Energy efficient power allocation strategy for downlink MU-MIMO with massive antennas

作     者：ZHAO Long ZHAO Hui ZHENG Kan 

作者机构：Key Laboratory of Universal Wireless Communication Ministry of Education Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing University of Posts and Telecommunications 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2013年第20卷第3期

页      面：1-7页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081001[工学-通信与信息系统] 

基　　金：supported by the Foundational Research Funds for the Central Universities the National Basic Research Program of China (2012CB316005) the Program for New Century Excellent Talents in University (NCET-11-0600) the National Key Technology R&D Program of China (2012ZX03004004) 

主　　题：green communications SE EE MU-MIMO zero-forcing 

摘      要：With the increasing energy consumption, energy efficiency （EE） has been considered as an important metric for wireless communication networks as spectrum efficiency （SE）. In this paper, EE optimization problem for downlink multi-user multiple-input multiple-output （MU-MIMO） system with massive antennas is investigated. According to the convex optimization theory, there exists a unique globally optimal power allocation achieving the optimal EE, and the closed-form of the optimal EE only related to channel state information is derived analytically. Then both the approximate and accurate power allocation algorithms with different complexity are proposed to achieve the optimal EE. Simulation results show that the optimal EE obtained by the approximate algorithm coincides to that achieved by the accurate algorithm within the controllable error limitation, and these proposed algorithms perform better than the existing equal power allocation algorithm. The optimal EE and corresponding SE increase with the number of antennas at base station, which is promising for the next generation wireless communication networks.