magazine
Publication date: Sep 2017, volume: 33, issue:5, pages: 32 - 39
Publisher: IEEE
 
» Low Complexity Post-Distorter for Visible Light Communications
Abstract:
In this letter, a visible light communication (VLC) link affected by the light emitting diode (LED) nonlinearity and dispersion due to the IEEE 802.15 PAN channel impulse response is considered. To mitigate severe intersymbol interference and LED nonlinearity, computationally complex classical post-distortion techniques fall short in terms of applicability to massively connected 5G deployments (as in a VLC attocell) due to increased demand on resources and intractability of implementation. To address these issues, this letter proposes a low-complexity reproducing kernel Hilbert space-based post-distorter using a better sparsification technique equipped with an adaptive kernel width optimized by a minimum symbol error rate (MSER) criterion. Use of the proposed MSER metric for kernel width optimization reduces the computational complexity at the receiver, without compromising on the bit error rate. An upper bound on step-size to guarantee convergence of the proposed post-distorter is analytically derived, and the steady-state mean square error is also analyzed theoretically and validated by simulations. Furthermore, analytical upper bounds for bit error rate and steady-state dictionary size are also derived.
Autors: Rangeet Mitra;Vimal Bhatia;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 1977 - 1980
Publisher: IEEE
 
» Low Rank Approximation and Decomposition of Large Matrices Using Error Correcting Codes
Abstract:
Low rank approximation is an important tool used in many applications of signal processing and machine learning. Recently, randomized sketching algorithms were proposed to effectively construct low rank approximations and obtain approximate singular value decompositions of large matrices. Similar ideas were used to solve least squares regression problems. In this paper, we show how matrices from error correcting codes can be used to find such low rank approximations and matrix decompositions, and extend the framework to linear least squares regression problems. The benefits of using these code matrices are the following. First, they are easy to generate and they reduce randomness significantly. Second, code matrices, with mild restrictions, satisfy the subspace embedding property, and have a better chance of preserving the geometry of an large subspace of vectors. Third, for parallel and distributed applications, code matrices have significant advantages over structured random matrices and Gaussian random matrices. Fourth, unlike Fourier or Hadamard transform matrices, which require sampling columns for a rank- approximation, the log factor is not necessary for certain types of code matrices. In particular, optimal Frobenius norm error can be achieved for a rank- approximation with samples. Fifth, fast multiplication is possible with structured code matrices, so fast approximations can be achieved for general dense input matrices. Sixth, for least squares regression problem , the relative error approximation can be achieved with samples, with high probability, when certain code matrices are used.
Autors: Shashanka Ubaru;Arya Mazumdar;Yousef Saad;
Appeared in: IEEE Transactions on Information Theory
Publication date: Sep 2017, volume: 63, issue:9, pages: 5544 - 5558
Publisher: IEEE
 
» Low-Complexity Base Station Selection Scheme in mmWave Cellular Networks
Abstract:
In this paper, we study the performance of next-generation cellular networks in the context of a low-complexity base station (BS) selection scheme. In contrast to existing BS cooperation approaches, where multiple BSs jointly transmit to the user, by using our proposed low-complexity technique, a user communicates with the BS that provides the maximum signal-to-interference-plus-noise-ratio from a set formed according to a pre-selection policy. We consider three pre-selection policies based on: 1) the Euclidean distance; 2) the averaged received power; and 3) a random selection. Moreover, we consider the case where the users have the ability to employ the successive interference cancellation (SIC) scheme. Despite its high computational complexity, SIC can potentially decode and remove strong interfering signals from the aggregate received signal, which can significantly boost the user’s performance. By using stochastic geometry tools, analytical expressions for the coverage performance are derived for each policy, by taking into account spatial randomness and blockage effects. Our proposed technique provides low computational and implementation complexity due to the two-level selection scheme. Furthermore, we show that our proposed scheme does not lose in diversity compared with existing cooperation techniques and that all policies can benefit by the employment of the SIC scheme.
Autors: Christodoulos Skouroumounis;Constantinos Psomas;Ioannis Krikidis;
Appeared in: IEEE Transactions on Communications
Publication date: Sep 2017, volume: 65, issue:9, pages: 4049 - 4064
Publisher: IEEE
 
» Low-Complexity Message-Passing Cooperative Localization in Wireless Sensor Networks
Abstract:
This letter proposes a low-complexity message-passing cooperative localizer for wireless sensor networks with (un-)quantized time-of-arrival (TOA) measurements. The collaborative positioning problem is first converted as a generalized nonlinear mixing problem, and then resolved by our developed extended generalized approximate message passing (EGAMP) algorithm. The EGAMP localizer iterates between Taylor expanding the nonlinear mixing problem as a linear mixing one, and recovering positions by one-step GAMP. It successfully handles the quantization losses of quantized TOAs. Its computational complexity is three orders lower than that of belief propagation localizers. Based on our experimental results, the EGAMP localizer gives the state-of-the-art positioning performances, and is robust to quantization losses.
Autors: Shengchu Wang;Feng Luo;Xiaojun Jing;Lin Zhang;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 2081 - 2084
Publisher: IEEE
 
