基于改进遗传算法的多AP联合传输方案研究

Research on multi-AP joint transmission scheme based on improved genetic algorithm

为解决密集Wi-Fi网络中重叠基本服务集(OBSS,overlapping basic service set)用户受到严重的同频干扰,导致接收信号信干噪比(SINR,signal to interference plus noise ratio)值低、数据传输速率低或者无法传输的问题,提出了一种基于改进遗传算法(IGA,improved genetic algorithm)选择接入点(AP,access point)协作集的多AP联合传输(JT,joint transmission)方案。首先,利用SINR阈值法将系统内所有站点(STA,station)分为中心用户和边缘用户,边缘用户采用JT方案。然后,以最大化边缘用户吞吐量为目标,利用IGA为每个边缘用户确定合适的协作AP形成其专属的AP协作集,最大化JT技术的潜在增益。仿真结果表明,所提方案在密集Wi-Fi网络场景下能够有效减小基本服务集(BSS,basic service set)间的同频干扰,提升BSS边缘用户的性能和吞吐量。

In order to solve the problem that overlapping basic service set(OBSS)users are subject to serious co-frequency interference in the dense Wi-Fi network,resulting in low signal to interference plus noise ratio(SINR)of received signals,low data transmission rate or inability to transmit,a multi-access point(AP)joint transmission(JT)scheme based on improved genetic algorithm(IGA)selection of AP coordination set was proposed.Firstly,the SINR threshold method was used to divide all station(STA)in the system into central users and edge users,and the JT scheme was adopted for edge users.Then,with the goal of maximizing the throughput of edge users,IGA was proposed to deter-mine the appropriate coordinated AP for each edge user to form its own AP coordination set,and maximize the potential gain of JT technology.The simulation results show that the proposed scheme can effectively reduce the co-frequency in-terference between BSS and improve the performance and throughput of BSS edge users in dense network.