Optimal Fronthaul Compression for Synchronization in the Uplink of Cloud Radio Access Networks

TL;DR

This paper addresses fronthaul compression in cloud radio access networks, focusing on improving time and phase synchronization at the central unit by designing compression strategies that consider synchronization errors.

Contribution

It introduces a novel compression design that enhances synchronization performance without assuming perfect initial synchronization, using information-theoretic and estimation bounds.

Findings

Proposed algorithm outperforms conventional solutions

Enhances synchronization accuracy at the CU

Analyzes impact of synchronization errors on link performance

Abstract

A key problem in the design of cloud radio access networks (CRANs) is that of devising effective baseband compression strategies for transmission on the fronthaul links connecting a remote radio head (RRH) to the managing central unit (CU). Most theoretical works on the subject implicitly assume that the RRHs, and hence the CU, are able to perfectly recover time synchronization from the baseband signals received in the uplink, and focus on the compression of the data fields. This paper instead dose not assume a priori synchronization of RRHs and CU, and considers the problem of fronthaul compression design at the RRHs with the aim of enhancing the performance of time and phase synchronization at the CU. The problem is tackled by analyzing the impact of the synchronization error on the performance of the link and by adopting information and estimationtheoretic performance metrics such as the rate-distortion function and the Cramer-Rao bound (CRB). The proposed algorithm is based on the Charnes-Cooper transformation and on the Difference of Convex (DC) approach, and is shown via numerical results to outperform conventional solutions.