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Efficient Resource Scheduling and Optimization for Over-Loaded LEO-Terrestrial Networks
yuan, Yaxiong; Lei, Lei; Vu, Thang Xuan et al.
2022In Proceeding of IEEE ICC 2022
Peer reviewed
 

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Keywords :
LEO satellites; resource allocation; reinforcement learning
Abstract :
[en] Towards the next generation networks, low earth orbit (LEO) satellites have been considered as a promising component for beyond 5G networks. In this paper, we study downlink LEO-5G communication systems in a practical scenario, where the integrated LEO-terrestrial system is over-loaded by serving a number of terminals with high-volume traffic requests. Our goal is to optimize resource scheduling such that the amount of undelivered data and the number of unserved terminals can be minimized. Due to the inherent hardness of the formulated quadratic integer programming problem, the optimal algorithm requires unaffordable complexity. To solve the problem, we propose a near-optimal algorithm based on alternating direction method of multipliers (ADMM-HEU), which saves computational time by taking advantage of the distributed ADMM structure, and a low-complexity heuristic algorithm (LC-HEU), which is based on estimation and greedy methods. The results demonstrate the near-optimality of ADMM-HEU and the computational efficiency of LC-HEU compared to the benchmarks.
Disciplines :
Electrical & electronics engineering
Author, co-author :
yuan, Yaxiong
Lei, Lei;  Xi'an Jiaotong University
Vu, Thang Xuan  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Fowler, Scott
Chatzinotas, Symeon  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
External co-authors :
yes
Language :
English
Title :
Efficient Resource Scheduling and Optimization for Over-Loaded LEO-Terrestrial Networks
Publication date :
May 2022
Event name :
IEEE International Conference on Communications
Event date :
16-5-2022
Main work title :
Proceeding of IEEE ICC 2022
Peer reviewed :
Peer reviewed
FnR Project :
FNR13718904 - Autonomous Network Slicing For Integrated Satellite-terrestrial Transport Networks, 2019 (01/06/2020-31/05/2023) - Symeon Chatzinotas
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since 07 December 2022

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