Cooperative access networks: Optimum fronthaul quantization in distributed Massive MIMO and cloud RAN

TL;DR

This paper analyzes the impact of fronthaul quantization in cooperative radio access networks like distributed Massive MIMO and Cloud RAN, proposing a new MMSE estimation approach to optimize uplink performance.

Contribution

It introduces a novel MMSE estimation method based on Bussgang decomposition for analyzing fronthaul quantization effects in cooperative networks.

Findings

Quantization significantly affects uplink performance.

The proposed MMSE estimator improves signal recovery.

Insights into fronthaul capacity requirements for optimal performance.

Abstract

We consider cooperative radio access network architectures, especially distributed massive MIMO and Cloud RAN, considering their similarities and differences. We address in particular the major challenge posed to both by the implementation of a high capacity fronthaul network to link the distributed access points to the central processing unit, and consider the effect on uplink performance of quantization of received signals in order to limit fronthaul load. We use the Bussgang decomposition along with a new approach to MMSE estimation of both channel and data to provide the basis of our analysis.