Antenna selection is a low-complexity low-cost alternative for implementing MIMO systems. It was proposed to trade off system hardware cost and system performance by keeping the same number of antennas and using a fewer RF chains. In this paper, we consider the joint transmit and receive antenna selection capacity-maximization problem in MIMO systems. The optimal joint transmit and receive antenna selection could be achieved by exhaustively searching all the transmit and receive antenna subsets. However, its applicability is limited due to the high computational complexity. The existing suboptimal algorithms decouple the selection into transmit antenna selection and receive antenna selection, and exhibit a performance loss compared to the optimal method. We propose JTRAS, a greedy algorithm to jointly select the transmit and receive antennas to maximize the channel capacity. We will demonstrate that JTRAS performs very close to the optimal exhaustive search method and outperforms the existing suboptimal algorithms. We will also investigate the computational complexity of JTRAS and show it is much lower than that of the optimal solution. Capacity performance of our proposed JTRAS algorithm will be provided by simulation.
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