Multiuser Detection
Rank-Two Relaxation Heuristics for MAX-CUT and Other Binary Quadratic Programs
SIAM Journal on Optimization
Multiuser detection of synchronous code-division multiple-accesssignals by perfect sampling
IEEE Transactions on Signal Processing
A near-optimal multiuser detector for DS-CDMA systems using semidefinite programming relaxation
IEEE Transactions on Signal Processing
Decision feedback multiuser detection: a systematic approach
IEEE Transactions on Information Theory
Linear multiuser detectors for synchronous code-division multiple-access channels
IEEE Transactions on Information Theory
Group detection for synchronous Gaussian code-division multiple-access channels
IEEE Transactions on Information Theory
The application of semidefinite programming for detection in CDMA
IEEE Journal on Selected Areas in Communications
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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Based on the binary quadratic programming model of the code division multiple access maximum likelihood multiuser detection problem, a detection strategy by the continuous relaxation method is presented. The proposed method relaxes the binary quadratic programming as a nonlinear programming, which is a quadratic objective function with simple quadratic constraints. A feasible direction method is used to solve the nonlinear programming. Based on the KKT solution of the nonlinear programming, a near optimal solution is obtained for the multiuser detection problem. Simulation results show that the bit error rate performances of a detection strategy based on the continuous relaxation method is low. Furthermore, average CPU time of continuous relaxation method is much lower than that of the semidefinite programming relaxation method, especially for the large-scale detection problems. This approach provides good approximations to the optimal maximum likelihood performance.