Statistical antenna selection for spatial multiplexing systems

Spatial multiplexing is a signaling strategy for achieving high spectral efficiencies in communication links that employ multiple transmit and multiple receive antennas. In such systems, it is desirable to use only a subset of the available transmit and/or receive antennas to reduce cost and complexity. We address the problem of optimal antenna subset selection in spatial multiplexing systems when only the second-order statistics of the channel are available. We derive selection criteria for both the maximum likelihood and zero forcing receivers, motivated by minimizing the average symbol error rate. We characterize the antenna selection gain and show that both coding gain and diversity gain is possible. We then use Monte Carlo simulations to validate our analysis.