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Rehenuma Tasnim Rodoshi
Rehenuma Tasnim Rodoshi
George Mason University
Geverifieerd e-mailadres voor chosun.kr
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Resource management in cloud radio access network: Conventional and new approaches
RT Rodoshi, T Kim, W Choi
Sensors 20 (9), 2708, 2020
572020
Reinforcement learning-based routing protocol for underwater wireless sensor networks: a comparative survey
RT Rodoshi, Y Song, W Choi
IEEE Access 9, 154578-154599, 2021
152021
Deep reinforcement learning based dynamic resource allocation in cloud radio access networks
RT Rodoshi, T Kim, W Choi
2020 International Conference on Information and Communication Technology …, 2020
92020
A survey on applications of deep learning in cloud radio access network
RT Rodoshi, W Choi
IEEE Access 9, 61972-61997, 2021
62021
Fuzzy logic and accelerated reinforcement learning-based user association for dense c-RANs
RT Rodoshi, T Kim, W Choi
IEEE Access 9, 117910-117924, 2021
32021
A Survey on Deep Learning for Cloud Radio Access Networks
RT Rodoshi, S Shin, W Choi
The 9th International Conference on Smart Media and Applications, 4-9, 2020
22020
Apparatus and method for dynamic resource allocation in cloud radio access networks
W Choi, RT Rodoshi
US Patent App. 17/487,516, 2022
2022
Reinforcement Learning-based User Association for Cloud Radio Access Networks
RT Rodoshi
조선대학교 대학원, 2021
2021
Accuracy Analysis of User Location Prediction using Lagrange Polynomial
RT Rodoshi, W Choi
한국통신학회 학술대회논문집, 47-48, 2020
2020
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Artikelen 1–9