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KF-LSTM Based Beam Tracking for UAV-Assisted mmWave HSR Wireless Networks
Yan, Li1; Fang, Xuming1; Fang, Yuguang2; Hao, Li1; Xue, Qing3,4; Xu, Chenren5
2022-10-01
Source PublicationIEEE Transactions on Vehicular Technology
ISSN0018-9545
Volume71Issue:10Pages:10796-10807
Abstract

Owing to the deployment flexibility, unmanned aerial vehicles (UAVs), equipped with lightweight base stations (BSs), provide a new paradigm for wireless access from the sky to temporarily complement terrestrial networks, which bring benefits to many applications, such high-speed railway (HSR) communications. In UAV-assisted wireless communications, the advantage of the line of sight (LOS) dominant air-ground channels makes it more attractive to apply directional millimeter wave (mmWave) communications, where beam management is highly related to user location. Nevertheless, due to the high mobility of UAVs and trains, how to accurately and efficiently track beams becomes a critical problem to solve. Based on this observation, in this paper, we first present an UAV-assisted dual-band HSR wireless network architecture, which integrates the frequency bands below 6 GHz (sub-6 GHz) to provide reliable transmissions for UAV controls and HSR safety services, with the mmWave bands to enhance the transmission capacity between UAVs and trains. To solve the beam tracking problem, we analyze the beam angular variations, and then propose an efficient algorithm based on Kalman filtering (KF) with varying update periods and long-short term memory (LSTM) to improve the beam tracking performance. Finally, we conduct extensive simulations to demonstrate that the proposed scheme can achieve more accurate beam tracking and higher spectrum efficiency.

KeywordDeep Learning High-speed Railway Integration Of Sub-6 Ghz And Mmwave bAnds Mmwave Beam Tracking Uav-assisted Wireless Access
DOI10.1109/TVT.2022.3187978
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Telecommunications ; Transportation
WOS SubjectEngineering, Electrical & Electronic Telecommunications, Transportation Science & Technology
WOS IDWOS:000870332400046
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141
Scopus ID2-s2.0-85134216496
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Citation statistics
Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorFang, Xuming
Affiliation1.Southwest Jiaotong University, Chengdu, 610031, China
2.University of Florida, Department of Electrical and Computer Engineering, Gainesville, 32611, United States
3.Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, Chongqing, 400065, China
4.University of Macau, State Key Laboratory of Internet of Things for Smart City, 999078, Macao
5.Peking University, Beijing, 100871, China
Recommended Citation
GB/T 7714
Yan, Li,Fang, Xuming,Fang, Yuguang,et al. KF-LSTM Based Beam Tracking for UAV-Assisted mmWave HSR Wireless Networks[J]. IEEE Transactions on Vehicular Technology, 2022, 71(10), 10796-10807.
APA Yan, Li., Fang, Xuming., Fang, Yuguang., Hao, Li., Xue, Qing., & Xu, Chenren (2022). KF-LSTM Based Beam Tracking for UAV-Assisted mmWave HSR Wireless Networks. IEEE Transactions on Vehicular Technology, 71(10), 10796-10807.
MLA Yan, Li,et al."KF-LSTM Based Beam Tracking for UAV-Assisted mmWave HSR Wireless Networks".IEEE Transactions on Vehicular Technology 71.10(2022):10796-10807.
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