Multi-Antenna Channel Interpolation via Tucker Decomposed Extreme Learning Machine
文献类型：期刊论文
| 作者 | Zhang, Han2; Ai, Bo3; Xu, Wenjun1; Xu, Li4; Cui, Shuguang2 |
| 刊名 | IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
 |
| 出版日期 | 2019-07-01 |
| 卷号 | 68期号:7页码:7160-7163 |
| 关键词 | Channel interpolation extreme learning machine tensor decomposition |
| ISSN号 | 0018-9545 |
| DOI | 10.1109/TVT.2019.2913865 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:000476775000077 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/4473]  |
| 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.Beijing Univ Posts & Telecommun, Minist Educ, Key Lab Universal Wireless Commun, Beijing 100876, Peoples R China 2.Univ Calif Davis, Dept Elect & Comp Engn, Davis, CA 95616 USA 3.Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, 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. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。