GAN-BASED JOINT ACTIVITY DETECTION AND CHANNEL ESTIMATION FOR GRANT-FREE RANDOM ACCESS

doi:10.1109/ICASSP43922.2022.9746152

	GAN-BASED JOINT ACTIVITY DETECTION AND CHANNEL ESTIMATION FOR GRANT-FREE RANDOM ACCESS
	Liang, Shuang1,2,3 ; Zou, Yinan1,2,3 ; Zhou, Yong1
	2022
会议录名称	ICASSP, IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING - PROCEEDINGS
ISSN	1520-6149
卷号	2022-May
页码	4413-4417
发表状态	已发表
DOI	10.1109/ICASSP43922.2022.9746152
摘要	Joint activity detection and channel estimation (JADCE) for grant-free random access is a critical issue that needs to be addressed to support massive connectivity in IoT networks. However, the existing model-free learning method can only achieve either activity detection or channel estimation, but not both. In this paper, we propose a novel model-free learning method based on generative adversarial network (GAN) to tackle the JADCE problem. We adopt the U-net architecture to build the generator rather than the standard GAN architecture, where a pre-estimated value that contains the activity information is adopted as input to the generator. By leveraging the properties of the pseudoinverse, the generator is refined by using an affine projection and a skip connection to ensure the output of the generator is consistent with the measurement. Moreover, we build a two-layer fully-connected neural network to design pilot matrix for reducing the impact of receiver noise. Simulation results show that the proposed method outperforms the existing methods in high SNR regimes, as both data consistency projection and pilot matrix optimization improve the learning ability. © 2022 IEEE
会议录编者/会议主办者	Chinese and Oriental Languages Information Processing Society (COLPIS) ; Singapore Exhibition and Convention Bureau ; The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen) ; The Institute of Electrical and Electronics Engineers Signal Processing Society
关键词	Massive connectivity joint activity detection and channel estimation deep generative adversarial network
会议名称	47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
会议地点	Virtual, Online, Singapore
会议日期	May 23, 2022 - May 27, 2022
URL	查看原文
收录类别	EI ; CPCI-S
语种	英语
资助项目	National Natural Science Foundation of China (NSFC)[U20A20159]
WOS研究方向	Acoustics ; Computer Science ; Engineering
WOS类目	Acoustics ; Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000864187904140
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20222312198126
原始文献类型	Conference article (CA)
来源库	IEEE
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/206370
专题	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_周勇组
通讯作者	Liang, Shuang; Zou, Yinan; Zhou, Yong
作者单位	1.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China 2.Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R 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	Liang, Shuang,Zou, Yinan,Zhou, Yong. GAN-BASED JOINT ACTIVITY DETECTION AND CHANNEL ESTIMATION FOR GRANT-FREE RANDOM ACCESS[C]//Chinese and Oriental Languages Information Processing Society (COLPIS), Singapore Exhibition and Convention Bureau, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), The Institute of Electrical and Electronics Engineers Signal Processing Society. 345 E 47TH ST, NEW YORK, NY 10017 USA:Institute of Electrical and Electronics Engineers Inc.,2022:4413-4417.