基于用户选择的大规模MIMO能效联合优化算法  

An Energy Efficiency Optimization Algorithm for Massive MIMO Systems Based on User Selection

作　　者：智应娟 曹海燕[1] 马智尧 许方敏[1] 方昕[1] ZHI Yingjuan;CAO Haiyan;MA Zhiyao;XU Fangmin;FANG Xin(School of Communication Engineering,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)

机构地区：[1]杭州电子科技大学通信工程学院,浙江杭州310018

出　　处：《杭州电子科技大学学报（自然科学版）》2020年第5期7-12,共6页Journal of Hangzhou Dianzi University：Natural Sciences

基　　金：国家自然科学基金资助项目(61501158);浙江省自然科学基金资助项目(LY14F010019,LY20F010009)。

摘　　要：针对单小区多用户大规模多输入多输出上行链路系统,为实现能效最大化,采用迫零接收,提出一种联合优化基站天线数、发射功率、用户集的资源分配算法。将复杂的三变量联合优化问题转化为两个子优化问题,首先利用凸优化理论对天线数、发射功率进行联合优化,推导出最优天线数和最优发射功率的表达式;然后引入注水法思想,优先服务信道条件较好的用户,对用户集进行优化。在此基础上,采用Dinkelbach算法,分别对3个变量,即基站天线数、发射功率、用户集进行迭代优化。仿真结果表明,所提算法能有效提高能量效率和频谱效率,并且降低发射功率。For a single-cell multi-user large-scale multiple-input multiple-output uplink system,in order to maximize energy efficiency,a resource allocation algorithm with zero-forcing reception is proposed,which jointly optimizes the number of base station antennas,transmit power,and user set.The complicated joint optimization problem of triple variables is transformed into two sub-optimization problems.Firstly,the convex optimization theory is used to jointly optimize the number of antennas and transmit power,and the expressions of the optimal number of antennas and optimal transmit power are derived;secondly,to optimize the user set by using water-filling method to serve for the users with better channel conditions.Based on this,Dinkelbach algorithm is used to iteratively optimize three variables,namely the numbers of base station antennas,transmit power,and user set.Simulation results show that the proposed algorithm can effectively improve energy efficiency and spectrum efficiency while greatly reduce transmission power.

关 键 词：大规模多输入多输出 能效 迫零接收 联合优化 

分 类 号：TN929.53[电子电信—通信与信息系统]