Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine

doi:10.1109/TVT.2019.2913865

	Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine
	Zhang, Han 1; Ai, Bo 2; Xu, Wenjun 3; Xu, Li 4; Cui, Shuguang 1
	2019-07-01
发表期刊	IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
ISSN	0018-9545
卷号	68 期号:7 页码:7160-7163
摘要	Channel interpolation is an essential technique for providing high-accuracy estimation of the channel state information for wireless systems design where the frequency-space structural correlations of multi-antenna channel are typically hidden in matrix or tensor forms. In this correspondence paper, a modified extreme learning machine (ELM) that can process tensorial data, or ELM model with tensorial inputs (TELM), is proposed to handle the channel interpolation task. The TELM inherits many good properties from ELMs. Based on the TELM, the Tucker decomposed extreme learning machine is proposed for further improving the performance. Furthermore, we establish a theoretical argument to measure the interpolation capability of the proposed learning machines. Experimental results verify that our proposed learning machines can achieve comparable mean squared error (MSE) performance against the traditional ELMs but with 15% shorter running time, and outperform the other methods for a 20% margin measured in MSE for channel interpolation.
关键词	Channel interpolation extreme learning machine tensor decomposition
DOI	10.1109/TVT.2019.2913865
收录类别	SCI
语种	英语
资助项目	National Science Foundation[CNS-1824553] ; National Science Foundation[DMS-1622433] ; National Science Foundation[AST-1547436] ; National Science Foundation[ECCS-1659025]
WOS研究方向	Engineering ; Telecommunications ; Transportation
WOS类目	Engineering, Electrical & Electronic ; Telecommunications ; Transportation Science & Technology
WOS记录号	WOS:000476775000077
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：12[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/4474
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Cui, Shuguang
作者单位	1.Univ Calif Davis, Dept Elect & Comp Engn, Davis, CA 95616 USA 2.Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China 3.Beijing Univ Posts & Telecommun, Minist Educ, Key Lab Universal Wireless Commun, Beijing 100876, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Han,Ai, Bo,Xu, Wenjun,et al. Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2019,68(7):7160-7163.
APA	Zhang, Han,Ai, Bo,Xu, Wenjun,Xu, Li,&Cui, Shuguang.(2019).Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine.IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,68(7),7160-7163.
MLA	Zhang, Han,et al."Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine".IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 68.7(2019):7160-7163.