长期演进(Long Term Evolution,LTE)作为当前主流的无线通信技术之一,其性能优化是当前研究的热点.文章针对LTE网络中的资源分配问题展开研究,通过分析正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术的基本原理,深入探讨其资源分配问题.针对传统粒子群优化(Particle Swarm Optimization,PSO)算法在资源分配过程中存在的局限性,文章研究一种基于混沌优化的PSO算法,以提高算法的全局搜索能力和收敛速度.通过在NS-3 仿真平台上进行实验验证,结果表明混沌优化的PSO算法在不同网络负载情况下均能有效增加系统吞吐量,相比传统PSO算法具有更好的性能表现.
Resource Allocation Strategy Based on Improved PSO in LTE Networks
As one of the mainstream wireless communication technologies,the performance optimization of Long Term Evolution(LTE)network is currently a hot research topic.This article focuses on the resource allocation problem in LTE networks,analyzes the basic principles of Orthogonal Frequency Division Multiplexing(OFDM)technology,and deeply explores its resource allocation problem.In response to the limitations of traditional Particle Swarm Optimization(PSO)algorithms in resource allocation,this paper studies a PSO algorithm based on chaotic optimization to improve the algorithm's global search ability and convergence speed.Through experimental verification on the NS-3 simulation platform,the results show that the chaos optimized PSO algorithm can effectively improve system throughput under different network load conditions,and has better performance compared to traditional PSO algorithms.
Long Term Evolution(LTE)Particle Swarm Optimization(PSO)chaos optimizationthroughput
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