Satellite Communication System Resource Scheduling Algorithm Based on Artificial Intelligence
With the rapid growth of social economy, the requirements for resource utilization are becoming higher and higher. How to effectively solve the problem of energy shortage has become a hot topic. However, there are still many deficiencies in the current resource scheduling algorithm. For example, for...
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| Veröffentlicht in: | Procedia computer science Jg. 228; S. 551 - 558 |
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| Sprache: | Englisch |
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Elsevier B.V
2023
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| Abstract | With the rapid growth of social economy, the requirements for resource utilization are becoming higher and higher. How to effectively solve the problem of energy shortage has become a hot topic. However, there are still many deficiencies in the current resource scheduling algorithm. For example, for different types of satellites with different needs and requirements, their performance indicators are different, and in the satellite communication system, the interaction between multiple nodes needs to be considered. Therefore, this paper studies the artificial intelligence algorithm, and proposes an improved particle complementary scheduling strategy for a single user in view of the shortcomings of the existing particle swarm optimization (PSO) algorithm. On this basis, this paper applies this method to evaluate the system performance and verify its effectiveness. The verification results show that the utilization efficiency of the satellite communication system resource scheduling algorithm is above 93%. |
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| AbstractList | With the rapid growth of social economy, the requirements for resource utilization are becoming higher and higher. How to effectively solve the problem of energy shortage has become a hot topic. However, there are still many deficiencies in the current resource scheduling algorithm. For example, for different types of satellites with different needs and requirements, their performance indicators are different, and in the satellite communication system, the interaction between multiple nodes needs to be considered. Therefore, this paper studies the artificial intelligence algorithm, and proposes an improved particle complementary scheduling strategy for a single user in view of the shortcomings of the existing particle swarm optimization (PSO) algorithm. On this basis, this paper applies this method to evaluate the system performance and verify its effectiveness. The verification results show that the utilization efficiency of the satellite communication system resource scheduling algorithm is above 93%. |
| Author | Zheng, Yufu Chen, Linli |
| Author_xml | – sequence: 1 givenname: Linli surname: Chen fullname: Chen, Linli email: zc15117188356@126.com – sequence: 2 givenname: Yufu surname: Zheng fullname: Zheng, Yufu |
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| CitedBy_id | crossref_primary_10_2139_ssrn_5066800 crossref_primary_10_3390_electronics13122374 |
| Cites_doi | 10.1002/sat.1396 10.1109/TWC.2021.3088609 10.1109/MCE.2022.3151325 10.1007/s00146-021-01294-x 10.1007/s00146-021-01298-7 10.1587/transfun.2019EAP1088 10.1109/MCE.2021.3135831 10.1109/LWC.2021.3056555 10.1002/sat.1443 10.1108/GS-03-2021-0030 10.1109/MCOM.001.2200508 10.1109/TAES.2021.3111787 10.1109/COMST.2022.3218527 10.1007/s00146-021-01289-8 10.1007/s10462-022-10206-4 10.1109/TVT.2021.3093117 10.1109/COMST.2022.3197695 10.1109/MC.2022.3212091 10.1002/sat.1455 10.1109/MC.2022.3212022 10.1109/LCOMM.2020.3029808 |
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| Keywords | Communication Algorithm Artificial Intelligence Resource Scheduling Satellite Communication |
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| Title | Satellite Communication System Resource Scheduling Algorithm Based on Artificial Intelligence |
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