# 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.

## Key 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.

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Source: https://tomesphere.com/paper/1904.08614