Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges

TL;DR

This paper reviews recent advances in fronthaul-constrained cloud radio access networks (C-RANs), focusing on system architectures, techniques to mitigate fronthaul limitations, and open challenges for 5G wireless systems.

Contribution

It provides a comprehensive survey of system architectures, key techniques, and open issues related to fronthaul constraints in C-RANs for 5G networks.

Findings

Techniques like compression and quantization help mitigate fronthaul limitations.

Large-scale processing and clustering improve spectral and energy efficiency.

Open issues include SDN, NFV, and partial centralization challenges.

Abstract

As a promising paradigm for fifth generation (5G) wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between a baseband unit (BBU) and a remote radio head (RRH), requires high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained C-RANs, including system architectures and key techniques. In particular, key techniques for alleviating the impact of constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified.