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Linear Minimum Mean-Square-Error Transceiver Design for Amplify-and-Forward Multiple Antenna Relaying Systems
Abstract of thesis entitled Linear Minimum Mean-Square-Error Transceiver Design for Amplify-and-Forward Multiple Antenna Relaying Systems submitted by Chengwen Xing for the degree of Doctor of Philosophy at The University of Hong Kong July 7, 2010 Multiple-antenna communication system is an important research topic in the past decades It increases the data rate or diversity in reception, without occupying additional frequency or time resource On the other hand, amplify-and-forward (AF) relaying attracts a lot of attention lately, as it is suitable in cases where the source cannot directly communicate with the destination, but is possible via a relay in the middle The AF relay simply amplifies the received signal without decoding, thus its operation is favorable in implementation The combination of multipleinput multiple-output (MIMO) communication and AF relaying technique is currently under consideration for several future wireless communication standards With the source, relay and destination all equipped with multiple antennas, a natural question is how to allocate the limited power resource to make the communication as efficient as possible This problem is addressed by linear transceiver design in this thesis Transceiver designs for point-to-point MIMO or multi-user MIMO systems have been widely addressed previously However, for AF MIMO relaying system, due to the relaying operation, transceiver design becomes more challenging In this thesis, we start with a fundamental three nodes source-relay-destination MIMO system The forwarding matrix at relay and equalizer at destination are jointly designed, under the realistic scenario that channel estimates in both hop contains Gaussian error Two robust design algorithms are proposed to minimize the mean-square-error (MSE) of the output signal at the destination The first one is an iterative algorithm with its convergence proved analytically The other is an approximated closed-form solution with much lower complexity than the iterative algorithm Next, we consider the AF MIMO orthogonal frequency division multiplexing (OFDM) system over frequency selective fading channels Again, the forwarding matrix at relay and equalizer at destination are jointly designed by minimizing the total MSE of the output signal at the destination, under channel estimation errors However, since OFDM is a multicarrier modulation, transceiver design in such system involves power allocation in both spatial and frequency domains, and thus is more complicated than the first system In the proposed solution, the second-order moments of channel estimation errors in the two hops are first deduced in the frequency domain Then, the optimal designs for both correlated and uncorrelated channel estimation errors are investigated The relationship between the proposed solutions with existing algorithms is also disclosed Finally, we consider the AF MIMO relaying system with multiple users It corresponds to the case where one base station communicates with multiple terminals via one relay station In this system, the source precoder, relay forwarding matrix and destination equalizer are jointly designed by minimum MSE criterion Both uplink and downlink cases are considered It is found that the uplink and downlink transceiver designs share some common features and can be solved by a general iterative algorithm On the other hand, another proposed algorithm for fully loaded or overloaded uplink system is shown to include several existing results as special cases (Total words: 477) Chengwen Xing Linear Minimum Mean-Square-Error Transceiver Design for Amplify-and-Forward Multiple Antenna Relaying Systems by Chengwen Xing B.Eng., Xidian University, Xi’an, P R China A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Department