基于朴素贝叶斯的室内VLC网络天线选择方法  

Naive Bayesian-based antenna selection approach for indoor VLC network

作　　者：冷亭亭 张延彬[1] 王法松[1] LENG Ting-ting;ZHANG Yan-bin;WANG Fa-song(School of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]郑州大学电气与信息工程学院,郑州450001

出　　处：《控制与决策》2023年第1期67-74,共8页Control and Decision

基　　金：国家自然科学基金项目(61401401,U1736107,61901366);河南省科技攻关项目(192102210088);河南省高校科技创新人才基金项目(18HASTIT021);国家重点研发项目(019QY0302)。

摘　　要：在室内多天线多用户可见光通信(VLC)网络中,为了改善在发射天线和用户数量增多的情况下,最优天线选择算法存在时间复杂度过高问题,将朴素贝叶斯(NB)方法应用于室内多用户VLC网络下行链路发光二极管(LED)选择问题中.首先,将该LED选择任务建模为多分类问题,利用用户已知信道状态信息生成训练样本集,并通过VLC网络多用户通信和速率最大生成对应类标签;其次,利用生成的训练样本集,通过NB方法得到分类器模型;最后,将训练得到的分类器模型应用于新用户的LED选择.仿真分析表明,与最优多用户VLC网络LED选择算法相比,所提出的基于NB的LED选择方案可以有效地降低时间复杂度,在算法复杂度和用户传输和速率之间实现了较好的平衡.In the indoor visible light communications(VLC)network with multiple antennas and multiple users,in order to improve the time complexity of the optimal antenna selection algorithm under the condition of increasing number of transmittin g antennas and users,the naive B ayes(NB)method is applied to the downlink light emitting diodes(LED)selection problem of the indoor multi-user VLC network.Firstly,the LED selection task is modelled as a multiclassification problem,and the training sample set is generated using the users’known channel state information.Then,the corresponding class labels are generated by maximizing the sum-rate of the multi-user VLC network.Futher,based on the generated training sample set,the classifier model is obtained using the NB method.Finally,the trained classifier model is applied to the LED selection of new users.Simulation results show that,compared with the optimal LED selection algorithm of the multi-user VLC network,the proposed LED selection scheme based on the NB method can effectively reduce the time complexity and achieve a good balance between algorithm complexity and system sum-rate.

关 键 词：朴素贝叶斯算法 LED选择 和速率 多用户 支持向量机 可见光通信 

分 类 号：TN911.25[电子电信—通信与信息系统]