基于随机森林的复杂室内混合WiFi-LiFi网络接入点选择研究  

Access point selection for complex indoor hybrid WiFi-LiFi networks based on random forest

作　　者：张慧颖[1] 马成宇 梁士达 盛美春 李月月 ZHANG Huiying;MA Chengyu;LIANG Shida;SHENG Meichun;LI Yueyue(Jilin Institute of Chemical Technology,Jilin 132022,China)

机构地区：[1]吉林化工学院信息与控制工程学院,吉林吉林132022

出　　处：《光学技术》2024年第5期567-573,共7页Optical Technique

基　　金：吉林省科技厅自然科学基金联合基金(YDZJ202101ZYTS189)。

摘　　要：针对复杂室内环境下混合LiFi-WiFi异构网络接入点选择困难的问题,提出一种基于随机森林模型的混合LiFi-WiFi网络接入点选择算法。所提出的网络接入点选择算法利用多个网络的信道特性,通过模拟不同的室内复杂环境,采集不同位置用户在不同情况下的接收信号强度和信噪比等值,构建训练集,使模型能够适应各种复杂的室内环境。仿真结果表明,与传统网络选择算法相比,算法的平均可实现吞吐量提高了约82%,特别是在室内情况较为复杂时,可提高160%。在用户移动时,并且接入用户数量增加时,文章提出的算法可比其他算法切换次数显著减少20%。Aiming at the problem of difficulty in selecting access points for hybrid LiFi-WiFi heterogeneous networks in complex indoor environments, a random forest model-based access point selection algorithm for hybrid LiFi-WiFi networks is proposed.The proposed network access point selection algorithm utilizes the channel characteristics of multiple networks, and constructs a training set by simulating different complex indoor environments and collecting the equivalent values of received signal strength and signal-to-noise ratio of users at different locations in different situations, so that the model can adapt to various complex indoor environments. Simulation results show that compared with the traditional network selection algorithm, the average user reachable throughput of this algorithm is improved by about 82%, especially when the indoor situation is more complex, it can be improved by 160%. The algorithm proposed can significantly reduce the number of switching times by 20% compared with other algorithms when the users are moving and the number of accessed users increases.

关 键 词：信息光学 混合网络 可见光通信(LiFi) 随机森林 

分 类 号：TN929.12[电子电信—通信与信息系统]