» Low-Complexity Model Predictive Stator Current Control of DFIG Under Harmonic Grid Voltages
Abstract:
This paper proposes a low-complexity model predictive stator current control (LC-MPSCC) strategy of the doubly fed induction generator (DFIG) under harmonic grid voltage conditions. Sinusoidal stator currents are ensured to be injected into the power grid due to the direct control of the stator currents rather than the rotor currents. No extractions of harmonic voltages or currents are needed in the proposed LC-MPSCC strategy. Conventional resonant regulators that are usually adopted to eliminate the harmonic components in the stator currents are also avoided. Thus, the control system complexity can be decreased. To reduce the iterative computation process in the predictive control strategy, a low-complexity method is designed and only two predictions are needed, which is much smaller than the conventional predictive control that needs seven predictions in a two-level three-phase inverter. The low-complexity method enables higher sampling frequency for better steady performance. Finally, simulation and experimental results on a 1-kW DFIG system are provided to validate the effectiveness of the LC-MPSCC strategy.
Autors: Chenwen Cheng;Heng Nian;
Appeared in: IEEE Transactions on Energy Conversion
Publication date: Sep 2017, volume: 32, issue:3, pages: 1072 - 1080
Publisher: IEEE
 
» Low-Complexity Semiblind Channel Estimation in Massive MU-MIMO Systems
Abstract:
Massive multi-user multiple-input multiple-output (MU-MIMO) systems are a promising solution for achieving high throughput and robust transmission in next generation mobile communications. Achieving the optimal transceiver design in such systems requires an accurate knowledge of the channel state information. However, in massive MU-MIMO systems, the quality of the channel estimates is often degraded by pilot contamination. In this paper, we propose a low-complexity semiblind channel estimation algorithm to mitigate the ill effects of pilot contamination. In the proposed approach, the received signals are first projected onto the subspace with minimal interference, where the bases of this subspace are determined recursively via a low-complexity modified power method. An initial estimate of the projected channel coefficients is then made based on a small number of pilot symbols. Finally, data symbols are detected and the channel estimation is refined alternatively. Compared with existing channel estimation methods, the proposed algorithm has lower complexity due to the subspace projection and innovation process. An asymptotic analysis reveals that the mean square error of the channel estimates is inversely proportional to the length of the data symbols. Simulation results demonstrate that the proposed algorithm outperforms the existing works and alleviates the pilot contamination effects effectively.
Autors: Chao-Yi Wu;Wan-Jen Huang;Wei-Ho Chung;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Sep 2017, volume: 16, issue:9, pages: 6279 - 6290
Publisher: IEEE
 
» Low-Complexity Soft-Decision Concatenated LDGM-Staircase FEC for High-Bit-Rate Fiber-Optic Communication
Abstract:
A concatenated soft-decision forward error correction (FEC) scheme consisting of an inner low-density generator-matrix (LDGM) code and an outer staircase code is proposed. The soft-decision LDGM code is used for error reduction, while the majority of bit errors are corrected by the low-complexity hard-decision staircase code. Decoding complexity of the concatenated code is quantified by a score based on the number of edges in the LDGM code Tanner graph, the number of decoding iterations, and the number of staircase code decoding operations. The inner LDGM ensemble is designed by solving an optimization problem, which minimizes the product of the average node degree and an estimate of the required number of decoding iterations. A search procedure is used to find the inner and outer code pair with lowest complexity. The design procedure results in a Pareto-frontier characterization of the tradeoff between net coding gain and complexity for the concatenated code. Simulations of code designs at overhead showed that the proposed scheme achieves net coding gains equivalent to existing soft-decision FEC solutions, with up to reduction in complexity.
Autors: Lei M. Zhang;Frank R. Kschischang;
Appeared in: Journal of Lightwave Technology
Publication date: Sep 2017, volume: 35, issue:18, pages: 3991 - 3999
Publisher: IEEE
 
» Low-Gain Integral Control for Multi-Input Multioutput Linear Systems With Input Nonlinearities
Abstract:
We consider the inclusion of a static antiwindup component in a continuous-time low-gain integral controller in feedback with a multi-input multi-output stable linear system subject to an input nonlinearity (from a class of functions that includes componentwise diagonal saturation). We demonstrate that the output of the closed-loop system asymptotically tracks every constant reference vector, which is “feasible” in a natural sense, provided that the integrator gain is sufficiently small. Robustness properties of the proposed control scheme are investigated and three examples are discussed in detail.
Autors: Chris Guiver;Hartmut Logemann;Stuart Townley;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4776 - 4783
Publisher: IEEE
 
