2023 Fiscal Year Annual Research Report
Radio Resource Management in 5G and Beyond Networks: A Layered In-network Learning Approach
| Project/Area Number |
20K11764
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| Research Institution | Ibaraki University |
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Principal Investigator |
王 瀟岩 茨城大学, 理工学研究科(工学野), 准教授 (10725667)
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| Co-Investigator(Kenkyū-buntansha) |
梅比良 正弘 茨城大学, 理工学研究科(工学野), 特命研究員 (00436239)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | wireless access / federated learning |
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| Outline of Annual Research Achievements |
We have realized and evaluated the proposed layered in-network learning approach. Specifically, the main functions of FL is implemented in a GPU-workstation, and meanwhile, global gradient updating features has been added to the intelligent BSs. We extensively evaluated the performance in terms of network throughput, spectrum utilization, bandwidth consumption and convergence speed.
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