Joint AGC and Receiver Design for Large-Scale MU-MIMO Systems with Coarsely Quantized Signals and C-RANs

TL;DR

This paper introduces a joint optimization approach for AGC and low-resolution aware MMSE filtering in large-scale MU-MIMO systems with coarse quantization, improving error rates and achievable sum rates in C-RANs.

Contribution

It proposes a novel joint AGC and LRA-MMSE receiver design tailored for coarsely quantized signals in large-scale MU-MIMO C-RANs, enhancing performance over existing methods.

Findings

Improved error rate performance compared to existing techniques.

Higher achievable sum rates demonstrated through simulations.

Effective interference cancellation with the proposed joint design.

Abstract

In this work, we propose the joint optimization of the automatic gain control (AGC), which works in the remote radio heads (RHHs), and a low-resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works on the baseband unit (BBU) pool, for large-scale multi-user multiple-input multiple-output (MU-MIMO) systems with coarsely quantized signals in cloud radio access networks. We develop successive interference cancellation receivers based on the proposed joint AGC and LRA-MMSE (AGC-LRA-MMSE) approach. An analysis of the achievable sum rates is also carried out. Simulations show that the proposed design has better error rates and higher achievable rates than existing techniques.