» Low-Leakage ESD Power Clamp Design With Adjustable Triggering Voltage for Nanoscale Applications
Abstract:
A low-leakage electrostatic discharge power clamp with adjustable triggering voltage ( is proposed in this paper. By enabling the static detection path using the transient one, the proposed clamp achieves a wide range of adjustable while maintaining low standby leakage current (, which overcomes the flaw of traditional static clamps. Besides, the adjustable with low is attractive for nanoscale applications. Moreover, the proposed clamp achieves enhanced false-triggering immunity over traditional transient clamps. The proposed clamp is successfully verified in a 65-nm CMOS process. Aside from silicon verifications, detailed comparisons with prior arts and practical application concerns are also addressed in this paper.
Autors: Guangyi Lu;Yuan Wang;Yize Wang;Xing Zhang;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3569 - 3575
Publisher: IEEE
 
» Low-Loss SOI-LIGBT With Triple Deep-Oxide Trenches
Abstract:
A novel 500-V silicon-on-insulator lateral insulated gate bipolar transistor (SOI-LIGBT) is proposed for the first time in this paper. The device features triple deep-oxide trenches (TDOT) arranged in the drift region. The depths of the trenches near the emitter side ( and near the collector side ( are shallower than that of the trench ( located in the silicon region between and . Compared with a reported SOI-LIGBT with dual deep-oxide trenches (DDOT), the shallow trench near the emitter side ( in the proposed TDOT SOI-LIGBT alleviates the JFET effect between the P-body region and , resulting in a lower on-state voltage drop (. In the off-state, the electric potential sustained by the TDOT is higher than that of the DDOT. At the same breakdown voltage of 560 V, the length of silicon region between and N-buffer region ( is reduced from for the DDOT SOI-LIGBT to for the proposed TDOT SOI-LIGB- , indicating a smaller number of stored carries at the collector side and thereby a faster turn-off in the proposed TDOT SOI-LIGBT. The experiments demonstrate that the proposed TDOT SOI-LIGBT achieves turn-off loss (% lower than the DDOT SOI-LIGBT at the same of 1.53 V.
Autors: Long Zhang;Jing Zhu;Minna Zhao;Siyang Liu;Weifeng Sun;Longxing Shi;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Sep 2017, volume: 64, issue:9, pages: 3756 - 3761
Publisher: IEEE
 
» Low-Power LDPC-CC Decoding Architecture Based on the Integration of Memory Banks
Abstract:
This brief proposes a low-power low-density parity check convolutional code (LDPC-CC) decoder that is fully compatible with the IEEE 1901 standard. The proposed architecture merges multiple memory banks into one to make it consume much less power than the conventional architecture. Memory operations conducted by all the unit processors are synchronized in the proposed decoder to merge the memory and avoid any possible data hazard. The data hazard happens when a unit processor tries to read a log-likelihood ratio before a different processor updates it, degrading the error-correcting performance. Memory-access patterns appearing in a memory-based LDPC-CC decoder are formulated to determine the size of a sliding window adequate for decoding. Experimental results show that the decoding architecture employing the merged memory and the proper window size reduces the power consumption by up to 40% compared to the conventional architecture that employs multiple memory banks.
Autors: Injae Yoo;In-Cheol Park;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Sep 2017, volume: 64, issue:9, pages: 1057 - 1061
Publisher: IEEE
 
» Low-Profile High-Power Optically Addressed Phased Array Antenna
Abstract:
A low-profile optically fed ultra-wideband-connected array (CA) antenna with increased operational power is presented. Introduction of a miniature optical prism into the fiber optic feed enables an efficient 90° coupling to a high-power charge-compensated-modified uni-travelling carrier photodiode connected directly at the feed point of an integrated CA antenna element. This technique significantly reduces the array profile and, herein, is implemented into a 1-D CA antenna array consisting of eight photodiode-coupled active dipole elements. The experimentally verified array achieves effective beamforming and beam steering over a 3-dB bandwidth of 6–17 GHz, as well as a peak effective isotropic radiated power of 27.5 dBm at 13 GHz.
Autors: Dylan D. Ross;Matthew R. Konkol;Shouyuan Shi;Charles E. Harrity;Andrew A. Wright;Christopher A. Schuetz;Dennis W. Prather;
Appeared in: Journal of Lightwave Technology
Publication date: Sep 2017, volume: 35, issue:18, pages: 3894 - 3900
Publisher: IEEE
 
» Low-Temperature Characterization of Cu–Cu:Silica-Based Programmable Metallization Cell
Abstract:
In this letter, low-temperature characterization of Cu–Cu:silica programmable metallization cells (PMC) is presented. Our results show that the PMC device is functional even at 4 K and that the low resistance state is essentially unaffected by temperature whereas the high resistance state increases with decreasing temperature. A direct tunneling model is applied to explain the temperature independent low-resistance state.
Autors: W. Chen;N. Chamele;Y. Gonzalez-Velo;H. J. Barnaby;M. N. Kozicki;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1244 - 1247
Publisher: IEEE
 
