Multi-stage Antenna Selection for Adaptive Beamforming in MIMO Arrays

TL;DR

This paper introduces a multi-stage antenna selection approach for MIMO arrays that reduces hardware and computational costs while maintaining high output SINR performance through various selection strategies.

Contribution

It proposes four novel antenna selection strategies for reconfigurable MIMO arrays, optimizing the trade-off between performance and cost with a unified determinant maximization framework.

Findings

Joint transmit-receive selection yields the best SINR performance.

All proposed methods effectively balance performance and hardware cost.

Theoretical results are validated through numerical simulations.

Abstract

Increasing the number of transmit and receive elements in multiple-input-multiple-output (MIMO) antenna arrays imposes a substantial increase in hardware and computational costs. We mitigate this problem by employing a reconfigurable MIMO array where large transmit and receive arrays are multiplexed in a smaller set of k baseband signals. We consider four stages for the MIMO array configuration and propose four different selection strategies to offer dimensionality reduction in post-processing and achieve hardware cost reduction in digital signal processing (DSP) and radio-frequency (RF) stages. We define the problem as a determinant maximization and develop a unified formulation to decouple the joint problem and select antennas/elements in various stages in one integrated problem. We then analyze the performance of the proposed selection approaches and prove that, in terms of the output SINR, a joint transmit-receive selection method performs best followed by matched-filter, hybrid and factored selection methods. The theoretical results are validated numerically, demonstrating that all methods allow an excellent trade-off between performance and cost.