Statistical-CSI-Based Antenna Selection and Precoding in Uplink MIMO

TL;DR

This paper introduces a novel antenna selection and precoding scheme for uplink MIMO systems that relies solely on long-term CSI statistics, reducing signaling overhead while maximizing long-term throughput.

Contribution

It proposes a joint antenna selection and precoding method based on statistical CSI, with a closed-form throughput expression and an iterative optimization algorithm.

Findings

Outperforms baseline schemes in numerical simulations.

Reduces signaling overhead by using long-term CSI.

Achieves higher long-term throughput.

Abstract

Classical antenna selection schemes require instantaneous channel state information (CSI). This leads to high signaling overhead in the system. This work proposes a novel joint receive antenna selection and precoding scheme for multiuser multiple-input multiple-output uplink transmission that relies only on the long-term statistics of the CSI. The proposed scheme designs the switching network and the uplink precoders, such that the expected throughput of the system in the long term is maximized. Invoking results from the random matrix theory, we derive a closed-form expression for the expected throughput of the system. We then develop a tractable iterative algorithm to tackle the throughput maximization problem, capitalizing on the alternating optimization and majorization-maximization (MM) techniques. Numerical results substantiate the efficiency of the proposed approach and its superior performance as compared with the baseline.