Simplified maximum-likelihood precoder selection for limited feedback spatial multiplexing systems

In this paper, we consider a precoder selection criterion for the maximum-likelihood (ML) detector in limited feedback spatial multiplexing systems. When the ML detector is employed, the exhaustive search for the optimal precoder selection requires very high computational complexity. As a good compromise, we propose a simple precoder selection scheme for the ML detector. It reduces the computational complexity significantly with negligible performance degradation. For the wideband OFDM systems, we extend the precoder selection by introducing a clustering concept in selecting the optimal precoder. Numerical results show that the proposed scheme achieves both the diversity order of the ML detector and the performance enhancement of the limited feedback spatial multiplexing. Moreover, the proposed precoder selection algorithm based on the clustering approach provides enhanced performance compared with conventional interpolation and clustering algorithms.