of Electrical and Electronic Engineering) at The University of Hong Kong July 7, 2010 ii Copyright c 2010 Chengwen Xing i Declaration I declare that this thesis represents my own work, except where due acknowledgment is made, and that it has not been previously included in a thesis, dissertation or report submitted to this University or to any other institution for a degree diploma or other qualifications Signed Chengwen Xing To my family iii Acknowledgments First, I am most grateful to my supervisors, Dr Yik-Chung Wu and Dr Ricky Yu-Kwong Kwok I am very lucky to have two very nice supervisors in my Ph.D study I really appreciate Dr Kwok for giving me the opportunity to study in the University of Hong Kong I am deeply indebted to Dr Wu for his patient guidance and encouragement which acquaints me with signal processing and optimization theory The door of his office is always open for me, and he selflessly shares with me his invaluable experience in research He taught me how to read a paper, how to find a direction, how to write a paper and even how to be a teacher I am indebted to Dr Wu for all his help, support and kind consideration This thesis would not be possible without the help from him I would like to express my sincere gratitude to Dr Shaodan Ma, for her helpful reviews, insightful comments and selfless help on my research I would also like to thank Prof Tung-Sang Ng for his encouragement and help in my study Moreover, I would like to thank my friends I have met in the University of Hong Kong over the years: Dr Tyrone Tai-On Kwok, Dr Fanglei Sun, Dr Gan Zheng, Dr Menglong Jiang, Dr Xiaoshan Liu, Dr Yiqing Zhou, Dr Hongzheng Wang, Mei Leng, Lanlan He, Dr Carson Ka-shun Hung, Dr Jianwu Chen, Dr Chiu-Wa Ng, Xiao Li, Jun Zheng, Kun Cai, Xun Cai, Steve, Terry, Jing Xie, Jian Du, Rui Min and Bin Luo for their kindly help iv I would like to thank the University of Hong Kong for providing financial support via postgraduate studentship and CRCG conference grants I must also acknowledge the Department of Electrical and Electronic Engineering for all its support to postgraduate students, including the departmental conference grant Finally, I am seriously indebted to my parents and my wife for their love My wife, Ms Xingyuan Hao has been waiting for me for years in Beijing during my postgraduate study Thanks for her love DISCARD THIS PAGE 97 10 MSE Algorithm by Guan The proposed Algorithm The proposed Algorithm −1 10 NB=4, NR=4, NM,k=4 NB=4, NR=6, NM,k=4 −2 10 10 12 14 16 18 20 P /σ2 (dB) s n Figure 4.7 Total MSEs of the detected data of the Algorithm 1, Algorithm with relaxation and the algorithm proposed in [30] Algorithm can be used for transceiver design in this case Fig 4.7 shows the total data MSEs of Algorithm for uplink and Algorithm with rank relaxation, when Lk = and NM,k = The SNR at BS is fixed at Pr /σξ =20dB The joint relay forwarding matrix and destination equalizer design in [30] is also shown for comparison It can be viewed as a design without source precoders at mobile terminals From Fig 4.7, it can be seen that Algorithm and Algorithm 2, which involve the joint design of precoder, forwarding matrix and equalizer perform better than the algorithm in [30] This indicates the importance of source precoder design in AF relay cellular networks Furthermore, although Algorithm involves a relaxation, its performance is still satisfactory, and is close to that of Algorithm Finally, it can also be concluded that increasing the number of antennas at relay station can greatly improve the performance of uplink transceiver design for all algorithms 98 4.5 Conclusions In this chapter, LMMSE transceiver design for amplify-and-forward MIMO relay cellular networks has been investigated Both uplink and downlink cases were considered In the downlink, precoder at base station, forwarding matrix at relay station and equalizer at mobile terminals were jointly designed by an