Energy-efficient resource allocation in C-RAN with fronthaul rate constraints

Abstract

Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can solve lots of challenges in the next generation mobile communication system, including the demand for higher energy efficiency(EE). In C-RAN EE research field, most of recent work focuses on systematic energy saving and ignores the needs of users. To improve the performance of C-RAN under fronthaul capacity constraint, signal quantization techniques have been developed. But how to introduce `quantization' into C-RAN EE field is still an open issue. Motivated by this, in this paper, based on informational-optimal Gaussian quantization, we intend to design the suitable algorithms to maximize user-centric EE in the uplink communication of an orthogonal frequency division multiple access (OFDMA) based C-RAN. In the special case of single user and single RRH, we propose a joint optimization algorithm to maximize the uplink user-centric EE by optimizing power and fronthaul rate allocation. In the extended general case of multi-user and multi-RRH, we propose a Modified Particle Swarm Optimization(M-PSO) algorithm to solve the non-linear and non-convex issue for simplicity. Our simulation results show the proposed algorithms can improve the user-centric EE obviously compared with other optimal algorithms.