» Low-Temperature Solution-Based In2O3 Channel Formation for Thin-Film Transistors Using a Visible Laser-Assisted Combustion Process
Abstract:
This letter reports the low-temperature solution-based fabrication of indium oxide (In2O3) thin-film transistors (TFTs) using a visible laser-assisted urea combustion process. An In2O3 precursor solution containing a small amount of urea absorbed the photon energy from a blue laser and started the combustion of urea to form a crystallized In2O3 phase. Atomic force microscopy and X-ray diffraction showed that both laser radiation and urea combustion together are necessary to convert a dried precursor solution layer to a crystallized In2O3 phase. A TFT fabricated from the 0.2-mol% urea-added solution and laser annealed with a 250-J/cm energy fluence exhibited superior transfer characteristics compared with the TFTs fabricated either without urea addition or with small energy fluence radiation. Based on these results and considering the price of blue laser diodes, this technique can be an economical solution for the fabrication of oxide semiconductor TFTs on flexible substrates with a low melting point.
Autors: Jae-Won Choi;Soo-Yeun Han;Manh-Cuong Nguyen;An Hoang-Thuy Nguyen;Jung Yeon Kim;Sujin Choi;Jonggyu Cheon;Hyungmin Ji;Rino Choi;
Appeared in: IEEE Electron Device Letters
Publication date: Sep 2017, volume: 38, issue:9, pages: 1259 - 1262
Publisher: IEEE
 
» Lower Bounds on the Size of Smallest Elementary and Non-Elementary Trapping Sets in Variable-Regular LDPC Codes
Abstract:
Trapping sets are known to be the main cause for the error floor of low-density parity-check (LDPC) codes. They are often classified by their size and the number of unsatisfied check nodes in their subgraph. Trapping sets can be partitioned into two categories of elementary and non-elementary, where the first category are those whose subgraph only contains degree-1 and degree-2 check nodes. Empirical results have shown that often the most harmful trapping sets are elementary. In this letter, we derive a lower bound on the size of the smallest non-elementary trapping sets for a given in variable-regular LDPC codes. The derived lower bound demonstrates that the size of the smallest possible non-elementary trapping set is, in general, larger than that of an elementary trapping set with the same value. This provides a theoretical justification as to why non-elementary trapping sets are often not among the most harmful trapping sets.
Autors: Yoones Hashemi;Amir H. Banihashemi;
Appeared in: IEEE Communications Letters
Publication date: Sep 2017, volume: 21, issue:9, pages: 1905 - 1908
Publisher: IEEE
 
» LS-Join: Local Similarity Join on String Collections
Abstract:
String similarity join, as an essential operation in applications including data integration and data cleaning, has attracted significant attention in the research community. Previous studies focus on global similarity join. In this paper, we study local similarity join with edit distance constraints, which finds string pairs from two string collections that have similar substrings. We study two kinds of local similarity join problems: checking local similar pairs and locating local similar pairs. We first consider the case where if two strings are locally similar to each other, they must share a common gram of a certain length. We show how to do efficient local similarity verification based on a matching gram pair. We propose two pruning techniques and an incremental method to further improve the efficiency of finding matching gram pairs. Then, we devise a method to locate the longest similar substring pair for two local similar strings. We conducted a comprehensive experimental study to evaluate the efficiency of these techniques.
Autors: Jiaying Wang;Xiaochun Yang;Bin Wang;Chengfei Liu;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 1928 - 1942
Publisher: IEEE
 
» Lung Ultrasound Surface Wave Elastography: A Pilot Clinical Study
Abstract:
A lung ultrasound surface wave elastography (LUSWE) technique is developed to measure superficial lung tissue elastic properties. The purpose of this paper was to translate LUSWE into clinical studies for assessing patients with interstitial lung disease (ILD) and present the pilot data from lung measurements on 10 healthy subjects and 10 patients with ILD. ILD includes multiple lung disorders in which the lung tissue is distorted and stiffened by tissue fibrosis. Chest radiography and computed tomography are the most commonly used techniques for assessing lung disease, but they are associated with radiation and cannot directly measure lung elastic properties. LUSWE provides a noninvasive and nonionizing technique to measure the elastic properties of superficial lung tissue. LUSWE was used to measure regions of both lungs through six intercostal spaces for patients and healthy subjects. The data are presented as wave speed at 100, 150, and 200 Hz at the six intercostal spaces. As an example, the surface wave speeds are, respectively, 1.88 ± 0.11 m/s at 100 Hz, 2.74 ± 0.26 m/s at 150 Hz, and 3.62 ± 0.13 m/s at 200 Hz for a healthy subject in the upper right lung; this is in comparison to measurements from an ILD patient of 3.3 ± 0.37 m/s at 100 Hz, 4.38 ± 0.33 m/s at 150 Hz, and 5.24 ± 0.44 m/s at 200 Hz in the same lung space. Significant differences in wave speed between healthy subjects and ILD patients were found. LUSWE is a safe and noninvasive technique which may be useful for assessing ILD.
Autors: Xiaoming Zhang;Thomas Osborn;Boran Zhou;Duane Meixner;Randall R. Kinnick;Brian Bartholmai;James F. Greenleaf;Sanjay Kalra;
Appeared in: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Publication date: Sep 2017, volume: 64, issue:9, pages: 1298 - 1304
Publisher: IEEE
 