iterative algorithm On the other hand, in the uplink case, we demonstrated that in general the transceiver design problem can be solved by an iterative algorithm with the same structure as in the downlink case Furthermore, for the fully loaded or overloaded uplink systems, a novel transceiver design algorithm was derived and it includes several existing algorithms for conventional point-to-point or multiuser systems as special cases Finally, simulation results were presented to show the performance advantage of the proposed algorithms over several suboptimal schemes 99 Chapter Conclusions and Future Research 5.1 Conclusions In this thesis, the joint design of linear relay forwarding matrix and destination equalizer for dual-hop single-user AF MIMO relay systems with Gaussian random channel uncertainties in both hops was first considered The data MSE formula at the destination averaged over the random channel uncertainties was first derived In order to minimize the average MSE, two robust design algorithms were proposed: an iterative algorithm with guaranteed convergence and a closed-form solution with a mild relaxation In the general case, the iterative algorithm has a better performance but a higher complexity Although a mild relaxation is required for the general case, the closed-form solution was shown to be optimal when the column correlation matrix of the channel estimation error in the second hop is an identity matrix Furthermore, we proceed to design robust linear transceiver for AF MIMOOFDM relay systems in which relay forwarding matrix and destination equalizer were jointly designed based on MMSE criterion The linear channel estimators and the corresponding averaged MSE expressions over channel estimation errors were first derived Then a general solution for optimal forwarding and equalizer matrices 100 was proposed When the channel estimation errors are uncorrelated, the optimal solution is in closed-form, and it also includes several existing transceiver design results as special cases On the other hand, when channel estimation errors are correlated, a practical algorithm was introduced Finally, LMMSE transceiver design for AF multiple-antenna relaying cellular networks was investigated, in which multiple mobile terminals communicate with the BS via a relay station As all nodes are equipped with multiple antennas, precoder at source, forwarding matrix at relay and equalizer at destination were jointly designed to minimize the total MSEs of detected data at the destination Both downlink and uplink have been considered It is found that the downlink and uplink transceiver design problems are in the same form, and iterative algorithms with the same structure can be used to solve the design problems For the specific cases of fully loaded or overloaded uplink systems, a novel algorithm is derived and several existing algorithms can be considered as its special cases 5.2 Future Research Directions There are some possible directions for the future research based on the results given in this thesis In this thesis, for the linear robust transceiver design, we focus on minimizing an averaged MSE over channel estimation errors For robust signal processing design, another criterion for robust design is worst-case or min-max This criterion aims at minimizing the objective function at the worst case in an uncertain region which is usually norm-bounded The worst case robust transceiver design for AF MIMO relay systems also has great meaning, which can guarantee the worst case performance In contrast to the transceiver design discussed in this thesis, which minimizes MSE under a power constraint, quality-of-service (QoS) 101 based transceiver design tries to minimize the transmission power under a basic QoS requirement, such as MSE, outage probability, BER and so on It is important to consider the QoS based transceiver design with channel estimation errors for AF MIMO relay systems, which