A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS
Low earth orbit mobile satellite system (LEO-MSS) is the major system to provide communication support for mobile terminals beyond the coverage of terrestrial communication systems. However, the quick movement of LEO satellites and current single-layer system architecture impose restrictions on the...
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doaj-319ec1c145ed45f9847b742bfc2d722a2021-03-30T02:53:57ZengIEEEIEEE Access2169-35362020-01-018185221853710.1109/ACCESS.2020.29685948966367A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSSYitao Li0https://orcid.org/0000-0001-9600-410XNa Deng1https://orcid.org/0000-0002-9565-559XWuyang Zhou2https://orcid.org/0000-0003-2229-2852Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, ChinaSchool of Information and Communication Engineering, Dalian University of Technology, Dalian, ChinaDepartment of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, ChinaLow earth orbit mobile satellite system (LEO-MSS) is the major system to provide communication support for mobile terminals beyond the coverage of terrestrial communication systems. However, the quick movement of LEO satellites and current single-layer system architecture impose restrictions on the capability to provide satisfactory service quality, especially for the remote and non-land regions with high traffic requirement. To tackle this problem, high-altitude platforms (HAPs) and terrestrial relays (TRs) are introduced to cover hot-spot regions, and the current single-layer system becomes an LEO-HAP multi-layer access network. Under this setup, we propose a hierarchical resource allocation approach to circumvent the complex management caused by the intricate relationships among different layers. Specifically, to maximize the throughputs, we propose a dynamic multi-beam joint resource optimization method in LEO-ground downlinks based on the predicted movement of LEO satellites. Afterwards, we propose the dynamic resource optimization method of HAP-ground downlinks when LEO satellites and HAPs share the same spectrum. To solve these problems, we use the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions to find the optimal solutions. Numerical results show that the proposed architecture outperforms current LEO-MSS in terms of average capacity. In addition, the proposed optimization methods increase the throughputs of LEO-ground downlinks and HAP-ground downlinks with an acceptable complexity.https://ieeexplore.ieee.org/document/8966367/Radio resource allocationmulti-beam satellitemulti-layer satellite networkLEO mobile satellite systemspace-air-ground integrated network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yitao Li Na Deng Wuyang Zhou |
spellingShingle |
Yitao Li Na Deng Wuyang Zhou A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS IEEE Access Radio resource allocation multi-beam satellite multi-layer satellite network LEO mobile satellite system space-air-ground integrated network |
author_facet |
Yitao Li Na Deng Wuyang Zhou |
author_sort |
Yitao Li |
title |
A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS |
title_short |
A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS |
title_full |
A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS |
title_fullStr |
A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS |
title_full_unstemmed |
A Hierarchical Approach to Resource Allocation in Extensible Multi-Layer LEO-MSS |
title_sort |
hierarchical approach to resource allocation in extensible multi-layer leo-mss |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Low earth orbit mobile satellite system (LEO-MSS) is the major system to provide communication support for mobile terminals beyond the coverage of terrestrial communication systems. However, the quick movement of LEO satellites and current single-layer system architecture impose restrictions on the capability to provide satisfactory service quality, especially for the remote and non-land regions with high traffic requirement. To tackle this problem, high-altitude platforms (HAPs) and terrestrial relays (TRs) are introduced to cover hot-spot regions, and the current single-layer system becomes an LEO-HAP multi-layer access network. Under this setup, we propose a hierarchical resource allocation approach to circumvent the complex management caused by the intricate relationships among different layers. Specifically, to maximize the throughputs, we propose a dynamic multi-beam joint resource optimization method in LEO-ground downlinks based on the predicted movement of LEO satellites. Afterwards, we propose the dynamic resource optimization method of HAP-ground downlinks when LEO satellites and HAPs share the same spectrum. To solve these problems, we use the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions to find the optimal solutions. Numerical results show that the proposed architecture outperforms current LEO-MSS in terms of average capacity. In addition, the proposed optimization methods increase the throughputs of LEO-ground downlinks and HAP-ground downlinks with an acceptable complexity. |
topic |
Radio resource allocation multi-beam satellite multi-layer satellite network LEO mobile satellite system space-air-ground integrated network |
url |
https://ieeexplore.ieee.org/document/8966367/ |
work_keys_str_mv |
AT yitaoli ahierarchicalapproachtoresourceallocationinextensiblemultilayerleomss AT nadeng ahierarchicalapproachtoresourceallocationinextensiblemultilayerleomss AT wuyangzhou ahierarchicalapproachtoresourceallocationinextensiblemultilayerleomss AT yitaoli hierarchicalapproachtoresourceallocationinextensiblemultilayerleomss AT nadeng hierarchicalapproachtoresourceallocationinextensiblemultilayerleomss AT wuyangzhou hierarchicalapproachtoresourceallocationinextensiblemultilayerleomss |
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1724184393019293696 |