In this paper we develop two quasi-maximum likelihood (ML) channel detectors for multiuser detection: semidefinite relaxation (SDR) detector and phase-shift-keying (PSK) detector. These detectors can deliver near-ML bit error rate (BER) performance with a polynomial worst-case complexity. The SDR detector for binary-phase-shift-keying (BPSK) constellation is based on a convex SDR, whereas the PSK detector for M-PSK constellations is based on a nonconvex low-rank SDR. The SDR detector is implemented using a dual-scaling interior-point method, while the PSK detector is based on a coordinate descent strategy on a feasible region homotopy. We use dynamic dimension reduction and warm start techniques to achieve signal-to-noise ratio (SNR)-sensitive improvements for both detectors. Numerical simulations of BER performance and running time indicate the effectiveness of the two quasi-ML detectors when compared to the conventional sphere decoder and its variants.
Bibliographical noteFunding Information:
Manuscript received March 16, 2007; accepted April 28, 2009. First published July 14, 2009; current version published November 18, 2009. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Xiaodong Cai. This research is supported in part by the National Science Foundation, Grant DMS-0610037. A preliminary version of this paper was published in the Proceedings of International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hong Kong, 2003, vol. 6, pp. VI 561–VI 564, and the Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), Philadelphia, PA, 2005, vol. 3, pp. III 433–III 436.
Copyright 2009 Elsevier B.V., All rights reserved.
- Dimension reduction
- MIMO systems
- Maximum-likelihood detection
- Semidefinite relaxation (SDR)