Millimeter-Wave Sensing and Mapping: A Low-Rank CP Decomposition Approach

被引：0

作者：

Zeng, Xianlong ^{[1
,2
]}

Wang, Peilan ^{[1
,2
]}

Fang, Jun ^{[1
,2
]}

机构：

[1] Univ Elect Sci & Technol China, Yangtze Delta Reg Inst Huzhou, Huzhou 313001, Peoples R China

[2] Univ Elect Sci & Technol China, Natl Key Lab Wireless Commun, Chengdu 611731, Peoples R China

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2024年 / 13卷 / 06期

关键词：

Sensors; Millimeter wave communication; Simultaneous localization and mapping; OFDM; Delay effects; Azimuth; Vectors; Integrated sensing and communication; millimeter wave communication; environment sensing and mapping; TENSOR DECOMPOSITION; LOCALIZATION; MIMO;

D O I：

10.1109/LWC.2024.3386164

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Integration sensing and communication (ISAC) has been envisaged as a promising candidate for 6G wireless communications. In this letter, we address a user-centric environment sensing and mapping on millimeter-Wave (mmWave) orthogonal frequency division multiplexing (OFDM) systems. By leveraging the inherent sparse characteristics of mmWave channels, the received signal in terms of the single-bounce reflected paths is formulated by a low-rank third-order tensor that admits a tensor rank decomposition. A structured CANDECOMP/PARAFAC (CP) decomposition based method is then developed to extract the sensing channel parameters for environment mapping. Simulation results show that the proposed method can achieve a centi-meter accuracy of localization and mapping.

引用

页码：1675 / 1679

页数：5

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