Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation
To address challenges such as co-frequency interference, spectrum scarcity, and uneven traffic distribution in multi-beam LEO satellites, a resource allocation algorithm based on decision performance evaluation was proposed. The system fairness was measured by a user satisfaction index and the syste...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2024-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024040/ |
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| _version_ | 1841539165851746304 |
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| author | WANG Chaowei PANG Mingliang WANG Su ZHAO Lingli GAO Feifei CUI Gaofeng WANG Weidong |
| author_facet | WANG Chaowei PANG Mingliang WANG Su ZHAO Lingli GAO Feifei CUI Gaofeng WANG Weidong |
| author_sort | WANG Chaowei |
| collection | DOAJ |
| description | To address challenges such as co-frequency interference, spectrum scarcity, and uneven traffic distribution in multi-beam LEO satellites, a resource allocation algorithm based on decision performance evaluation was proposed. The system fairness was measured by a user satisfaction index and the system throughput was optimized while considering fairness. The optimization problem was modeled as a multi-objective optimization. The continuous resource allocation process with temporal correlation was modeled as a Markov decision process, and a decision-evaluation dual-network algorithm was proposed to solve it. The decision network parameters were adjusted based on evaluation network results to optimize resource allocation and update the evaluation network parameters. Through iterative optimization, the decision network achieved accurate predictions. Simulation results show that the proposed algorithm outperforms traditional resource allocation algorithms in terms of throughput and fairness. |
| format | Article |
| id | doaj-art-03353942d186450d94ba8d3c48f25b07 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-07-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-03353942d186450d94ba8d3c48f25b072025-01-14T07:24:46ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-07-0145374767385023Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluationWANG ChaoweiPANG MingliangWANG SuZHAO LingliGAO FeifeiCUI GaofengWANG WeidongTo address challenges such as co-frequency interference, spectrum scarcity, and uneven traffic distribution in multi-beam LEO satellites, a resource allocation algorithm based on decision performance evaluation was proposed. The system fairness was measured by a user satisfaction index and the system throughput was optimized while considering fairness. The optimization problem was modeled as a multi-objective optimization. The continuous resource allocation process with temporal correlation was modeled as a Markov decision process, and a decision-evaluation dual-network algorithm was proposed to solve it. The decision network parameters were adjusted based on evaluation network results to optimize resource allocation and update the evaluation network parameters. Through iterative optimization, the decision network achieved accurate predictions. Simulation results show that the proposed algorithm outperforms traditional resource allocation algorithms in terms of throughput and fairness.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024040/multi-beam satellitedeep reinforcement learningmulti-objective optimizationresource management |
| spellingShingle | WANG Chaowei PANG Mingliang WANG Su ZHAO Lingli GAO Feifei CUI Gaofeng WANG Weidong Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation Tongxin xuebao multi-beam satellite deep reinforcement learning multi-objective optimization resource management |
| title | Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation |
| title_full | Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation |
| title_fullStr | Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation |
| title_full_unstemmed | Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation |
| title_short | Resource allocation algorithm for multi-beam LEO satellite based on decision performance evaluation |
| title_sort | resource allocation algorithm for multi beam leo satellite based on decision performance evaluation |
| topic | multi-beam satellite deep reinforcement learning multi-objective optimization resource management |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024040/ |
| work_keys_str_mv | AT wangchaowei resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation AT pangmingliang resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation AT wangsu resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation AT zhaolingli resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation AT gaofeifei resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation AT cuigaofeng resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation AT wangweidong resourceallocationalgorithmformultibeamleosatellitebasedondecisionperformanceevaluation |