| Project/Area Number |
21K14162
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 21020:Communication and network engineering-related
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| Research Institution | Institute of Physical and Chemical Research |
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Principal Investigator |
Hashima Sherief 国立研究開発法人理化学研究所, 革新知能統合研究センター, 特別研究員 (00865462)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Project Status |
Granted (Fiscal Year 2022)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2023: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2022: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2021: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | RIS / UAV-mounted RIS / RIS relaying / Hybrid band RF/VLC / Load Balancing / MAB / PHE / RUCB, ETC / D2D Communications / millimeter wave (mmWave) / radio frequency (RF) / multi-armed bandit (MAB) / UCB / Thompson sampling (TS) / MOSS / WSNs / B5G / 6G / ML / D2D |
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| Outline of Research at the Start |
we develop combinatorial online ML algorithms to overcome mmWave D2D network problems to increase the efficiency and reliability of these networks. We propose novel online prediction methods for spectrum sensing/sharing in mmWave cognitive radio communications and mmWave interference mitigation to ease its deployment at highly dense scenarios. we implement different configurations of mmWave networks using commercial WiGig devices to assure the proposed ML schemes' validity and scalability in real scenarios.
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| Outline of Annual Research Achievements |
Hybrid Band RF/VLC optimization problem was formulated using budget constrained MABs and comparsion between different MAB solutions were conducted. Also, we proposed algorithm for UAV mounted RIS trajectory planning that maximizes the data rate and minimizes UAV energy consumption. Besides, we applied sophisticated MAB techniques (PHE and MOTS) to the same problem with superior performance outcome.
Dual objective bandits were implemented to RIS relay probing to maximize the BS-user NLOS linkage data rate and minimize the beaform training time.The problem of mmWave RIS-user association in muliple RIS multi-user scenarios is considered to maximize users’ achievable data rates while maintaining load balance among the deployed RIS boards.Three centralized MP-MAB algorithms with arms’ load alancing, coming from the family of upper confidence bound (UCB), namely UCB1-LB, Kullback-Leibler UCB-LB (KLUCB-LB), and minimax optimal stochastic strategy-LB (MOSS-LB), are proposed to address the formulated bandit game and to compare their performance.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Still more 6G based problems need further investigation and formulations such as UAV-NOMA scenario, Metaverse, V2I, Multiobjective optimization problems, etc. Also, the experimental part is still under implementation to validate theoritcal outcomes.
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| Strategy for Future Research Activity |
Multi hop RIS relay probing problem will be under investigation.
we will further investigate the current metaverse problems and find suitable online formulations and algorithm solutions.
In vehicular communications, we will find better online solutions for over the air software updates for the vehicles using V2I scenarios.
Hence, we will deploy theoritically guranteed algorithms for these problems
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