Traffic-Aware Dynamic Functional Split for 5G Cloud Radio Access Networks

TL;DR

This paper proposes a traffic-aware dynamic functional split method for 5G C-RAN that optimizes midhaul bandwidth usage and increases centralization by adaptively selecting split options based on traffic conditions.

Contribution

It introduces a novel optimization approach for dynamic split selection in 5G C-RAN, improving centralization under bandwidth constraints.

Findings

Achieves 90% centralization with dynamic split selection.

Outperforms static split configurations in bandwidth efficiency.

Effectively adapts to traffic heterogeneity in 5G networks.

Abstract

The recent adaption of virtualization technologies in the next generation mobile network enables 5G base station to be segregated into a Radio Unit (RU), a Distributed Unit (DU), and a Central Unit (CU) to support Cloud based Radio Access Networks (C-RAN). RU and DU are connected through a fronthaul link. In contrast, CU and DU are connected through a midhaul link. Although virtualization of CU gives benefits of centralization to the operators, there are other issues to be solved such as optimization of midhaul bandwidth and computing resources at edge cloud and central cloud where the DUs and CUs are deployed, respectively. In this paper, we propose a dynamic functional split selection for the DUs in 5G C-RAN by adopting to traffic heterogeneity where the midhaul bandwidth is limited. We propose an optimization problem that maximizes the centralization of the C-RAN system by operating more number of DUs on split Option-7 by changing the channel bandwidth of the DUs. The dynamic selection of split options among each CU-DU pair gives 90% centralization over the static functional split for a given midhaul bandwidth.