Channel Estimation Based on Contrastive Feature Learning with Few Labeled Samples

doi:10.1109/SPAWC53906.2023.10304517

	Channel Estimation Based on Contrastive Feature Learning with Few Labeled Samples
	Xu, Yihan; Lian, Lixiang
	2023-09-25
会议录名称	2023 IEEE 24TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC)
ISSN	1948-3244
页码	91-95
发表状态	已发表
DOI	10.1109/SPAWC53906.2023.10304517
摘要	Deep learning shows great potential in massive MIMO channel estimation (CE). The traditional channel estimator based on deep neural network (DNN) requires a large amount of labeled data when completing supervised learning. Considering that real channel state information (CSI) is difficult to obtain, such methods suffer from high training cost and limited ability to adapt to dynamic environment. In this paper, we propose an efficient and effective CE algorithm based on contrastive feature learning, which can learn the ground truth channel accurately with a limited number of labeled data. The location information is utilized to preprocess the received measurement to obtain positive and negative samples, after which, contrastive learning (CL) is exploited to effectively extract CSI features. The CSI features are fed into the downstream network to complete the CE task. To improve the effectiveness of feature extraction, a joint learning scheme is further proposed. Simulation results show that the contrastive feature learning can greatly reduce the required number of labeled data and enhance the overall CE performance. © 2023 IEEE.
会议录编者/会议主办者	IEEE Signal Processing Society ; The Institute of Electrical and Electronics Engineers (IEEE)
关键词	Contrastive feature learning channel estimation few labeled samples feature extraction
会议名称	24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023
会议地点	Shanghai, China
会议日期	25-28 Sept. 2023
URL	查看原文
收录类别	EI
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20234915163161
EI主题词	Feature extraction
EI分类号	461.4 Ergonomics and Human Factors Engineering ; 802.3 Chemical Operations
原始文献类型	Conference article (CA)
来源库	IEEE
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/348716
专题	信息科学与技术学院信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_廉黎祥组
通讯作者	Lian, Lixiang
作者单位	ShanghaiTech University, School of Information Science and Technology, Shanghai; 201210, China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Xu, Yihan,Lian, Lixiang. Channel Estimation Based on Contrastive Feature Learning with Few Labeled Samples[C]//IEEE Signal Processing Society, The Institute of Electrical and Electronics Engineers (IEEE):Institute of Electrical and Electronics Engineers Inc.,2023:91-95.