Network Calculus Based Delay Analysis for Mixed Fronthaul and Backhaul 5G Networks

Abstract

Cloud Radio Access Network (C-RAN) is a crucial component in 5G network deployments. The C-RAN technology will reduce operating costs, improve energy efficiency, and support enhanced capacity and coverage by taking advantage of centralized processing. However, C-RAN requires strict latency bounds on the fronthaul network that connects the distributed radio units and the central processing units. Instead of deploying dedicated fronthaul transport networks, the reuse of existing backhaul transport networks to carry fronthaul data needs to be leveraged. In this paper, we study the end-to-end delay bounds for a mixed fronthaul and backhaul 5G network. Deterministic network calculus is used to derive worst-case delay bounds in a mixed transport network, and this is verified using a C-RAN experimental testbed with real traffic characteristics. The impact on end-to-end delay due to the effect of multiplexing fronthaul and diurnal backhaul traffic in business and residential regions is studied analytically. We also propose a framework to determine the choice of enabling the appropriate fronthaul split at the distributed radio units and the central processing units to meet the latency requirements. The proposed network calculus based framework can be utilized by network engineers while designing the future 5G transport network deployments.