A Novel Dual-Driven Channel Estimation Scheme for Spatially Non-Stationary Fading Environments

doi:10.1109/TWC.2023.3336973

	A Novel Dual-Driven Channel Estimation Scheme for Spatially Non-Stationary Fading Environments
	Jiang, Jiaqi 1; Lian, Lixiang2 ; Yu, Tao 1; Shi, Qi 1; Zhang, Shunqing 1; Chen, Xiaojing 1; Lau, Vincent K. N.3
	2023
发表期刊	IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (IF:8.9[JCR-2023],8.6[5-Year])
ISSN	1558-2248
EISSN	1558-2248
卷号	PP 期号:99 页码:1-1
发表状态	已发表
DOI	10.1109/TWC.2023.3336973
摘要	Channel estimation is crucial to modern wireless systems and becomes increasingly challenging when the ultra-sized antenna is configured in sub-6GHz wireless communication systems. In an ultra-massive multiple-input multiple-output (U-MIMO) orthogonal frequency division multiplex (OFDM) system, the channel demonstrates spatial non-stationarity. Additionally, the limited pilot location in the OFDM system further complicates the channel estimation process. In this paper, we propose a model-data dual-driven (MDD) scheme to jointly perform the model-driven non-stationary channel denoising and the data-driven channel interpolation in an end-to-end way, which is followed by a low-complexity channel refinement module to improve the robustness of the proposed scheme. Specifically, image contour extraction (ICE) is utilized to effectively eliminate the non-stationary noises in the channel matrices before being sent to the downstream interpolation network. An enhanced convolutional neural network (CNN)-based residual network (eCNN-RN) is developed to perform non-linear interpolations for recovering the U-MIMO-OFDM channels. Based on ICE, the proposed online refinement module can improve the generalizability of the learned model to a practical environment. Numerical experiments demonstrate the efficiency and the effectiveness of the cross-fertilization of the model-driven and data-driven approaches. IEEE
关键词	channel estimation non-stationary dual driven multiple input multiple output
URL	查看原文
收录类别	EI ; SCI
语种	英语
资助项目	National Natural Science Foundation of China (NSFC)[62071284] ; National Key Research and Development Program of China["2022YFB2902304","2022YFB2902002","2022YFB2902005"] ; Key-Area Research and Development Program of Guangdong Province[2020B0101130012] ; Innovation Program of Shanghai Municipal Science and Technology Commission[21ZR1422400]
WOS研究方向	Engineering ; Telecommunications
WOS类目	Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001267002700084
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20235115236811
EI主题词	Interpolation
EI分类号	723.2 Data Processing and Image Processing ; 731.1 Control Systems ; 731.3 Specific Variables Control ; 802.3 Chemical Operations ; 921.6 Numerical Methods
原始文献类型	Article in Press
来源库	IEEE
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/347966
专题	信息科学与技术学院_PI研究组_廉黎祥组
通讯作者	Lian, Lixiang; Zhang, Shunqing
作者单位	1.School of Communication and Information Engineering, Shanghai University, Shanghai, China; 2.ShanghaiTech University, Shanghai, China; 3.Department of ECE, Hong Kong University of Science and Technology, Hong Kong, China
通讯作者单位	上海科技大学
推荐引用方式 GB/T 7714	Jiang, Jiaqi,Lian, Lixiang,Yu, Tao,et al. A Novel Dual-Driven Channel Estimation Scheme for Spatially Non-Stationary Fading Environments[J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,2023,PP(99):1-1.
APA	Jiang, Jiaqi.,Lian, Lixiang.,Yu, Tao.,Shi, Qi.,Zhang, Shunqing.,...&Lau, Vincent K. N..(2023).A Novel Dual-Driven Channel Estimation Scheme for Spatially Non-Stationary Fading Environments.IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,PP(99),1-1.
MLA	Jiang, Jiaqi,et al."A Novel Dual-Driven Channel Estimation Scheme for Spatially Non-Stationary Fading Environments".IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS PP.99(2023):1-1.