Efficient implementation of quasi- maximum-likelihood detection based on semidefinite relaxation

IEEE Transactions on Signal Processing

Volumn 57, Issue 12, 2009, Pages 4811-4822

  Kisialiou, Mikalai ^a   Luo, Xiaodong ^c   Luo, Zhi Quan ^b  

^a INTEL CORPORATION   (United States)

^b University of Minnesota   (United States)

^c Research Group   (United States)

Author keywords

Dimension reduction; Duality; Maximum likelihood detection; MIMO systems; Semidefinite relaxation (SDR)

Indexed keywords

BER PERFORMANCE; BIT ERROR RATE PERFORMANCE; COORDINATE DESCENT; DIMENSION REDUCTION; DUALITY; EFFICIENT IMPLEMENTATION; FEASIBLE REGIONS; HOMOTOPIES; INTERIOR-POINT METHOD; MAXIMUM- LIKELIHOOD DETECTION; ML DETECTORS; NONCONVEX; NUMERICAL SIMULATION; RUNNING TIME; SEMIDEFINITE RELAXATION; SPHERE DECODERS; WARM START; WORST-CASE COMPLEXITY;

BIT ERROR RATE; COMPUTER SIMULATION; DECODING; INFORMATION RETRIEVAL; MAXIMUM LIKELIHOOD; MIMO SYSTEMS; MODULATION; MULTIPLEXING; MULTIUSER DETECTION; PHASE SHIFT; PHASE SHIFT KEYING; SIGNAL TO NOISE RATIO;

DETECTORS;

EID: 70450277222     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2009.2027741     Document Type: Article

References (30)

