Study of Joint Automatic Gain Control and MMSE Receiver Design Techniques for Quantized Multiuser Multiple-Antenna Systems

TL;DR

This paper introduces a joint optimization of AGC and MMSE receiver design tailored for quantized MU-MIMO systems, improving capacity and performance with low-resolution signals through simulation comparisons.

Contribution

It proposes a novel joint AGC and MMSE receiver optimization specifically for quantized MU-MIMO systems, including capacity bounds and performance evaluation.

Findings

The LRA-MMSE receiver outperforms conventional MMSE and ZF receivers with low-resolution quantization.

The proposed methods improve system capacity under coarse quantization.

Simulation results validate the effectiveness of the joint optimization approach.

Abstract

This paper presents the development of a joint optimization of an automatic gain control (AGC) algorithm and a linear \textit{minimum mean square error} (MMSE) receiver for multi-user multiple input multiple output (MU-MIMO) systems with coarsely quantized signals. The optimization of the AGC is based on the minimization of the \textit{mean square error} (MSE) and the proposed receive filter takes into account the presence of the AGC and the effects due to quantization. Moreover, we provide a lower bound on the capacity of the MU-MIMO system by deriving an expression for the achievable rate. The performance of the proposed Low-Resolution Aware MMSE (LRA-MMSE) receiver and AGC algorithm is evaluated by simulations, and compared with the conventional MMSE receive filter and Zero-Forcing (ZF) receiver using quantization resolution of 2, 3, 4 and 5 bits.