Massive CSI Acquisition for Dense Cloud-RANs With Spatial-Temporal Dynamics

doi:10.1109/TWC.2018.2797969

	Massive CSI Acquisition for Dense Cloud-RANs With Spatial-Temporal Dynamics
	Xuan Liu 1; Yuanming Shi2 ; Jun Zhang 3; Khaled B. Letaief 4
	2018-04
发表期刊	IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (IF:8.9[JCR-2023],8.6[5-Year])
ISSN	1536-1276
卷号	17 期号:4 页码:2557-2570
发表状态	已发表
DOI	10.1109/TWC.2018.2797969
摘要	Dense cloud radio access networks (cloud-RANs) provide a promising way to enable scalable connectivity and handle diversified service requirements for massive mobile devices. To fully exploit the performance gains of dense cloud-RANs, channel state information of both the signal link and interference links is required. However, with limited radio resources for training, the channel estimation problem in dense cloud-RANs becomes a high-dimensional estimation problem, i.e., the number of measurements will be typically smaller than the dimension of the channel. In this paper, we shall develop a generic high-dimensional structured channel estimation framework for dense cloud-RANs, which is based on a convex structured regularizing formulation. Observing that the wireless channel possesses ample exploitable statistical characteristics, we propose to convert the available spatial and temporal prior information into appropriate convex regularizers. Simulation results demonstrate that exploiting the spatial and temporal dynamics can achieve good estimation performance even with limited training resources. The alternating direction method of multipliers algorithm is further adopted to solve the resultant large-scale high-dimensional channel estimation problems. The proposed framework thus enjoys modeling flexibility, low training overhead, and computation cost scalability.
关键词	Cloud-RANs CSI high-dimensional structured estimation structured regularizers ADMM spatial and temporal dynamics and massive device connectivity
URL	查看原文
收录类别	SCI ; SCIE ; CPCI
语种	英语
资助项目	Shanghai Sailing Program[16YF1407700]
WOS研究方向	Engineering ; Telecommunications
WOS类目	Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000429695900031
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS关键词	SCALE CONVEX-OPTIMIZATION ; CHANNEL ESTIMATION ; M-ESTIMATORS ; MIMO ; FRAMEWORK ; NETWORKS
原始文献类型	Article ; Proceedings Paper
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/20185
专题	信息科学与技术学院信息科学与技术学院_PI研究组_石远明组
作者单位	1.School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia 2.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 3.Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong 4.Hamad Bin Khalifa University, Doha, Qatar
推荐引用方式 GB/T 7714	Xuan Liu,Yuanming Shi,Jun Zhang,et al. Massive CSI Acquisition for Dense Cloud-RANs With Spatial-Temporal Dynamics[J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,2018,17(4):2557-2570.
APA	Xuan Liu,Yuanming Shi,Jun Zhang,&Khaled B. Letaief.(2018).Massive CSI Acquisition for Dense Cloud-RANs With Spatial-Temporal Dynamics.IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,17(4),2557-2570.
MLA	Xuan Liu,et al."Massive CSI Acquisition for Dense Cloud-RANs With Spatial-Temporal Dynamics".IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 17.4(2018):2557-2570.