Resource Allocation and Computation Offloading in a Millimeter-Wave Train-Ground Network

doi:10.1109/TVT.2022.3185331

	Resource Allocation and Computation Offloading in a Millimeter-Wave Train-Ground Network
	Li, Linqian 1,2; Niu, Yong 1,3; Mao, Shiwen 4; Ai, Bo 1,2; Zhong, Zhangdui 1,2; Wang, Ning 5; Chen, Yali 6
	2022-10-01
发表期刊	IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
ISSN	0018-9545
卷号	71 期号:10 页码:10615-10630
摘要	In this paper, we consider an mmWave-based train-ground communication system in the high-speed railway (HSR) scenario, where the computation tasks of users can be partially offloaded to the rail-side base station (BS) or the mobile relays (MRs) deployed on the roof of the train. The MRs operate in the full-duplex (FD) mode to achieve high spectrum utilization. We formulate the problem of minimizing the average task execution latency of all users, under local device and MRs energy consumption constraints. We propose a joint resource allocation and computation offloading scheme (JRACO) to solve the problem. It consists of a resource allocation and computation offloading (RACO) algorithm and an MR Energy constraint algorithm. RACO utilizes the matching game theory to iterate between two subproblems, i.e., data segmentation and user association and sub-channel allocation. With the RACO results, the MR energy constraint algorithm ensures that the MR energy consumption constraint is satisfied. Extensive simulations validate that JRACO can effectively reduce the average latency and increase the number of served users compared with three baseline schemes.
关键词	Resource management Task analysis Rail transportation Energy consumption Communication systems Broadband communication Millimeter wave communication Full-duplex (FD) communications millimeter-wave (mmWave) communications mobile edge computing (MEC) resource allocation train-ground communications
DOI	10.1109/TVT.2022.3185331
收录类别	SCI
语种	英语
资助项目	Fundamental Research Funds for the Central Universities, China[2022JBXT001] ; Fundamental Research Funds for the Central Universities, China[2022JBQY004] ; National Natural Science Foundation of China[61801016] ; National Natural Science Foundation of China[61725101] ; National Natural Science Foundation of China[61961130391] ; National Natural Science Foundation of China[U1834210] ; National Key Research and Development Program[2021YFB2900301] ; State Key Laboratory of Rail Traffic Control and Safety[RCS2021ZT009] ; Beijing Jiaotong University ; Southeast University[2021D09] ; National Key R&D Program of China[2020YFB1806903] ; Fundamental Research Funds for the Central Universities[2020JBM089] ; Project of China Shenhua[GJNY-20-01-1] ; NSF[ECCS-1923717]
WOS研究方向	Engineering ; Telecommunications ; Transportation
WOS类目	Engineering, Electrical & Electronic ; Telecommunications ; Transportation Science & Technology
WOS记录号	WOS:000870332400033
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：6[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/2XEOYT63/19926
专题	中国科学院计算技术研究所期刊论文
通讯作者	Niu, Yong
作者单位	1.Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China 2.Beijing Jiaotong Univ, Beijing Engn Res Ctr High Speed Railway Broadband, Beijing 100044, Peoples R China 3.Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 211189, Peoples R China 4.Auburn Univ, Dept Elect & Comp Engn, Auburn, AL 36849 USA 5.Zhengzhou Univ, Sch Informat Engn, Zhengzhou 450001, Peoples R China 6.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Li, Linqian,Niu, Yong,Mao, Shiwen,et al. Resource Allocation and Computation Offloading in a Millimeter-Wave Train-Ground Network[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2022,71(10):10615-10630.
APA	Li, Linqian.,Niu, Yong.,Mao, Shiwen.,Ai, Bo.,Zhong, Zhangdui.,...&Chen, Yali.(2022).Resource Allocation and Computation Offloading in a Millimeter-Wave Train-Ground Network.IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,71(10),10615-10630.
MLA	Li, Linqian,et al."Resource Allocation and Computation Offloading in a Millimeter-Wave Train-Ground Network".IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 71.10(2022):10615-10630.