Energy Efficiency Enhancement in User-Centric and Cell-Free Millimeter-Wave Massive MIMO Systems With Hybrid Beamforming
Qinyuan Zheng, Pengcheng Zhu, Jiamin Li, Dongming Wang, Xiaohu You
Abstract
Cell-free massive multiple-input multiple-output (CF-mMIMO) is a new and scalable network architecture that can bring antennas closer to users. In addition, hybrid beamforming can greatly reduce the power consumption by limiting the number of radio frequency chains. To achieve higher energy efficiency (EE) of a wireless network, it is of practical interest to incorporate hybrid beamforming into CF-mMIMO systems to fully utilize their combined benefits. Moreover, user-centric scheme is considered so that idle access points (APs) can be turned into sleep mode for energy saving. In this paper, we formulate the EE maximization problem where user-AP association, hybrid beamformers and AP selection are jointly optimized with a realistic power consumption model. Due to the binary variables involved, the formulated problem is a mixed integer nonlinear programming problem. Given this setup, we first exploit the strong coupling between binary variables and continuous beamformers, then a group sparse beamforming method is used to induce group-sparsity of beamformers, and finally the original problem is transformed into a more tractable one. To reduce complexity, we propose another low-complexity method to solve the original problem by using an alternate optimization algorithm. Numerical results indicate the superiority of the two proposed algorithms over some well-known schemes.