Energy-efficient power allocation for distributed large-scale MIMO cloud radio access networks

Recently, promoting energy efficiency is an important research issue in the wireless communication system. This paper investigates the resource management problem with the regularized zero-forcing (RZF) precoding for the distributed large-scale multiple-input multiple-output cloud radio access network (DLS MIMO C-RAN) which consists of a large number of spatially distributed remote radio heads (RRHs). The challenges of this power allocation problem arise from the presence of both interference and imperfect channel state information at the transmitter (CSIT). Therefore, the C-RAN based power allocation schemes are designed to efficiently allocate the transmit power of each RRH. Moreover, the large random matrix theory is applied to derive the asymptotic expressions for large number of antennas. Simulation results show that the proposed schemes can provide better energy efficiency with the consideration of quality-of-service (QoS) support.