多输入多输出
数学优化
光谱效率
粒子群优化
计算机科学
最优化问题
高效能源利用
帕累托原理
多目标优化
多群优化
算法
数学
工程类
电信
频道(广播)
电气工程
波束赋形
作者
Yuetian Zhou,Oiaoqiao Zhang,Xin Xu,Mingshuo Wei
标识
DOI:10.1109/bmsb55706.2022.9828598
摘要
When the number of transmit antennas is much larger than the number of users in a cell, massive MIMO systems can activate partial transmit antennas by controlling the number of transmit antennas, thus achieving both higher spectral efficiency and higher energy efficiency. Based on the above scenarios, the energy efficiency and spectral efficiency of massive MIMO systems are considered in this paper, the idea of solving multi-objective optimization problems directly replaces converting the multi-objective optimization problems into single-objective one to solve, so as to obtain plenty of Pareto optimal solutions by particle swarm optimization algorithm at one iteration. In this paper, we present a multi-objective optimization algorithm MOPSO to solve the problem of EE-SE joint optimization in massive MIMO systems. The feasibility and superiority of the proposed scheme are verified by comparing the system simulation with the existing single-objective optimization PSO algorithm. Compared with the single-objective optimization algorithm, the plenty of solution set achieved by MOPSO which evenly distributed on the Pareto frontier, has better diversity of decision variables.
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