Efficient soft demodulation of MIMO QPSK via semidefinite relaxation

We develop a computationally efficient and memory efficient approach to (near) maximum a posteriori probability demodulation for MIMO systems with QPSK signalling, based on semidefinite relaxation. Existing approaches to this problem require either storage of a large list of candidate bit-vectors, or the solution of multiple binary quadratic problems. In contrast, the proposed demodulator does not require the storage of a candidate list, and involves the solution of a single (efficiently solvable) semidefmite program per channel use. Our simulation results show that the resulting computational and memory efficiencies are obtained without incurring a significant degradation in performance.

[1]  Björn E. Ottersten,et al.  On the complexity of sphere decoding in digital communications , 2005, IEEE Transactions on Signal Processing.

[2]  Giuseppe Caire,et al.  Iterative multiuser joint decoding: Unified framework and asymptotic analysis , 2002, IEEE Trans. Inf. Theory.

[3]  G. Matz,et al.  Capacity-based performance comparison of MIMO-BICM demodulators , 2008, 2008 IEEE 9th Workshop on Signal Processing Advances in Wireless Communications.

[4]  Zhi-Quan Luo,et al.  Efficient Implementation of a Quasi-Maximum-Likelihood Detector Based on Semi-Definite Relaxation , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[5]  Reinaldo A. Valenzuela,et al.  Simplified processing for high spectral efficiency wireless communication employing multi-element arrays , 1999, IEEE J. Sel. Areas Commun..

[6]  Donald Ervin Knuth,et al.  The Art of Computer Programming , 1968 .

[7]  Zhan Guo,et al.  Algorithm and implementation of the K-best sphere decoding for MIMO detection , 2006, IEEE Journal on Selected Areas in Communications.

[8]  T. Kailath,et al.  Iterative decoding for MIMO channels via modified sphere decoding , 2004, IEEE Transactions on Wireless Communications.

[9]  M. Nekuii,et al.  List-based soft demodulation of MIMO QPSK via semidefinite relaxation , 2007, 2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications.

[10]  H. Vincent Poor,et al.  Iterative (turbo) soft interference cancellation and decoding for coded CDMA , 1999, IEEE Trans. Commun..

[11]  Erik G. Larsson,et al.  Fixed-Complexity Soft MIMO Detection via Partial Marginalization , 2008, IEEE Transactions on Signal Processing.

[12]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[13]  Nikos D. Sidiropoulos,et al.  A Semidefinite Relaxation Approach to MIMO Detection for High-Order QAM Constellations , 2006, IEEE Signal Processing Letters.

[14]  Gerhard Fettweis,et al.  A Fixed-Complexity Smart Candidate Adding Algorithm for Soft-Output MIMO Detection , 2009, IEEE Journal of Selected Topics in Signal Processing.

[15]  Timothy N. Davidson,et al.  A Semidefinite Relaxation Approach to Efficient Soft Demodulation of MIMO 16-QAM , 2009, 2009 IEEE International Conference on Communications.

[16]  Giuseppe Caire,et al.  On maximum-likelihood detection and the search for the closest lattice point , 2003, IEEE Trans. Inf. Theory.

[17]  Helmut Bölcskei,et al.  Soft–Input Soft–Output Single Tree-Search Sphere Decoding , 2009, IEEE Transactions on Information Theory.

[18]  John S. Thompson,et al.  Extending a Fixed-Complexity Sphere Decoder to Obtain Likelihood Information for Turbo-MIMO Systems , 2008, IEEE Transactions on Vehicular Technology.

[19]  Zhi-Quan Luo,et al.  Efficient Implementation of Quasi- Maximum-Likelihood Detection Based on Semidefinite Relaxation , 2009, IEEE Transactions on Signal Processing.

[20]  Ralf R. Müller,et al.  Iterative multiuser joint decoding: optimal power allocation and low-complexity implementation , 2004, IEEE Transactions on Information Theory.

[21]  Alexander Vardy,et al.  Closest point search in lattices , 2002, IEEE Trans. Inf. Theory.

[22]  Y. Nesterov Quality of semidefinite relaxation for nonconvex quadratic optimization , 1997 .

