| 研究課題/領域番号 |
21K14162
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分21020:通信工学関連
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| 研究機関 | 国立研究開発法人理化学研究所 |
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研究代表者 |
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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| 研究期間 (年度) |
2021-04-01 – 2024-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
4,550千円 (直接経費: 3,500千円、間接経費: 1,050千円)
2023年度: 1,040千円 (直接経費: 800千円、間接経費: 240千円)
2022年度: 1,560千円 (直接経費: 1,200千円、間接経費: 360千円)
2021年度: 1,950千円 (直接経費: 1,500千円、間接経費: 450千円)
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| キーワード | 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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| 研究開始時の研究の概要 |
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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| 研究実績の概要 |
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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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
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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| 今後の研究の推進方策 |
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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