» Magnetic Field Analysis in Shell-Like Spherical Induction Machines with Zenithal Traveling Waves
Abstract:
In this paper, a magnetic field analysis is done for spherical shell-like induction machines with a zenithal progressive magnetic traveling wave, using an analytical model in spherical coordinates. These analytical models have major importance in the simulation, project, and preliminary optimization of devices due to its analytical solutions and physical insight. The magnetic field analysis is made for a shell-like induction machine for the study of its electromagnetic and mechanical quantities, as the magnetic field, induced currents, and electromagnetic torque. The developed model is validated, first with a set of generic windings distributions using the results of a commercial finite element analysis (FEA) tool and, second, validated by comparing with the results from the shell-like induction machine prototype. The results obtained from the analytical model are very close to the ones obtained by the FEA tool and from the prototype tests.
Autors: João Filipe Pereira Fernandes;Vitor Maló Machado;Paulo J. Costa Branco;
Appeared in: IEEE Transactions on Energy Conversion
Publication date: Sep 2017, volume: 32, issue:3, pages: 1081 - 1089
Publisher: IEEE
 
» Magnetic Field Characteristics of Wet Belt Permanent High Gradient Magnetic Separator and Its Full-Scale Purification for Garnet Ore
Abstract:
Purification of non-metallic ores has received considerable attention in the recent decade. In this investigation, the magnetic field characteristics of the innovative plate-type permanent magnet in wet belt permanent high gradient magnetic separator (WBHGMS) were analyzed; then, its full-scale purification of a garnet ore was introduced, and its performance dependences on the key operational parameters, i.e., magnet length, belt rotation speed, and feed particle size, were respectively examined. The separator produced a high-quality non-magnetic product assaying 2.00% Fe at an iron removal rate of 95.00% from the ore assaying 13.10% Fe. It was thus concluded that this WBHGMS separator has provided a promising method for the purification of non-metallic ores.
Autors: Luzheng Chen;Yongming Zheng;Jianwu Zeng;Yongxing Zheng;Jian Liu;
Appeared in: IEEE Transactions on Magnetics
Publication date: Sep 2017, volume: 53, issue:9, pages: 1 - 5
Publisher: IEEE
 
» Major Trends Impacting Power Systems [From the Editor's Desk]
Abstract:
Presents the introductory editorial for this issue of the publication.
Autors: Lanny Floyd;
Appeared in: IEEE Industry Applications Magazine
Publication date: Sep 2017, volume: 23, issue:5, pages: 3 - 3
Publisher: IEEE
 
» Making VTM Ever More Exciting [From the Editor]
Abstract:
Presents the introductory editorial for this issue of the publication.
Autors: Klaus David;
Appeared in: IEEE Vehicular Technology Magazine
Publication date: Sep 2017, volume: 12, issue:3, pages: 3 - 3
Publisher: IEEE
 
» Managing Temporal Constraints with Preferences: Representation, Reasoning, and Querying
Abstract:
Representing and managing temporal knowledge, in the form of temporal constraints, is a crucial task in many areas, including knowledge representation, planning, and scheduling. The current literature in the area is moving from the treatment of “crisp” temporal constraints to fuzzy or probabilistic constraints, to account for preferences and\or uncertainty. Given a set of temporal constraints, the evaluation of the tightest implied constraints is a fundamental task, which is essential also to provide reliable query-answering facilities. However, while such tasks have been widely addressed for “crisp” temporal constraints, they have not attracted enough attention in the “non-crisp” context yet. We overcome such a limitation, by (i) extending quantitative temporal constraints to cope with preferences, (ii) defining a temporal reasoning algorithm which evaluates the tightest temporal constraints, and (iii) providing suitable query-answering facilities based on it.
Autors: Paolo Terenziani;Antonella Andolina;Luca Piovesan;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 2067 - 2071
Publisher: IEEE
 
» Mandatory Content Access Control for Privacy Protection in Information Centric Networks
Abstract:
Several Information Centric Network (ICN) architectures have been proposed as candidates for the future Internet, aiming to solve several salient problems in the current IP-based Internet architecture such as mobility, content dissemination and multi-path forwarding. In general, security and privacy are considered as essential requirements in ICN. However, existing ICN designs lack built-in privacy protection for content providers (CPs), e.g., any router in an Internet Service Provider in ICN can cache any content, which may result in information leakage. In this paper, we propose Mandatory Content Access Control (MCAC), a distributed information flow control mechanism to enable a content provider to control which network nodes can cache its contents. In MCAC, a CP defines different security labels for different contents, and content routers check these labels to decide if a content object should be cached. To ensure correct enforcement of MCAC, we also propose a design of a trusted architecture by extending existing mainstream router architectures. We evaluate the performance of MCAC in the NS-3 simulator. The simulation results show that enforcing MCAC in routers does not introduce significant overhead in content forwarding.
Autors: Qi Li;Ravi Sandhu;Xinwen Zhang;Mingwei Xu;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Sep 2017, volume: 14, issue:5, pages: 494 - 506
Publisher: IEEE
 
» Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging
Abstract:
Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.
Autors: Daniele Ravì;Himar Fabelo;Gustavo Marrero Callic;Guang-Zhong Yang;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Sep 2017, volume: 36, issue:9, pages: 1845 - 1857
Publisher: IEEE
 
» Manipulation Over Phase Transformation in Iron Oxide Nanoparticles via Calcination Temperature and Their Effect on Magnetic and Dielectric Properties
Abstract:
Iron oxide nanoparticles (IONPs) have gained technological importance in many fields that broadly includes health, environment, and energy applications. Consequently, the synthesis of IONPs with different phases and morphologies possesses significant interest. Therefore, here we report the facile synthesis of IONPs through the hydrothermal method followed by calcination process at different temperatures (300 °C, 500 °C, and 700 °C) and studied the influence of various phases of IONPs on their magnetic and dielectric properties. The structural studies using X-ray diffraction confirmed that the as-prepared material possesses the Fe3O4 phase, and the increasing calcination temperatures leads to the phase transformation from maghemite (-Fe2O3 to hematite (-Fe2O3 phase. The morphological studies revealed that the as-prepared material possesses flaky morphology with a size around 20 nm, -Fe2O3 to have nanoparticles of sizes around 50 nm, and -Fe2O3 phase with mixed morphology of hexagonal and elongated shaped particles with size ranges from 60–140 nm. The optical properties of synthesized materials revealed that the band gap energy is found to be varied in between 2 and 2.7 eV depending upon the phase of IONPs. The hysteresis behavior of as-prepared and calcined IONPs at 300 °C and 500 °C indicated the soft-ferromagnetic properties of the phases. However, the IONPs prepared at 700° showed the weak-ferromagn- tic property due to the existence of mixed -Fe2O3 phase. All the calcined IONPs showed the soft-ferromagnetic properties with saturation magnetization () that varied in between 47.88 and 0.35 emu/g. The occurrence of the reduced ascribed to the phase transformation of the respective IONPs system. The dielectric studies of IONPs exhibited drastic variations with increasing frequency and with respect to their phase.
Autors: P. Bhavani;N. Ramamanohar Reddy;I. Venkata Subba Reddy;M. Sakar;
Appeared in: IEEE Transactions on Magnetics
Publication date: Sep 2017, volume: 53, issue:9, pages: 1 - 5
Publisher: IEEE
 
» MAS Consensus and Delay Limits Under Delayed Output Feedback
Abstract:
In this technical note, we study the consensus problem for discrete-time multi-agent systems over an undirected, fixed network communication graph, focusing on the robustness of consensus with respect to communication delay. We assume that the agents' input is subject to a constant albeit possibly unknown time delay, and is generated by a distributed dynamic output feedback control protocol. Drawing upon concepts and techniques from robust control, notably those concerning gain margin optimization and analytic interpolation, we derive explicit, closed-form conditions for general linear agents to achieve consensus. Our results display an explicit dependence of the consensus condition on the delay value as well as on the agent's unstable poles and non-minimum phase zeros, showing that delayed communication between agents will generally hinder consensus and impose restrictions on the network topology. We also show that a lower bound on the maximal delay allowable for consensus can be computed by a simple line search method.
Autors: Tian Qi;Li Qiu;Jie Chen;
Appeared in: IEEE Transactions on Automatic Control
Publication date: Sep 2017, volume: 62, issue:9, pages: 4660 - 4666
Publisher: IEEE
 
» Massive Machine Type Communication With Data Aggregation and Resource Scheduling
Abstract:
To enable massive machine type communication (mMTC), data aggregation is a promising approach to reduce the congestion caused by a massive number of machine type devices (MTDs). In this paper, we consider a two-phase cellular-based mMTC network, where MTDs transmit to aggregators (i.e., aggregation phase) and the aggregated data is then relayed to base stations (i.e., relaying phase). Due to the limited resources, the aggregators not only aggregate data, but also schedule resources among MTDs. We consider two scheduling schemes: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). By leveraging the stochastic geometry, we present a tractable analytical framework to investigate the signal-to-interference ratio (SIR) for each phase, thereby computing the MTD success probability, the average number of successful MTDs and probability of successful channel utilization, which are the key metrics characterizing the overall mMTC performance. Our numerical results show that, although the CRS outperforms the RRS in terms of SIR at the aggregation phase, the simpler RRS has almost the same performance as the CRS for most of the cases with regards to the overall mMTC performance. Furthermore, the provision of more resources at the aggregation phase is not always beneficial to the mMTC performance.
Autors: Jing Guo;Salman Durrani;Xiangyun Zhou;Halim Yanikomeroglu;
Appeared in: IEEE Transactions on Communications
Publication date: Sep 2017, volume: 65, issue:9, pages: 4012 - 4026
Publisher: IEEE
 
