Heterogeneous cloud radio access networks: a new perspective for enhancing spectral and energy efficiencies

TLDR

H‑CRANs are proposed to mitigate severe inter‑tier interference and enhance cooperative gains in HetNets by integrating cloud computing. The article surveys H‑CRAN research, covering system architectures, spectral and energy efficiency, and key techniques such as cloud‑based coordinated multipoint, large‑scale MIMO, cooperative radio resource management, and self‑organizing networks, while highlighting challenges like stochastic‑geometry performance, fronthaul constraints, and standardization.

Abstract

To mitigate the severe inter-tier interference and enhance the limited cooperative gains resulting from the constrained and non-ideal transmissions between adjacent base stations in HetNets, H-CRANs are proposed as cost-efficient potential solutions through incorporating cloud computing into HetNets. In this article, state-of-the-art research achievements and challenges of H-CRANs are surveyed. In particular, we discuss issues of system architectures, spectral and energy efficiency performance, and promising key techniques. A great emphasis is given toward promising key techniques in HCRANs to improve both spectral and energy efficiencies, including cloud-computing-based coordinated multipoint transmission and reception, large-scale cooperative multiple antenna, cloud-computing-based cooperative radio resource management, and cloud-computingbased self-organizing networks in cloud converging scenarios. The major challenges and open issues in terms of theoretical performance with stochastic geometry, fronthaul-constrained resource allocation, and standard development that may block the promotion of H-CRANs are discussed as well.