Multi-agent reinforcement learning based dynamic optimization algorithm of CRE offset for heterogeneous networks
To cope with the high throughput demand caused by the proliferation of wireless network users, a multi-agent reinforcement learning based dynamic optimization algorithm of cell range expansion (CRE) offset was proposed for interference scenarios in macro-pico heterogeneous networks.Based on the valu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2023-12-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023235/ |
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| Summary: | To cope with the high throughput demand caused by the proliferation of wireless network users, a multi-agent reinforcement learning based dynamic optimization algorithm of cell range expansion (CRE) offset was proposed for interference scenarios in macro-pico heterogeneous networks.Based on the value decomposition network framework of collaborative multi-agent reinforcement learning, a personalized online local decision of CRE offset for all pico-base stations was achieved by reasonably utilizing and interacting the intra-system user distribution and their interference levels among pico-base stations.Simulation results show that the proposed algorithm has significant advantages in increasing system throughput, balancing the throughput of each base station and improving edge-user throughput, compared to CRE=5 dB and distributed Q-learning algorithms. |
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| ISSN: | 1000-436X |