Spectrum allocation algorithm based on multi-agent reinforcement learning in smart grid
In view of the fact that 5G networks are used to meet the service requirements of various power terminals in smart grid, a spectrum allocation algorithm based on multi-agent reinforcement learning was proposed.Firstly, for the integrated access backhaul system deployed in smart grid, considering the...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2023-09-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023179/ |
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| Summary: | In view of the fact that 5G networks are used to meet the service requirements of various power terminals in smart grid, a spectrum allocation algorithm based on multi-agent reinforcement learning was proposed.Firstly, for the integrated access backhaul system deployed in smart grid, considering the different communication requirements of services in lightweight and non-lightweight terminal, the spectrum allocation problem was formulated as a non-convex mixed-integer programming aiming to maximize the overall energy efficiency.Secondly, the above problem was modeled as a partially observable Markov decision process and transformed into a fully cooperative multi-agent problem, then a spectrum allocation algorithm was proposed which was based on multi-agent proximal policy optimization under the framework of centralized training and distributed execution.Finally, the performance of the proposed algorithm was verified by simulation.The results show that the proposed algorithm has a faster convergence speed and can increase the overall transmission rate by 25.2% through effectively reducing intra-layer and inter-layer interference and balancing the access and backhaul link rates. |
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| ISSN: | 1000-436X |