can enlarge the life time of wireless equipments 102 List of References [1] A Scaglione, D L Goeckel, and J N Laneman, “Cooperative communications in mobile Ad Hoc networks,” IEEE Signal Process Mag., vol 23, no 5, pp 18–29, Sep 2006 [2] J N Laneman, D N C Tse, and G W Wornell, “Cooperative diversity in wireless networks: Efficient protocols and outage behavior,” IEEE Trans Inf Theory, vol 50, no 12, pp 3062–3080, Dec 2004 [3] S Stefania, I Toufik, and M backer, LTE, the UMTS Long Term Evolution: From Theory to Practice Wiley, 2009 [4] A Osseiran, etc, “The road to IMT-advanced communication systems: stateof-the-art and innovation areas addressed by the WINNER + project - [topics in radio communications],” IEEE Communication Magazine, vol 47, no 6, pp 38–47, June 2009 [5] V Havary-Nassab, S Shahbazpanahi, A Grami, and Z.-Q Luo, “Distributed beamforming for relay networks based on second-order statistics of the channel state information,” IEEE Trans Signal Process., vol.56, no 9, 4306–4316, Sep 2008 [6] H Bolcskei, R U Nabar, O Oyman, and A J Paulraj, “Capacity scaling laws in MIMO relay networks,” IEEE Trans Wireless Commun., vol 5, no 6, pp 1433–1443, June 2006 [7] E Koyuncu, Y Jing, and H Jafarkhani, “Distributed beamforming in wireless relay networks with quantized feedback,” IEEE J Select Areas Commun., vol 26, no 8, 4306–4316, Oct 2008 [8] Y Jing and H Jafarkhani, “Network beamforming using relays with perfect channel information,” IEEE Trans Inf Theory, vol 55, no 6, pp 2499–2517, June 2009 103 [9] Y Jing and B Hassibi, “Distributed space-time coding in wireless relay networks,” IEEE Trans Wireless Commun., vol 5, no 12, pp 3524–3536, Dec 2006 [10] A S Behbahani, R Merched, and A M Eltawil, “Optimizations of a MIMO relay Network, ” IEEE Trans Signal Process., vol 56, no 10, part 2, pp 5062–5073, Oct 2008 [11] Y Jing and H Jafarkhani, “Using orthogonal and quasi-orthogonal designs in wireless relay networks,” IEEE Trans Inf Theory, vol 53, no 11, pp 4106– 4118, Nov 2007 [12] A del Coso and C Ibars, “Linear relaying for Gaussian mutiple-access and broadcast channels,” IEEE Trans Wireless Commun., vol 8, no 4, pp 2024– 2035, April 2009 [13] X Tang and Y Hua, “Optimal design of non-regenerative MIMO wireless relays,” IEEE Trans Wireless Commun., vol 6, no 4, pp 1398–1407, Apr 2007 [14] O Munoz-Medina, J Vidal, and A Agustin, “Linear transceiver design in nonregenerative relays with channel state information,” IEEE Trans Signal Process., vol 55, no 6, pp 2593–2604, June 2007 [15] H Bolcskei, D Gesbert, C B Papadias, and A.-J Van Der Veen, Space-Time Wireless Systems Cambridge University Press, 2006 [16] E G Larsson and P Stoica, Space-Time Block Coding for Wireless Communications Cambridge University Press, 2003 [17] D Tse and P Viswanath, Fundamentals of Wireless Communications Cambridge University Press, 2005 [18] P Vishwanath and D Tse, “Sum capacity of multiple antenna Gaussian broadcast channel and uplink-downlink duality,” IEEE Trans Inf Theory, vol 49, no 8, pp 1912–1923, Aug 2003 [19] Z.-Q Luo, T N Davidson, G B Giannakis and K M Wong, “Transceiver optimization for block-based multiple access through ISI channels,” IEEE Trans on Signal Process., vol 52, no 4, pp 1037–1052, Apr 2004 [20] S Vishwanath, N Jindal, and A J Goldsmith, “Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels,” IEEE Trans Inf Theory, vol 49, no 10, pp 2658–2668, Oct 2003 104 [21] M Schuber and H Boche, “Solution of the multi-user downlink beamforming problem with indiviudal SINR constraints,” IEEE Trans Veh Thechnol., vol 53, no 1, pp 18–28, Jan 2004 [22] K S Fomadam and S A Jafar, “Duality of MIMO multiple access channel and broadcast channel with amplify-and-forward relays,” IEEE Trans Wireless Commun., vol 58, no 1, pp 221–217, Jan 2010 [23] H Sampath, P Stoica, and A Paulraj, “Generalized linear precoder and decoder design for MIMO channels using the weighted MMSE criterion,” IEEE Trans