重庆邮电大学学报（自然科学版）2024，Vol.36Issue(2)：209-219,11.DOI:10.3979/j.issn.1673-825X.202305090132
基于信道特征生成对抗网络的信道建模方法
Channel modeling method based on channel feature generative adversarial networks
摘要
Abstract
This paper proposes an improved model of generative adversarial networks(GAN)tailored for channel feature generation,named as channel feature generative adversarial networks(CFGAN).Using a completely unsupervised learning channel feature method,the model utilizes the mutual information relationship between the linear coding vector and the gen-erated channel,alongside variational mutual information maximization principles,to establish a correspondence between the coding vector and channel characteristics.The CFGAN model is trained using a dataset of measured indoor power line chan-nel data.The trained CFGAN can learn different channel feature distributions.Simulation shows that in a large dynamic range channel with an attenuation amplitude of-80～-10 dB,CFGAN can generate four types of channel models with signifi-cant differences based on the learned channel characteristics,and the difference in channel characteristics between the gen-erated channel and the measured channel is less than 2%.关键词
生成对抗网络/信道建模/互信息Key words
generative adversarial networks/channel modeling/mutual information分类
信息技术与安全科学引用本文复制引用
刘何鑫,段红光,黄凤翔..基于信道特征生成对抗网络的信道建模方法[J].重庆邮电大学学报（自然科学版）,2024,36(2):209-219,11.基金项目
重庆市基础与前沿研究计划项目(cstc2019jcyj-msxmX0079) The Chongqing Research Program of Basic Research and Frontier Technology(cstc2019jcyj-msxmX0079) （cstc2019jcyj-msxmX0079）
