移动多用户通信系统的功率分配智能优化

Power Allocation Intelligent Optimization for Mobile Multiuser Communication System

随着第五代移动通信技术的发展,移动用户的数量呈爆炸性增长.但是由于复杂多变的移动通信环境,对移动多用户通信系统的性能研究非常复杂,也是一个亟待解决的问题.本文在N-Nakagami信道下,建立了移动多用户通信系统模型,设计了发射天线选择(Transmit Antenna Selection,TAS)方案,研究了移动多用户通信系统的中断概率(Outage Probability,OP)性能.针对TAS方案,推导了系统中断概率的闭合表达式.然后建立功率优化目标函数,提出了基于增强灰狼算法的功率分配优化机制.和差分进化算法(Differential Evolution,DE),粒子群优化算法(Particle Swarm Optimization,PSO),布谷鸟搜索算法(Cuckoo Search,CS),萤火虫算法(Firefly Algorithm,FA)等进行了比较,仿真结果表明:本文所提出的算法优化性能更好,理论分析的正确性得到了验证。

With the development of the fifth generation mobile communication technology,the number of mobile users is exploding.Due to the complex and changeable mobile communication environment,the research on the performance of mobile multi-user communication system is very complicated,which is also an urgent problem to be solved.In this work,we establish the mobile multi-user communication system model,design the transmit antenna selection(TAS)scheme,and the outage probability(OP)performance over N-Nakagami fading channels is investigated.For the TAS scheme,the exact closed-form OP expressions is derived.Based on the derived OP expressions,we formulate the power allocation problem,and propose an enhanced grey wolf optimization(EGWO)-based power allocation optimization algorithm.We test differential evolution(DE)algorithm,particle swarm optimization(PSO)algorithm,cuckoo search(CS)algorithm,and firefly algorithm(FA).Compared to PSO,CS,FA,and DE algorithms,the Monte-Carlo results shows that the EGWO algorithm can consistently achieve higher OP performance results,which verifies the accuracy of the analytical results.