IEEE Transactions on Communications
Efficient implementation of quasi-maximum-likelihood detection based on semidefinite relaxation
IEEE Transactions on Signal Processing
Robust cognitive beamforming with bounded channel uncertainties
IEEE Transactions on Signal Processing
PIC-based iterative SDR detector for OFDM systems in doubly-selective fading channels
IEEE Transactions on Wireless Communications
Probabilistic analysis of the semidefinite relaxation detector in digital communications
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Matrix-lifting semi-definite programming for detection in multiple antenna systems
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A fast constrained sphere decoder for ill conditioned communication systems
IEEE Communications Letters
Probabilistic Analysis of Semidefinite Relaxation for Binary Quadratic Minimization
SIAM Journal on Optimization
Wireless Personal Communications: An International Journal
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Because of the powerful symbol error performance of multiuser maximum-likelihood (ML) detection, recently, there has been much interest in seeking effective ways of approximating multiuser ML detection (MLD) with affordable computational costs. It has been illustrated that for the synchronous code division multiple access (CDMA) scenario, the so-called semidefinite relaxation (SDR) algorithm can accurately and efficiently approximate multiuser MLD. This SDR-MLD algorithm, however, can only handle binary and quadratic phase shift keying (PSK) symbol constellations. In this sequel, we propose an extended SDR algorithm for MLD with M-ary PSK (MPSK) constellations. For the synchronous CDMA scenario, the proposed SDR algorithm provides an attractive polynomial-time complexity order of K3.5, where K is the number of users. Simulation results indicate that the proposed detector provides improved symbol error performance compared with several commonly used multiuser detectors.