User-Centric Association in Ultra-Dense mmWave Networks via Deep Reinforcement Learning

doi:10.1109/LCOMM.2021.3108013

UM > THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)

Residential College	false
Status	已發表Published
	User-Centric Association in Ultra-Dense mmWave Networks via Deep Reinforcement Learning
	Xue, Qing 1; Sun, Yao 2; Wang, Jian 3; Feng, Gang 4; Yan, Li 5; Ma, Shaodan1
	2021-08-26
Source Publication	IEEE Communications Letters
ISSN	1089-7798
Volume	25 Issue:11 Pages:3594-3598
Abstract	For ultra-dense networks, user-centric architecture is regarded as a promising candidate to offer mobile users better quality of service. One of the main challenges of user-centric architecture is exploring efficient scheme for user association in the ultra-dense network. In this letter, we study dynamic user-centric association (UCA) problem for ultra-dense millimeter wave (mmWave) networks to provide reliable connectivity and high achievable data rate. We consider time-varying network environments and propose a deep Q-network based UCA scheme to find the optimal association policy based on the historical experience. Simulation results are presented to verify the performance gain of our proposed scheme.
Keyword	Deep Learning Multiple Association Ultra-dense Mmwave Network User-centric
DOI	10.1109/LCOMM.2021.3108013
URL	View the original
Indexed By	SCIE
Language	英語English
WOS Research Area	Telecommunications
WOS Subject	Telecommunications
WOS ID	WOS:000716696200035
Publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141
Scopus ID	2-s2.0-85113825172
Fulltext Access	View Full-Text via DOI View Full-Text via Web of Science View Full-Text via Scopus
Citation statistics
Document Type	Journal article
Collection	THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) Faculty of Science and Technology DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding Author	Sun, Yao
Affiliation	1.Chongqing Key Laboratory of Mobile Communications Technology, Chongqing University of Posts and Telecommunications (CQUPT), Chongqing, China 2.James Watt School of Engineering, University of Glasgow, Glasgow, United Kingdom 3.National Key Laboratory of Science and Technology on Communications, UESTC, Chengdu, China 4.Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, Chengdu, China 5.State Key Lab. of Internet of Things for Smart City and the Dept. of Elec. and Computer Engineering, University of Macau, Macau, Macao
Recommended Citation GB/T 7714	Xue, Qing,Sun, Yao,Wang, Jian,et al. User-Centric Association in Ultra-Dense mmWave Networks via Deep Reinforcement Learning[J]. IEEE Communications Letters, 2021, 25(11), 3594-3598.
APA	Xue, Qing., Sun, Yao., Wang, Jian., Feng, Gang., Yan, Li., & Ma, Shaodan (2021). User-Centric Association in Ultra-Dense mmWave Networks via Deep Reinforcement Learning. IEEE Communications Letters, 25(11), 3594-3598.
MLA	Xue, Qing,et al."User-Centric Association in Ultra-Dense mmWave Networks via Deep Reinforcement Learning".IEEE Communications Letters 25.11(2021):3594-3598.

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