Learning-Based Joint Resource Slicing and Scheduling in Space-Terrestrial Integrated Vehicular Networks

Huaqing Wu; Jiayin Chen; Conghao Zhou; Junling Li; Xuemin(Sherman)Shen

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Learning-Based Joint Resource Slicing and Scheduling in Space-Terrestrial Integrated Vehicular Networks

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In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements.

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《通信与信息网络学报（英文）》 |2021年第003期|P.208-223|共16页
作者
Huaqing Wu; Jiayin Chen; Conghao Zhou; Junling Li; Xuemin(Sherman)Shen;
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作者单位

Department of Electrical and Computer Engineering University of Waterloo Waterloo.ON N2L 3G1 Canada;

Department of Electrical and Computer Engineering the University of British Columbia Vancouver BC V6T 1Z4 Canada;

Department of Electrical and Computer Engineering University of Waterloo Waterloo.ON N2L 3G1 Canada;

Shenzhen Institute of Artificial Intelligence and Robotics for Society(AIRS) and the Department of Electrical and Computer Engineering University of Waterloo Canada;

Department of Electrical and Computer Engineering University of Waterloo Waterloo.ON N2L 3G1 Canada;

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原文格式 PDF
正文语种 chi
中图分类 TN9;
关键词
space-terrestrial integrated vehicular networks; LEO satellite communication; resource slicing and scheduling; reinforcement learning; matching-based optimization;

Learning-Based Joint Resource Slicing and Scheduling in Space-Terrestrial Integrated Vehicular Networks

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