Commun., vol 49, no 12, pp 2198–2206, Dec 2001 [24] D P Palomar, J M Cioffi, and M A Lagunas, “Joint Tx-Rx beamforming design for multicarrier MIMO channels: A unified framework for convex optimization,” IEEE Trans Signal Process., vol 51, no 9, pp 2381–2399, Sep 2003 [25] F Rey, M Lamarca, and G Vazquez, “Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI,” IEEE Trans Signal Process., vol 53, no 3, pp 1070–1085, Mar 2005 [26] M Joham, W Utschick, and J A Nossek, “Linear transmit processing in MIMO communications systems,” IEEE Trans Signal Process., vol 53, no 8, pp 2700–2712, Aug 2005 [27] B Wang, J Zhang, and A Host-Madsen, “On the capacity of MIMO relay channels,” IEEE Trans Inf Theory, vol 51, no 1, pp 29–43, Jan 2005 [28] S Jin, M R McKay, C Zhong, and K.-K Wong, “Ergodic capacity analysis of amplify-and-forward MIMO dual-hop systems,” IEEE Trans Inf Theory, vol 56, no 5, pp 2204–2224, May 2010 [29] H W Je, B Lee, S Kim, and K B Lee, “Design of non-regenerative MIMOrelay systems with partial channel state information,” in Proc IEEE ICC 2008, May 2008, pp 4441–4445 [30] W Guan and H Luo, “Joint MMSE transceiver design in non-regenerative MIMO relay systems,” IEEE Commun Lett., vol 12, no 7, pp 517–519, July 2008 [31] Y Rong, X Tang, and T Hua, “A unified framework for optimizing linear nonregenerative multicarrier MIMO relay communication systems,” IEEE Trans Signal Process., vol 57, no 12, pp 4837–4851, Dec 2009 105 [32] I Hammerstrom and A Wittneben, “Power allocation schemes for amplifyand-forward MIMO-OFDM relay links, ” IEEE Trans Wireless Commun., vol 6, no 8, pp 2798–2802, Aug 2007 [33] C.-B Chae, T W Tang, R W Health, and S.-Y Cho, “MIMO relaying with linear processing for multiuser transmission in fixed relay networks,” IEEE Trans Signal Process., vol 56, no 2, pp 727–738, Feb 2008 [34] R Zhang, C C Chai, and Y.-C Liang, “Joint beamforming and power control for multiantenna relay broadcast channel with QoS constraints,” IEEE Trans Signal Process., vol 57, no 2, pp 726–737, Feb 2009 [35] B K Chalise and L Vandendorpe, “MIMO relay design for multipoint-tomultipoint communications with imperfect channel state information,” IEEE Trans Signal Process., vol 57, no 7, pp 2785–2796, July 2009 [36] A Pascual-Iserte, D P Palomar, A I Perez-Neira, and M A Lagunas, “A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization”, IEEE Trans Signal Process., vol 54, no 1, pp 346–360, Jan 2006 [37] I E Telatar, “Capacity of multi-antenna Gaussian channels,” European Trans on Telecommu., vol 10, pp 585–595, Nov 1999 [38] S M Kay, Fundamental of Statistical Signal Processing: Estimation Theory Englewood Cliffs, NJ: Prentice-Hall, 1993 [39] R Hunger, M Joham, and W Utschick, “On the MSE-Duality of the broadcast channel and multiple access channel,” IEEE Trans Siganl Process., vol 57, no 2, pp 698–713, Feb 2009 [40] J Zhang, Y Wu, S Zhou, and J Wang, “Joint linear transmitter and receiver design for the downlink of multiuser MIMO systems,” IEEE Commun Lett., vol 9, no 11, pp 991–993, Nov 2005 [41] S Shi, M Chubert, and H Boche, “Rate optimization for multiuser MIMO systems with linear processing,” IEEE Trans Signal Process., vol 56, no 8, pp 4020–4030, Aug 2008 [42] S Serbetli and A Yener, “Transceiver optimization for multiuser MIMO systems,” IEEE Trans Signal Process., vol 52, no 9, pp 214–226, Jan 2004 [43] M Codreanu, A Tolli, M Juntti and M Latva-aho, “Joint design of Tx-Rx beamforming in MIMO downnlink channel,” IEEE Trans Signal Process., vol 55, no 9, pp 4639–4655, Sep 2007 106 [44] S S Christensen, R Agarwal, E de Carvalho and J M Cioffi, “Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design,” IEEE Trans Wireless Commun., vol 7, no 12, pp 4792–4799, Dec 2008 [45] S Shi, M Chubert, and H Boche, “Downlink MMSE transceiver optimization for multiuser MIMO systems: Dulaity and sum-MSE minmization,” IEEE Trans Signal Process., vol 55, no 11, pp 5436–5446, Nov 2007 [46] Frank