User relay‐aided energy‐efficient resource allocation in heterogeneous cloud radio access network

Abstract

In this article, we consider a user relay-aided resource allocation problem for femtocell access points (FAPs) and macrocells to improve energy efficiency in heterogeneous cloud radio access networks. The formulated optimization problem is NP-hard and mixed-integer non-linear programming due to the incredibly complex relation between different optimization variables and their impacts on each other. To solve this non-convex and NP-hard optimization problem in an effective and distributed method, we propose an efficient three-step iterative algorithm. The solution approaches are derived from successive convex approximation and complementary geometric programming by considering maximum power, front-haul link and baseband unit (BBU) capacity, Jain's fairness index, and quality of service constraints of macro and femtocell users. The simulation results depict that the proposed algorithm can effectively decrease the energy consumption of BBUs by switching off under-utilized BBUs and offloading the traffic from remote radio heads and macro-cell to FAPs.