Near optimum maximum likelihood detector for structured communication problems

Maximum likelihood (ML) detector is the optimal method for detecting symbols transmitted through wireless communication channels, but it has a higher computational complexity. Generalized minimum mean squared error (GMMSE) detector has a bit error rate (BER) performance that is almost the same as minimum mean squared error (MMSE) detector and less performance than ML detector. In this paper, the bit error rate (BER) performance of GMMSE detector is improved to be near optimum maximum likelihood (NML) detector using the local search method. The computational complexity of this detector is kept to be almost the same as that of GMMSE detector.