Radio Resource Management in 5G and Beyond Networks: A Layered In-network Learning Approach

Research Project

Project/Area Number	20K11764
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 60060:Information network-related
Research Institution	Ibaraki University
Principal Investigator	王瀟岩茨城大学, 理工学研究科(工学野), 准教授 (10725667)
Co-Investigator(Kenkyū-buntansha)	梅比良正弘茨城大学, 理工学研究科(工学野), 教授 (00436239)
Project Period (FY)	2020-04-01 – 2023-03-31
Project Status	Granted (Fiscal Year 2020)
Budget Amount *help	¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000) Fiscal Year 2022: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000) Fiscal Year 2021: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000) Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywords	In-network learning / radio resource
Outline of Research at the Start	Radio resource management (RRM) is the key enabler for full-featured 5G networks. In this research, we propose a layered in-networking learning RRM approach, and evaluate its performance via both simulations and experiments on testbeds.