A Dietrich, Robust Signal Processing for Wireless Communications, Foundations in Signal Processing, Communications and Networking Springer, Dec 2007 [47] A K Gupta and D K Nagar, Matrix Variate Distributions London, U.K.: Chapman&Hall/CRC, 2000 [48] A T James, “Dstributions of matrix variates and latent roots derived from normal samples,” Ann Math Statistics, vol 35, pp 475–501, 1964 [49] L Musavian, M R Nakhi, M Dohler, and A H Aghvami, “Effect of channel uncertianty on the mutual information of MIMO fading channels,” IEEE Trans Veh Technol., vol 56, no 5, pp 2798–2806, Sep 2007 [50] M Ding and S D Blostein, “MIMO minimum total MSE transceiver design with imperfect CSI at both ends,” IEEE Trans Signal Processing, vol 57, no 3, pp 1141–1150, March 2009 [51] S Ulukus and A Yener, “Iterative transmitter and receiver optimization for CDMA networks,” IEEE Trans Wireless Commun., vol 3, no 6, pp 1879– 1884, Nov 2004 [52] D P Bertsekas, Nonlinear Programming, 2nd ed New York: Athena, 2005 [53] E K P Chong and S H Zak, An Introduction to Optimization John wiley & Sons, Inc 1996 [54] A Beck, “Quadratic matrix programming,” SIAM Journal on Optimization, vol 17, no 4, pp 1224–1238, 2007 [55] R A Horn and C R Johnson, Matrix Analysis Cambridge University Press, 1985 [56] A W Marshall and I Olkin, Inequalities: Theory of Majorization and Its Applications New York: Academic Press, 1979 107 [57] F Frachinei and J S Pang, Finite-Dimensional Variational Inequalities and Complementarity Problems Spring Series in Operation Research Volume I, 2003 [58] S Boyd and L Vandenberghe, Convex Optimization Cambridge University Press, 2004 [59] X Zhang, D P Palomar, and B Ottersten, “Statistically robust design of linear MIMO transceiver,” IEEE Trans Signal Process., vol 56, no 8, pp 3678– 3689, Aug 2008 [60] S Ma and T.-S Ng,“Time domain signal detection based on second-order statistics for MIMO-OFDM system”, IEEE Trans Signal Process., vol 55(3), pp 1150-1158, Mar 2007 [61] J Chen, Y.-C Wu, S Ma, and T.-S Ng, “Joint CFO and channel estimation for multiuser MIMO-OFDM systems with optimal training sequences,” IEEE Trans Signal Process., vol 56, no 8, pp 4008–4019, Aug 2008 [62] F Verde, D Darsena, and A Scaglione, “Cooperative Randomized MIMOOFDM Downlink for Multicell Networks: Design and Analysis,” IEEE Trans Signal Process., vol 58, no 1, pp 384–402, Jan 2010 [63] C P Robert, The Bayesian Choice New York: Springer Press, 2001 [64] D P Bertsekas, A Nedic, and A E Ozdaglar, Convex Analysis and Optimization Athena Scientific, 2003 [65] P Stoica and O Besson, “Training sequence deisgn for frequency offset and frequency-selective channel estimation,” IEEE Trans Commun., vol 51, no 11, pp.1910–1917, Nov 2003 [66] M Ghogho and A Swami, “Training design for multipath channel and frequency-Offset Estimation in MIMO systems,” IEEE Trans Signal Processing, vol 54, no 10, pp 3957–3965, Oct 2006 [67] H Minn and N Al-Dhahir, “Optimal training signals for MIMO OFDM channel estimation,” IEEE Trans Wireless Commun., vol 5, no 5, pp 1158–1168, May 2006 [68] J G Andrews, A Ghosh, and R Muhamed, Fundamentals of WiMAX USA: Prentice Hall, 2007 [69] F Ohrtman and K Roeder, Wi-Fi Handbook: Building 802.11 b wireless networks McGraw-Hill, 2003 108 [70] A Beck, A Ben-Tal, and Y C Eldar, “Robust mean-squared error estimation of multiple signals in linear systems affected by model and noise uncertainties”, Math Programming, vol.107 155-187, Springer, 2006 [71] C Xing, S Ma, and Y.-C Wu, “Robust joint design of linear relay precoder and destination equalizer for dual-hop amplify-and-forward MIMO relay systems,” IEEE Trans Signal Process., vol 58, no 4, pp 2273–2283, Apr 2010 [72] L Vandenberghe and S Boyd, “Semidefinite programmming,” SIAM Review, vol 38, no 1, pp.49–95, March 1996 [73] K.