[23]  Patrick Robertson,et al.  A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[24]  Robert W. Heath,et al.  Space-time Chase decoding , 2005, IEEE Transactions on Wireless Communications.

[25]  Babak Hassibi,et al.  High-rate codes that are linear in space and time , 2002, IEEE Trans. Inf. Theory.

[26]  Donald E. Knuth,et al.  The art of computer programming, volume 3: (2nd ed.) sorting and searching , 1998 .

[27]  David P. Williamson,et al.  Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming , 1995, JACM.

[28]  Georgios B. Giannakis,et al.  Approaching MIMO channel capacity with soft detection based on hard sphere decoding , 2006, IEEE Transactions on Communications.

[29]  Joachim Hagenauer,et al.  The List-Sequential (LISS) Algorithm and Its Application , 2007, IEEE Transactions on Communications.

[30]  Andrew C. Singer,et al.  Minimum mean squared error equalization using a priori information , 2002, IEEE Trans. Signal Process..

[31]  M. Nekuii Soft Demodulation Schemes for MIMO Communication Systems , 2008 .

[32]  Ba-Ngu Vo,et al.  Blind ML detection of orthogonal space-time block codes: efficient high-performance implementations , 2006, IEEE Transactions on Signal Processing.

[33]  Timothy N. Davidson,et al.  A Multistack Algorithm for Soft MIMO Demodulation , 2009, IEEE Transactions on Vehicular Technology.

[34]  Zhi-Quan Luo,et al.  Soft quasi-maximum-likelihood detection for multiple-antenna wireless channels , 2003, IEEE Trans. Signal Process..

[35]  Zhi-Quan Luo,et al.  Soft quasi-maximum-likelihood detection for multiple-antenna channels , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[36]  John S. Thompson,et al.  Fixing the Complexity of the Sphere Decoder for MIMO Detection , 2008, IEEE Transactions on Wireless Communications.

[37]  Tricia J. Willink,et al.  Iterative tree search detection for MIMO wireless systems , 2005, IEEE Transactions on Communications.

[38]  B. Ottersten,et al.  Parallel Implementation of a Soft Output Sphere Decoder , 2005, Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005..

[39]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[40]  Joachim Hagenauer,et al.  The turbo principle-tutorial introduction and state of the art , 1997 .

[41]  F. Schreckenbach,et al.  Iterative detection of MIMO signals with linear detectors , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[42]  Stephan ten Brink,et al.  Achieving near-capacity on a multiple-antenna channel , 2003, IEEE Trans. Commun..

[43]  Babak Hassibi,et al.  Statistical Pruning for Near-Maximum Likelihood Decoding , 2007, IEEE Transactions on Signal Processing.

[44]  Zhi-Quan Luo,et al.  Quasi-maximum-likelihood multiuser detection using semi-definite relaxation with application to synchronous CDMA , 2002, IEEE Trans. Signal Process..

[45]  Y. Nesterov Semidefinite relaxation and nonconvex quadratic optimization , 1998 .

[46]  Joachim Hagenauer,et al.  Iterative detection of MIMO transmission using a list-sequential (LISS) detector , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[47]  Giuseppe Caire,et al.  A unified framework for tree search decoding: rediscovering the sequential decoder , 2005, IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, 2005..

[48]  Robert J. Vanderbei,et al.  An Interior-Point Method for Semidefinite Programming , 1996, SIAM J. Optim..

[49]  M. V. Wilkes,et al.  The Art of Computer Programming, Volume 3, Sorting and Searching , 1974 .

[50]  Thomas H. Cormen,et al.  Introduction to algorithms [2nd ed.] , 2001 .

[51]  Björn E. Ottersten,et al.  The Diversity Order of the Semidefinite Relaxation Detector , 2006, IEEE Transactions on Information Theory.

[52]  Ami Wiesel,et al.  Semidefinite relaxation for detection of 16-QAM signaling in MIMO channels , 2005, IEEE Signal Processing Letters.

[53]  Evaggelos Geraniotis,et al.  Iterative multiuser detection for coded CDMA signals in AWGN and fading channels , 2000, IEEE Journal on Selected Areas in Communications.