System Architecture and Key Technologies for 5G Heterogeneous Cloud Radio Access Networks

TL;DR

This paper surveys the system architecture and key technologies of 5G Heterogeneous Cloud Radio Access Networks (H-CRANs), highlighting their potential for significant spectral, energy efficiency, and throughput improvements over 4G.

Contribution

It introduces the concept of Node C for centralized processing, proposes a software-defined H-CRAN architecture, and summarizes advancements in cooperative signal processing, resource management, and virtualization.

Findings

H-CRAN can significantly enhance spectral and energy efficiency.

Node C enables centralized control of remote radio heads.

Key technologies face challenges like fronthaul constraints and energy harvesting.

Abstract

Compared with the fourth generation (4G) cellular systems, the fifth generation wireless communication systems (5G) are anticipated to provide spectral and energy efficiency growth by a factor of at least 10, and the area throughput growth by a factor of at least 25. To achieve these goals, a heterogeneous cloud radio access network (H-CRAN) is presented in this article as the advanced wireless access network paradigm, where cloud computing is used to fulfill the centralized large-scale cooperative processing for suppressing co-channel interferences. The state-of-the-art research achievements in aspects of system architecture and key technologies for H-CRANs are surveyed. Particularly, Node C as a new communication entity is defined to converge the existing ancestral base stations and act as the base band unit (BBU) pool to manage all accessed remote radio heads (RRHs), and the software-defined H-CRAN system architecture is presented to be compatible with software-defined networks (SDN). The principles, performance gains and open issues of key technologies including adaptive large-scale cooperative spatial signal processing, cooperative radio resource management, network function virtualization, and self-organization are summarized. The major challenges in terms of fronthaul constrained resource allocation optimization and energy harvesting that may affect the promotion of H-CRANs are discussed as well.