Sparse beamforming based energy efficiency optimization for distributed antenna systems

Abstract

In this paper, we propose a sparse beamforming based energy efficiency (EE) maximization problem for multi-user distributed antenna systems (DASs). In DAS, the power consumption of remote antenna units (RAUs) and corresponding backhaul links have an important influence on the whole network efficiency. Hence this paper addresses RAU selection. We select optimal RAUs and corresponding backhaul links to operate in sleep mode when building the network power consumption model. Meanwhile, the power consumption of backhaul also plays a significant role, and RAU clustering is considered when calculate backhaul power consumption. With QoS requirements and per-RAU power constraints, a non-convex joint optimization problem considering transmit beamforming, RAU selection and RAU clustering is presented. In order to solve the problem, a series of operations including equivalent transformations, convex relaxation and compressed sensing are performed. An iterative algorithm is designed to solve the practical problem. Simulation results show the proposed algorithm can converge at a fast rate, and there are optimal number of users and RAUs achieving the largest EE.