Research On Joint Optimization Of Energy Efficiency And Spectral Efficiency Of Massive MIMO Based On Swarm Intelligence Algorithm

In recent years,massive MIMO has become one of the most potential technologies in the fifth generation(5G)of mobile communications due to its high spectral efficiency(SE)and energy efficiency(EE).In massive MIMO systems,there is a conflict between energy efficiency and spectral efficiency when considering the circuit power consumption and large-scale fading.This paper mainly studies how to choose transmit power and the number of transmit antennas to achieve the Pareto efficiency,and so that to meet the dual requirements of 5G for spectrum efficiency and energy efficiency.The Existing studies transformed this multi-objective optimization(MOO)problem into a single-objective optimization(SOO)problem,and proposed two effective algorithms called WS-PSO and NBI-PSO.In this paper,we considered to apply swarm intelligence optimization algorithm to solving this MOO problem directly,and analyzed their performances.The main work of this paper is as follows:1)Investigated the joint optimization model of SE and EE in the downlink of a single-cell multi-user MIMO system when base station(BS)adopts random transmit antenna selection and zero-forcing precoding.And analyzed the concavity and convexity of its Pareto front.2)Proposed an innovative solution to achieve EE-SE Pareto efficiency by using swarm intelligent optimization algorithm directly.We mainly proposed solutions based on NSGA-II algorithm and MOPSO algorithm,and we discussed the simulation designing,key procedures and their performances respectively.3)Programmed to realize the two proposed algorithms,and analyzed the merits and demerits of each algorithm.Simulation results showed that both of NSGA-II and MOPSO were effective in solving the joint EE-SE optimization problem and the obtained results had good convergence metric and diversity metric.