1. E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, "Closest point search in lattices," IEEE Trans. Inf. Theory, vol.48, no.8, pp. 2201-2214, Aug. 2002.
2. S. J. Benson, Y.Ye, and X. Zhang, "Solving large-scale sparse semidefinite programs for combinatorial optimization," SIAM J. Optimiz., vol.10, no.2, pp. 443-461, 2000.
3. S. J. Benson and Y. Ye, DSDP5: Software for Semidefinite Programming, Mathematics and Computer Science Division, Argonne National Laboratory, ANL/MCS-P1289-0905, 2005.
4. S. Burer, R. D. C. Monteiro, and Y. Zhang, "Rank-two relaxation heuristics for Max-Cut and other binary quadratic programs," SIAM J. Optimiz., vol.12, no.2, pp. 503-521, 2001.
5. T. Cui, T. Ho, and C. Tellambura, "Polynomial moment relaxation for MIMO detection," in Proc. IEEE Int. Conf. Commun., 2006, vol.7, pp. 3129-3134.
6. M. O. Damen, H. El Gamal, and G. Caire, "On maximum-likelihood detection and the search for the closest lattice point," IEEE Trans. Inf. Theory, vol.49, no.10, pp. 2389-2402, 2003.
7. U. Fincke and M. Pohst, "Improved methods for calculating vectors of short length in a lattice, including a complexity analysis," Math. Comput., vol.44, pp. 463-471, 1985.
8. G. B. Giannakis, Z. Liu, X. Ma, and S. Zhou, Space-time coding for broadband wireless communications, 1st ed. New York:Wiley-Interscience, 2003.
9. J. Jalden, "Detection for multiple input multiple output channels," Ph.D. dissertation, KTH, School of Electrical Engineering, Stockholm, Sweden, 2006.
10. J. Jalden, C. Martin, and B. Ottersten, "Semidefinite programming for detection in linear systems-optimality conditions and space-time decoding," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), 2003, vol.4, pp. IV-9-IV-12.
11. J. Jalden and B. Ottersten, "An exponential lower bound on the expected complexity of sphere decoding," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), 2004, vol.4, pp. IV-393-IV-396.
12. M. Kisialiou and Z.-Q. Luo, "Probabilistic analysis of semidefinite relaxation for binary quadratic minimization," SIAM J. Optimiz., submitted for publication.
13. M. Kisialiou and Z.-Q. Luo, "Performance analysis of quasi-maximum- likelihood detector based on semi-definite programming," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), 2005, vol.3, pp. III 433-III 436.
14. Z.-Q. Luo, X. Luo, and M. Kisialiou, "An efficient quasi-maximum- likelihood decoder for PSK signals," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), 2003, vol.6, pp. VI 561-VI 564.
15. Z.-Q. Luo, N. D. Sidiropoulos, P. Tseng, and S. Zhang, "Approximation bounds for quadratic optimization with homogeneous quadratic constraints," SIAM J. Optimiz., vol.18, no.1, pp. 1-28, 2007.
16. W. K. Ma, P. C. Ching, and Z. Ding, "Semidefinite relaxation based multiuser detection for M-ary PSK multiuser systems," IEEE Trans. Signal Process., vol.52, no.10, pp. 2862-2872, 2004.
17. W. K. Ma, T. N. Davidson, K. M. Wong, Z.-Q. Luo, and P. C. Ching, "Quasi-maximum-likelihood multiuser detection using semi-definite relaxation," IEEE Trans. Signal Process., vol.50, no.4, pp. 912-922, Apr. 2002.
18. Z. Mao, X.Wang, and X.Wang, "Semidefinite programming relaxation approach for multiuser detection of QAM signals," IEEE Trans. Wireless Commun., vol.6, no.12, pp. 4275-4279, 2007. (Pubitemid 350249463)
19. A. Mobasher,M. Taherzadeh, R. Sotirov, and A. K. Khandani, "A near maximum likelihood decoding algorithm for MIMO systems based on semi-definite programming," in Proc. Int. Symp. Inf. Theory, 2005, pp. 1686-1690.
20. A. D. Murugan, H. El Gamal, M. O. Damen, and G. Caire, "A unified framework for tree search decoding: Rediscovering the sequential decoder," IEEE Trans. Inf. Theory, vol.52, no.3, pp. 933-953, 2006.
21. M. Nekuii, M. Kisialiou, T. N. Davidson, and Z.-Q. Luo, "Efficient soft demodulation of MIMO QPSK via semidefinite relaxation," IEEE Trans. Signal Process., 2008, submitted for publication.
22. C. P. Schnorr and M. Euchner, "Lattice basis reduction: Improved practical algorithms and solving subset sum problems," Math. Programm., vol.66, pp. 181-191, 1994.
23. N. D. Sidiropoulos and Z.-Q. Luo, "A semidefinite relaxation approach toMIMO detection for higher-orderQAMconstellations," IEEE Signal Process. Lett., vol.13, no.9, pp. 525-528, 2006.
24. J. F. Sturm, "Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones," Optimiz. Methods Softw., vol.11-12, pp. 625-653, 1999.
25. P. H. Tan and L. K. Rasmussen, "The application of semidefinite programming for detection in CDMA," IEEE J. Sel. Areas Commun., vol.19, no.8, pp. 1442-1449, 2001.
26. K. C. Toh, "A note on the calculation of step-lengths in interior-point methods for semidefinite programming," Comput. Optimiz. Appl., vol.21, pp. 301-310, 1999.
27. E. Viterbo and J. Bouros, "A universal lattice code decoder for fading channels," IEEE Trans. Inf. Theory, vol.45, no.5, pp. 1639-1642, 1999.
28. A.Wiesel, Y. Eldar, and S. Shamai, "Semidefinite relaxation for detection of 16-QAM signaling in MIMO channels," IEEE Signal Process. Lett., vol.12, no.9, pp. 653-656, 2005.
29. Y. Yang, C. Zhao, P. Zhou, and W. Xu, "MIMO detection of 16-QAM signaling based on semidefinite relaxation," IEEE Signal Process. Lett., vol.14, no.11, pp. 797-800, 2007.
30. M. Kisialiou, X. Luo, and Z.-Q. Luo, Semidefinite Relaxation Codes for the Discrete Integer Least Squares Problem. [Online]. Available: http://www.ece.umn.edu/users/luozq/software/sw-about.html