Lattice basis reduction: improved practical algorithms and solving subset sum problems
Mathematical Programming: Series A and B
A Note on the Calculation of Step-Lengths in Interior-Point Methods for Semidefinite Programming
Computational Optimization and Applications
Rank-Two Relaxation Heuristics for MAX-CUT and Other Binary Quadratic Programs
SIAM Journal on Optimization
Solving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization
SIAM Journal on Optimization
Space Time Coding for Broadband Wireless Communications
Space Time Coding for Broadband Wireless Communications
Approximation Bounds for Quadratic Optimization with Homogeneous Quadratic Constraints
SIAM Journal on Optimization
Probabilistic Analysis of Semidefinite Relaxation for Binary Quadratic Minimization
SIAM Journal on Optimization
Semidefinite relaxation based multiuser detection for M-ary PSK multiuser systems
IEEE Transactions on Signal Processing - Part I
IEEE Transactions on Signal Processing
Semidefinite programming relaxation approach for multiuser detection of QAM signals
IEEE Transactions on Wireless Communications
A universal lattice code decoder for fading channels
IEEE Transactions on Information Theory
Closest point search in lattices
IEEE Transactions on Information Theory
On maximum-likelihood detection and the search for the closest lattice point
IEEE Transactions on Information Theory
A unified framework for tree search decoding: rediscovering the sequential decoder
IEEE Transactions on Information Theory
The application of semidefinite programming for detection in CDMA
IEEE Journal on Selected Areas in Communications
Probabilistic Analysis of Semidefinite Relaxation for Binary Quadratic Minimization
SIAM Journal on Optimization
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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 polynomialworst-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.