Multiple-input multiple-output (MIMO) systems with antenna selection are practical in that they can alleviate the computational complexity at the receiver and achieve good reception performance. Channel correlation, not just carrier-to-noise ratio (CNR), has a great impact on reception performance in MIMO channels. We propose a practical receive antenna subset selection algorithm with reduced complexity that uses the condition number of the partial channel matrix and a predetermined CNR threshold. This paper describes the algorithm and its performance evaluation by both computer simulation and indoor experiments using a prototype receiver and received signals obtained in an actual mobile outdoor experiment. The results confirm that our proposed method provides good bit error rate performance by setting the CNR threshold properly.

In this letter, we propose two different joint transmit and receive antenna subset selection schemes for multiple-input multiple-output (MIMO) systems on the basis of capacity maximization criterion. We assume that perfect channel state information (CSI) is known at the receiver but unknown to the transmitter. As the selection signaling is perfectly fed back to the transmitter, we propose a flexible two-step selection algorithm (TSSA) in practical MIMO channel scenarios. Computer simulations show that TSSA can maximize the capacity at low computation cost in most scenarios. It performs well in terms of capacity, computational complexity and flexibility. Furthermore, we propose a simplified algorithm based on the correlation matrix when the channel correlation information (CCI) is known to the transmitter. Simulation results show that the proposed correlation matrix based selection algorithm is only slightly inferior to an optimal selection algorithm.

Aiming to optimally transmit space-time block codes (STBCs) over distributed antennas (DAs), this paper examines downlink transmit antenna subset selection with power allocation for STBCs in non-ergodic Rayleigh fading channels with receive antenna correlations. Closed-form outage probability is first derived, which is a function of data rate, rate of STBCs, transmit power, large-scale fading (shadowing and path loss), power allocation weights to each DA and receive antenna correlation. However, achieving the optimal power allocation solution is computationally demanding and the use of sub-optimal techniques is necessitated. Assuming feedback of eigenvalues of transmit and receive antenna correlation matrix at the transmitter and accurate channel state information (CSI) at the receiver, an antenna subset selection with sub-optimal power allocation scheme is proposed, whose performance approaches optimal. The effectiveness of this sub-optimal method has been demonstrated by numerical results.