-K Wong, A Paulraj, and R D Murch, “Efficient high-performance decoding for overloaded MIMO antenna systems,” IEEE Trans Wireless Commun., vol 6, no 5, pp.1833–1843, May 2007 [74] R de Miguel, V Gardasevic, R R Muller, and F F Knudsen, “On overloaded vector precoding for single-user MIMO channels,” IEEE Trans Wireless Commun., vol 9, no 2, pp 745–753, Feb 2010 [75] S Ma, C Xing, Y Fan, Y.-C Wu, T.-S Ng, and H Vincent Poor, “Iterative Transceiver Design for MIMO AF Relay Networks with Multiple Sources” accepted by IEEE Milcom 2010 [76] M Grant, S Boyd, and Y Y Ye, “CVX: Matlab Software for Disciplined Convex Programming,” available at: http : //www.stanf ord.edu/boyd/cvx/, V.1.0RC3, Feb 2007 109 Vita July 2005 B.Eng in Information Countermeasure, Xidian University September 2006–Present Ph.D candidate, Department of Electrical and Electronic Engineering, The University of Hong Kong He can be reached at the email address xingchengwen@gmail.com 110 List of Publications Journal Articles: Chengwen Xing, Shaodan Ma and Yik-Chung Wu, “On Low Complexity Robust Beamforming with Positive Semi-Definite Constraints,” IEEE Transactions on Signal Processing vol 57, no 12, pp 4942–4945, Dec 2009 Chengwen Xing, Shaodan Ma and Yik-Chung Wu, “Robust Joint Design of Linear Relay Precoder and Destination Equalizer for Dual-Hop Amplify-andForward MIMO Relay Systems,” IEEE Transactions on Signal Processing vol 58, no 4, pp 2273–2283, Apr 2010 Xiao Li, Chengwen Xing, Yik-Chung Wu and S.C Chan, “Timing Estimation and Re-synchronization for Amplify-and-Forward Communication Systems,” IEEE Transactions on Signal Processing vol 58, no 4, pp 2218– 2229, Apr 2010 Chengwen Xing, Shaodan Ma, Yik-Chung Wu and Tung-Sang Ng, “Transceiver Design at Relay and Destination for Dual-Hop Non-regenerative MIMOOFDM Relay Systems Under Channel Uncertainties,” submitted to IEEE Transactions on Signal Processing, revised June 2010 Chengwen Xing, Minghua Xia, Shaodan Ma and Yik-Chung Wu, “Linear MMSE Beamforming Design for Amplify-and-Forward Multi-Antenna Relaying Cellular Networks,” under preparation Chengwen Xing, Shaodan Ma and Yik-Chung Wu, “Robust Joint Transceiver Design for Dual-Hop AF MIMO Relay Systems Using Weighted MMSE Criterion,” under preparation 111 Articles in Refereed Conference Proceedings: Chengwen Xing, Shaodan Ma and Yik-Chung Wu, “Iterative LMMSE Transceiver Design for Dual-Hop AF MIMO Relay Systems Under Channel Uncertainties,” Proceedings of IEEE Personal, Indoor and Mobile Radio Communications Symposium (PIMRC’2009), 2009, Japan Chengwen Xing, Shaodan Ma and Yik-Chung Wu, “Bayesian Robust Linear Transceiver Design for Dual-Hop Amplify-and-Forward MIMO Relay Systems,” Proceedings of IEEE Global Communications Conference (GlobeCom’2009),, 2009, U.S.A Chengwen Xing, Shaodan Ma, Yik-Chung Wu and Tung-Sang Ng, “Robust Beamforming for Amplify-and-Forward MIMO Relay Systems Based on Quadratic Matrix Programming,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’2010), 2010, U.S.A Chengwen Xing, Shaodan Ma, Yik-Chung Wu, Tung-Sang Ng, and H Vincent Poor,“Linear Transceiver Design for Amplify-and-Forward MIMO Relay Systems under Channel Uncertainties,” IEEE Wireless Communications and Networking Conference (WCNC’2010), 2010, Australia Shaodan Ma, Chengwen Xing, Yijia Fan, Yik-Chung Wu, Tung-Sang Ng, and H Vincent Poor, “Iterative Transceiver Design for MIMO AF Relay Networks with Multiple Sources” accepted by IEEE Milcom 2010 (Invited Paper) ... Design for Amplify-and-Forward Multiple Antenna Relaying Systems by Chengwen Xing B.Eng., Xidian University, Xi’an, P R China A thesis submitted in partial fulfillment of the requirements for the... thesis Transceiver designs for point-to-point MIMO or multi-user MIMO systems have been widely addressed previously However, for AF MIMO xi relaying system, due to the relaying operation, transceiver. .. important metric for transceiver design [23–26] Furthermore, based on implementation consideration, linear minimum mean-square-error (LMMSE) transceiver is more preferable compared to its nonlinear counterparts