Massive MIMO performance with imperfect channel reciprocity and channel estimation error

TL;DR

This paper analyzes how RF mismatches and channel estimation errors affect the performance of linear precoding in TDD massive MIMO systems, providing analytical expressions and practical design insights.

Contribution

It models RF mismatches with a truncated Gaussian, derives closed-form SINR expressions, and investigates asymptotic performance for practical system design.

Findings

RF mismatches significantly degrade precoding performance.

Analytical SINR expressions match simulation results.

Guidelines for selecting effective precoding schemes are provided.

Abstract

Channel reciprocity in time-division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems can be exploited to reduce the overhead required for the acquisition of channel state information (CSI). However, perfect reciprocity is unrealistic in practical systems due to random radio-frequency (RF) circuit mismatches in uplink and downlink channels. This can result in a significant degradation in the performance of linear precoding schemes, which are sensitive to the accuracy of the CSI. In this paper, we model and analyse the impact of RF mismatches on the performance of linear precoding in a TDD multi-user massive MIMO system, by taking the channel estimation error into considerations. We use the truncated Gaussian distribution to model the RF mismatch, and derive closed-form expressions of the output signal-to-interference-plus-noise ratio for maximum ratio transmission and zero forcing precoders. We further investigate the asymptotic performance of the derived expressions, to provide valuable insights into the practical system designs, including useful guidelines for the selection of the effective precoding schemes. Simulation results are presented to demonstrate the validity and accuracy of the proposed analytical results.