Joint Computing and Radio Resource Allocation in Cloud Radio Access Networks

This paper considers the problem of joint radio and computing resource allocation in Cloud Radio Access Network (C-RAN) architecture. We develop a resource allocation scheme to maximize weighted sum-rate of the system, while minimizing total power consumption. For power consumption, we consider both static and dynamic power consumption in Remote Radio Heads (RRHs), fronthaul links, and Base Band processing Units (BBUs). Our model considers quality of service requirements, fronthaul capacity, maximum transmission power, and computing capacity constraints in a comprehensive formulation. The joint resource allocation problem is non-convex, which is shown to be NP-hard, and thus we apply a number of techniques to convexify the problem. Then, using the Karush-Kuhn-Tucker (KKT) conditions, we show that the problem can be decomposed into two sub-problems that can be efficiently solved using an iterative Quadratically Constrained Quadratic Program (QCQP) and a bin packing algorithm, respectively. The performance of the proposed scheme is evaluated through simulation studies, which shows the proposed scheme outperforms the existing approaches in BBU minimization, total power consumption, and system utility which is defined as the weighted sum-rate minus power consumption.