» Massive MIMO Performance With Imperfect Channel Reciprocity and Channel Estimation Error
Abstract:
Channel reciprocity in time-division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems can be exploited to reduce the overhead required for the acquisition of channel state information (CSI). However, perfect reciprocity is unrealistic in practical systems due to random radio-frequency (RF) circuit mismatches in uplink and downlink channels. This can result in a significant degradation in the performance of linear precoding schemes, which are sensitive to the accuracy of the CSI. In this paper, we model and analyse the impact of RF mismatches on the performance of linear precoding in a TDD multi-user massive MIMO system, by taking the channel estimation error into considerations. We use the truncated Gaussian distribution to model the RF mismatch, and derive closed-form expressions of the output signal-to-interference-plus-noise ratio for maximum ratio transmission and zero forcing precoders. We further investigate the asymptotic performance of the derived expressions, to provide valuable insights into the practical system designs, including useful guidelines for the selection of the effective precoding schemes. Simulation results are presented to demonstrate the validity and accuracy of the proposed analytical results.
Autors: De Mi;Mehrdad Dianati;Lei Zhang;Sami Muhaidat;Rahim Tafazolli;
Appeared in: IEEE Transactions on Communications
Publication date: Sep 2017, volume: 65, issue:9, pages: 3734 - 3749
Publisher: IEEE
 
» Matching for Concurrent Harmonic Sensing in an ${M}$ -Phase Mixer-First Receiver
Abstract:
This brief proposes the use of passive mixer-first receiver topology to sense signals at higher LO harmonics. The advantages of such a receiver include sensing of multiple bands concurrently and reduced tuning range requirements in the frequency synthesizer. The single and joint harmonic matching performance of a zero-IF -phase mixer-first receiver is analyzed. It is shown that minimum possible return loss for joint matching occurs when the geometric mean of input impedances at the highest and lowest sensing bands equals the antenna impedance. The noise figure (NF) when sensing higher order LO harmonics is shown to result in only modest degradation, with the loss becoming even less with increasing number of LO phases. As an example, a 12-phase harmonicsensing mixer first receiver is simulated and its performance at first, third, and fifth harmonics is evaluated in terms of input matching and NF.
Autors: Esmail Babakrpur;Won Namgoong;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Sep 2017, volume: 64, issue:9, pages: 1017 - 1021
Publisher: IEEE
 
» Matching Theory for Distributed User Association and Resource Allocation in Cognitive Femtocell Networks
Abstract:
In this paper, a novel framework is proposed to jointly optimize user association and resource allocation in the uplink cognitive femtocell network (CFN). In the considered CFN, femtocell base stations (FBSs) are deployed to serve a set of femtocell user equipments (FUEs) by reusing subchannels used in a macrocell base station (MBS). The problem of joint user association, subchannel assignment, and power allocation is formulated as an optimization problem, in which the goal is to maximize the overall uplink throughput while guaranteeing FBSs overloading avoidance, data rate requirements of the served FUEs, and MBS protection. To solve this problem, a distributed framework based on the matching game is proposed to model and analyze the interactions between the FUEs and FBSs. Using this framework, distributed algorithms are developed to enable the CFN to make decisions about user association, subchannel allocation, and transmit power. The algorithms are then shown to converge to a stable matching and exhibit a low computational complexity. Simulation results show that the proposed approach yields a performance improvement in terms of the overall network throughput and outage probability, with a small number of iterations to converge.
Autors: Tuan LeAnh;Nguyen H. Tran;Walid Saad;Long Bao Le;Dusit Niyato;Tai Manh Ho;Choong Seon Hong;
Appeared in: IEEE Transactions on Vehicular Technology
Publication date: Sep 2017, volume: 66, issue:9, pages: 8413 - 8428
Publisher: IEEE
 
» Matheuristic with machine-learning-based prediction for software-defined mobile metro-core networks
Abstract:
In general, humans follow a routine with highly predictable daily movements. For instance, we commute from home to work on a daily basis and visit a selected set of places for commercial and recreational purposes during the nights and weekends. The use of mobile phones increases when commuting via public transportation, during lunch breaks, and at night. Such regular behavior creates predictable spatiotemporal fluctuations of traffic patterns. In this paper, we introduce a matheuristic for dynamic optical routing, which can be implemented as an application into a software-defined mobile carrier network. We use machine learning to predict tidal traffic variations in a mobile metro-core network, which allows us to solve off-line mixed-integer linear programming instances of an optical routing (and wavelength) assignment optimization problem. The optimal results are used to favor near-optimal on-line routing decisions. Results demonstrate the effectiveness of our on-line methodology, with results that match almost perfectly the behavior of a network that performs optical routing reconfiguration with a perfect, oracle-like traffic prediction and the solution of an optimization problem.
Autors: Rodolfo Alvizu;Sebastian Troia;Guido Maier;Achille Pattavina;
Appeared in: IEEE/OSA Journal of Optical Communications and Networking
Publication date: Sep 2017, volume: 9, issue:9, pages: D19 - D30
Publisher: IEEE
 
