Over-the-Air Fronthaul Signaling for Uplink Cell-Free Massive MIMO Systems

TL;DR

This paper introduces an over-the-air computation framework for uplink cell-free massive MIMO systems that reduces fronthaul overhead by computing sufficient statistics locally at access points and aggregating them efficiently at the CPU.

Contribution

It proposes a novel OTA computation method for cell-free MIMO, enabling scalable and resource-efficient data processing compared to traditional wired fronthaul systems.

Findings

OTA framework reduces fronthaul overhead

Closed-form MSE expressions for estimators

Improved SER and BER performance benchmarks

Abstract

We propose a novel resource-efficient over-the-air(OTA) computation framework to address the huge fronthaul computational and control overhead requirements in cell-free massive multiple-input multiple-output (MIMO) networks. We show that the global sufficient statistics to decode the data symbols can be computed OTA using the locally available information at the access points (APs). We provide the essential signal processing aspects at the APs and the central processing unit (CPU) to facilitate the OTA computation of sufficient statistics. The proposed framework scales effectively with an increase in the number of APs. We also make a comprehensive study of the benefits of an OTA framework compared to a conventional digital fronthaul in terms of the overhead associated in transferring the sufficient statistics from the APs to the CPU. To evaluate the performance of the OTA framework, we give closed-form expressions for the mean-square error (MSE)of the estimators of sufficient statistics and the overall data estimator. Furthermore, we assess the symbol error rate (SER)and bit error rate (BER) of the user equipment (UEs) data to demonstrate the efficacy of our method, and benchmark them against the state-of-the-art wired fronthaul networks.