May 2017 edition – Vol.9 no.5

2023 International Conference on Microelectronics (ICM)
from December 17 to 20, 2023, Abu Dhabi, United Arab Emirates.
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2023 IEEE 11th International Conference on Systems and Control (ICSC)
from December 18 to 20, 2023, Sousse, Tunisia.
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2024 37th International Conference on VLSI Design and 2024 23rd International Conference on Embedded Systems (VLSID)
from January 6 to 10, 2024, Kolkata, India.
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2024 IEEE International Solid-State Circuits Conference (ISSCC)
from February 18 to 22, 2024, San Francisco, California, USA.
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2024 IEEE 15th Latin America Symposium on Circuits and Systems (LASCAS)
from February 27 to March 1, 2024, Punta del Este, Uruguay.
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2024 IEEE Custom Integrated Circuits Conference (CICC)
from April 21 to 24, 2024, Denver, Colorado, USA.
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2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS)
from April 22 to 25, 2024, Abu Dhabi, United Arab Emirates.
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2024 9th International Conference on Integrated Circuits, Design, and Verification (ICDV)
from June 6 to 7, 2024, Hanoi, Vietnam.
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2024 61st ACM/IEEE Design Automation Conference (DAC)
from June 23 to 27, 2024, San Francisco, California, USA.
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2024 IEEE International Conference on Multimedia and Expo (ICME)
from July 15 to 19, 2024, Niagara Falls, Ontario, Canada.
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Prof. Wei-Ping Zhu
Concordia University
Member of ReSMiQ since 2008

Prof. Wei-Ping Zhu received the Ph.D. degree in Electrical Engineering from Southeast University, Nanjing, China. He is currently Professor and graduate program director in the Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada. He was an Associate Professor in the Department of Information Engineering at Nanjing University of Posts and Telecommunications. Dr. Zhu worked as a System Engineer at Nortel Networks and at SR Telecom Inc. in Ottawa. His research interests include digital signal processing fundamentals, speech and statistical signal processing, and signal processing for wireless communication with a particular focus on MIMO systems and cooperative communication. Dr. Zhu has published more than 250 papers in refereed journals and international conferences. He has served as an Associate Editor of several IEEE Transaction journals and is currently an Associate Editor of the Journal of The Franklin Institute. Dr. Zhu was Secretary and Chair of the Digital Signal Processing Technical Committee of the IEEE CAS Society. More details

Below is a selection of publications in recent years followed by representative work.

1. W. Zhang, X. Wu, W.-P. Zhu and L. Yu, "Unsupervized image clustering with SIFT-based soft-matching affinity propagation," in IEEE Signal Processing Letters, vol. 24, no. 4, pp. 461-464, April 2017.
2. M. Parchami, W.-P. Zhu and B. Champagne, "Speech dereverberation using weighted prediction error with correlated inter-frame speech components," in Speech Communication,  vol. 87, pp. 49-57, Jan 2017. 
3. H. Abdzadeh-Ziabari, W.-P. Zhu and M.N.S. Swamy, “Improved coarse timing estimation in OFDM systems using high order statistics” in IEEE Trans. on Communications, vol. 64, no. 12, pp.5239-5253, Dec. 2016.
4. X. Ji, W.-P. Zhu and D. Massicotte, “Transmit power minimization for two-way amplify-and-forward relaying with asymmetric traffic requirements,” in IEEE Trans. on Vehicular Technology, vol. 65, no.12, pp. 9687-9702, Dec. 2016.
5. M. Parchami, W.-P. Zhu, B. Champagne and Eric Plourde, “Recent developments in speech enhancement in the short-time Fourier transform domain,” in IEEE Circuits and Systems Magazine, vol. 16, iss. 3, pp. 45-77, 3^rd Quarter, 2016. (doi: 10.1109/MCAS.2016.2583681)
6. X. He, R. Song and W.-P. Zhu, “Pilot allocation for distributed compressed sensing based sparse channel estimation in MIMO-OFDM systems,” in IEEE Trans. on Vehicular Technology, vol. 65, no.5, pp. 2990-3004, May 2016.
7. X. Wu, W.-P. Zhu and J. Yan, “Direction of arrival estimation for off-grid signals based on sparse Bayesian learning,” in IEEE Sensors Journal, vol. 16, no. 7, pp. 2004-2016, April 2016.
8. M. Lin, J. Ouyang and W.-P. Zhu, “Joint beamforming and power control for device-to-device communications underlying cellular networks,” in IEEE Journal on Selected Areas in Communications, vol. 34, no.1, pp.138-150, Jan. 2016.

Transmit Power Minimization for Two-Way Amplify-and-Forward
Relaying with Asymmetric Traffic Requirements

Two-way relaying (TWR) has received a great deal of research interest as it can enhance the spectrum efficiency and throughput of communication systems. In this work, we consider a half-duplex TWR system as shown in Fig. 1, where two end terminals T_A and T_B want to send, respectively, signal s_A and signal s_B to each other through the assistance of a half-duplex amplify-and-forward (AF) relay. We suppose multiple relays (N) are available but only one relay is selected for relaying cooperation. We addresses the power minimization problem subject to a target quality-of-service (QoS) constraint of the TWR with asymmetric traffic requirements using the AF relaying mode. By transforming the power minimization problem into a two-stage problem and using the traffic information together with the short-term channel knowledge, an optimum power control (OPC) scheme is first proposed, leading to closed-form solutions for individual transmit power at the relay and the sources. Then, by making use of the available diversity of the multiple-relay channel, the joint design of OPC and relay selection (RS) is investigated, eventually resulting in a joint power control and RS (JPCRS) algorithm with two decentralized RS policies for transmit power minimization. It is shown that our proposed strategies can significantly reduce the system transmit power, while ensuring the target QoS of the system, and that the proposed RS algorithm is superior to the conventional max–min and max-sum selection strategies in any traffic and channel conditions in terms of energy saving.

Fig. 2 plots the total power consumption of different RS strategies as a function of the terminal A to relay distance d_AR (the distance between the two terminals is normalized to unity), when the relay number N = 3, the target system outage probability s_Q=0.01 and the diversity gain d=1, respectively. Here we have considered three traffic scenarios, strongly asymmetric, moderately asymmetric and symmetric, as indicated by the target traffic rates r_A and r_B of the two terminals. It shows that the proposed optimum and sub-optimum policies perform much better than the conventional max-sum policy, and better than the max–min policy. Fig. 3 depicts the total power consumption versus the number of relays for selection, where d_AR = d_BR = 0.5, s_Q = 0.01, and d = 1. It is seen that our policies perform better than the conventional max–min and max-sum policies for all the three traffic scenarios. Fig. 3 also shows that the total power consumptions of the optimal and suboptimal policies are almost identical, indicating that the simplified suboptimal policy can replace the optimal one to implement RS.

Fig. 1. Two-time-slot TWR system model.

Fig. 2. Comparison with conventional max–min and max-sum policies for different location of relay.

Fig. 3. Comparison with conventional max–min and max-sum policies for different number of relay candidates.