» Maximizing Acceptance in Rejection-Aware Spatial Crowdsourcing
Abstract:
With the rapid development of mobile networks and the widespread usage of mobile devices, spatial crowdsourcing, which refers to assigning location-based tasks to moving workers, has drawn increasing attention. One of the important issues in spatial crowdsourcing is task assignment, which allocates tasks to appropriate workers. However, existing works generally assume that no rejection would happen after the task assignment is completed by the server. Ignorance of such an operation can lead to low system throughput. Thus, in this paper, we take workers’ rejection into consideration and try to maximize workers’ acceptance in order to improve the system throughput. Specifically, we first formally define the problem of maximizing workers’ acceptance in rejection-aware spatial crowdsourcing. Unfortunately, the problem is NP-hard. We propose two exact solutions to obtain the optimal assignment, but they are not efficient enough and not scalable for large inputs. Then, we present four approximation approaches for improving the efficiency. Finally, we show the effectiveness of the proposed pruning strategy for the exact solutions and the superiority of the proposed Greedy algorithm over other approximation methods through extensive experiments.
Autors: Libin Zheng;Lei Chen;
Appeared in: IEEE Transactions on Knowledge and Data Engineering
Publication date: Sep 2017, volume: 29, issue:9, pages: 1943 - 1956
Publisher: IEEE
 
» Maximum Efficiency Point Tracking (MEPT) for Variable Speed Small Hydropower Plant With Neural Network Based Estimation of Turbine Discharge
Abstract:
The paper presents the control system of a small hydropower plant (SHP) working at variable speed operation (VSO). In general, VSO increases the turbine operating discharge and gives higher efficiency over a wide operating range. It is particularly advantageous under conditions different from the original design conditions. Changing of the hydrological conditions requires adjustments to the control system; therefore, the new maximum efficiency point tracking (MEPT) algorithm is proposed. The MEPT algorithm implemented in the load controller employs the gradient method. The water level governor based on the PI controller combined with the adaptive load controller is analyzed. The troublesome measurement of the turbine discharge is replaced by the neural-network-based estimator. The correlation analysis of the system parameters was performed by using principal component analysis. The proposed algorithm was implemented in the programmable logic controller and tested on a real low-head SHP of 150 kW power with two single-regulated propeller turbines.
Autors: Dariusz Borkowski;
Appeared in: IEEE Transactions on Energy Conversion
Publication date: Sep 2017, volume: 32, issue:3, pages: 1090 - 1098
Publisher: IEEE
 
» Maximum Power Point Tracking Strategy for a New Wind Power System and Its Design Details
Abstract:
This study presents two methods to improve the maximum power point tracking strategy for a new wind power system that consists of a planetary gear, two permanent magnet synchronous machines, and loads. The generator, the electric motor, and the wind turbine are connected to the sun gear, ring gear, and carrier of planetary gear, respectively. With the aid of an electric motor, the system can track the maximum power without the full-power converter for generator because of its special operating principle. Conventional optimum torque (COT) control method with a torque error feed forward branch is proposed to obtain faster response compared with COT control method. Moreover, considering that the actual power cannot reach the theoretical optimum point due to the loss torque of the system, the COT control with torque loss compensation is described. A method is also proposed to estimate loss torque. Finally, the theoretical analysis is verified by simulation and experiment results.
Autors: Zongze Cui;Liwei Song;Shupei Li;
Appeared in: IEEE Transactions on Energy Conversion
Publication date: Sep 2017, volume: 32, issue:3, pages: 1063 - 1071
Publisher: IEEE
 

Publication archives by date

  2017:   January     February     March     April     May     June     July     August     September     October     November     December    

  2016:   January     February     March     April     May     June     July     August     September     October     November     December    

  2015:   January     February     March     April     May     June     July     August     September     October     November     December    

  2014:   January     February     March     April     May     June     July     August     September     October     November     December    

  2013:   January     February     March     April     May     June     July     August     September     October     November     December    

  2012:   January     February     March     April     May     June     July     August     September     October     November     December    

  2011:   January     February     March     April     May     June     July     August     September     October     November     December    

  2010:   January     February     March     April     May     June     July     August     September     October     November     December    

  2009:   January     February     March     April     May     June     July     August     September     October     November     December    

 
0-C     D-L     M-R     S-Z