通信学报2025，Vol.46Issue(5)：91-102,12.DOI:10.11959/j.issn.1000-436x.2025082
基于mRMR-GA的太赫兹信道场景识别研究
Research on scenario recognition for THz channels based on mRMR-GA
摘要
Abstract
To address the challenges of excessive feature parameter redundancy and insufficient scene correlation in tera-hertz(THz)channel scenario recognition,a recognition algorithm integrating the minimal redundancy maximal rel-evance(mRMR)criterion with genetic algorithm(GA)optimization was constructed based on feature selection theory and evolutionary computation principles.The crossover and mutation operations of channel characteristics were executed by the genetic algorithm(GA),and the optimal feature parameters with high scenario relevance were selected using the minimum redundancy maximum relevance(mRMR)criterion.These parameters were then inputed into a backpropaga-tion neural network model.To validate the method,a dataset containing 12 channel features was constructed with 1 745 groups of terahertz channel simulation data collected from indoor scenarios,and the model was trained and rigorously validated based on this dataset.The results demonstrate that the proposed algorithm improves accuracy and efficiency by 8%and 38.8%,respectively,and outperforms traditional algorithms in terms of convergence and transfer generalization capabilities.关键词
太赫兹信道/场景识别/特征选择/遗传算法/神经网络Key words
THz channel/scenario recognition/feature selection/genetic algorithm/neural network分类
电子信息工程引用本文复制引用
郝昕宇,廖希,王洋,林峰,罗娇,张杰..基于mRMR-GA的太赫兹信道场景识别研究[J].通信学报,2025,46(5):91-102,12.基金项目
国家自然科学基金资助项目(No.62271095,No.62171071) （No.62271095,No.62171071）
重庆市自然科学基金资助项目(No.CSTB2022NSCQ-MSX1125) （No.CSTB2022NSCQ-MSX1125）
重庆市教委科学技术研究资金资助项目(No.KJZD-K202300607) （No.KJZD-K202300607）
重庆市自然科学基金创新发展联合基金资助项目(No.CSTB2022NSCQ-LZX0037)The National Natural Science Foundation of China(No.62271095,No.62171071),The Natural Science Founda-tion of Chongqing(No.CSTB2022NSCQ-MSX1125),The Science and Technology Research Program of Chongqing Municipal Edu-cation Commission(No.KJZD-K202300607),The Natural Science Foundation Innovation and Development Joint Fund Project of Chongqing(No.CSTB2022NSCQ-LZX0037) （No.CSTB2022NSCQ-LZX0037）
