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Thi Ha Ly Dinh
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2020 – today
- 2024
- [j6]Megumi Kaneko
, Thi Ha Ly Dinh, Yousef N. Shnaiwer
A Multi-Agent Risk-Averse Reinforcement Learning Method for Reliability Enhancement in Sub-6GHz/mmWave Mobile Networks. IEEE Wirel. Commun. Lett. 13(10): 2657-2661 (2024) - [c10]Thanh Trung Nguyen, Minh Hai Vu
MuLeS: A Multi-Client Learning-Based MPQUIC Scheduler. CCNC 2024: 656-661 - [c9]Minh Hai Vu, Thanh Trung Nguyen, Thi Ha Ly Dinh, Phi Le Nguyen, Kien Nguyen:
LoGra: an LSTM-DDPG Integrated MPQUIC Scheduler for Mobile Video Streaming. VTC Fall 2024: 1-5 - 2023
- [j5]Megumi Kaneko, Thi Ha Ly Dinh, Kenichi Kawamura, Takatsune Moriyama, Yasushi Takatori:
Wireless Multi-Interface Connectivity with Deep Learning-Enabled User Devices: An Energy Efficiency Perspective. IEEE Netw. 37(3): 132-139 (2023) - [c8]Giang Nguyen, Thi Ha Ly Dinh, Thanh Hung Nguyen, Kien Nguyen, Phi Le Nguyen
A Data-Driven Scheduling Strategy for Mobile Air Quality Monitoring Devices. ACIIDS (2) 2023: 74-86 - [c7]Nam Duong Tran, Manh Cuong Dao, Thanh Hung Nguyen, Thi Ha Ly Dinh, Kien Nguyen, Phi Le Nguyen
A Deep Reinforcement Learning-Based Multi-objective Optimization for Crowdsensing-Based Air Quality Monitoring Systems. ACIIDS (Companion) 2023: 436-448 - 2022
- [j4]Thi Ha Ly Dinh
Device Selection and Beamforming Optimization in Large-Scale mmWave IoT Networks. IEEE Internet Things J. 9(24): 25395-25408 (2022) - [c6]Thi Ha Ly Dinh, Megumi Kaneko, Kenichi Kawamura, Takatsune Moriyama, Yasushi Takatori:
Improving Reliability by Risk-Averse Reinforcement Learning over Sub6GHz/mmWave Integrated Networks. ICC 2022: 3178-3183 - 2021
- [j3]Thi Ha Ly Dinh
Distributed user-to-multiple access points association through deep learning for beyond 5G. Comput. Networks 197: 108258 (2021) - [j2]Thi Ha Ly Dinh
Energy Efficient Resource Allocation Optimization in Fog Radio Access Networks With Outdated Channel Knowledge. IEEE Trans. Green Commun. Netw. 5(1): 146-159 (2021) - [c5]Thi Ha Ly Dinh, Megumi Kaneko, Keisuke Wakao, Kenichi Kawamura, Takatsune Moriyama, Hirantha Abeysekera, Yasushi Takatori:
Deep Reinforcement Learning-based User Association in Sub6GHz/mmWave Integrated Networks. CCNC 2021: 1-7 - [c4]Thi Ha Ly Dinh, Megumi Kaneko, Keisuke Wakao, Kenichi Kawamura, Takatsune Moriyama, Yasushi Takatori:
Towards an Energy-Efficient DQN-based User Association in Sub6GHz/mmWave Integrated Networks. MSN 2021: 645-652 - 2020
- [i2]Thi Ha Ly Dinh, Megumi Kaneko, Ellen Hidemi Fukuda, Lila Boukhatem:
Energy Efficient Resource Allocation Optimization in Fog Radio Access Networks with Outdated Channel Knowledge. CoRR abs/2009.12275 (2020)
2010 – 2019
- 2019
- [j1]Megumi Kaneko, Lila Boukhatem, Nicolas Pontois, Thi Ha Ly Dinh:
User Pre-Scheduling and Beamforming with Imperfect CSI for Future Cloud/Fog-Radio Access Networks. IEICE Trans. Commun. 102-B(7): 1230-1239 (2019) - [c3]Thi Ha Ly Dinh, Megumi Kaneko, Lila Boukhatem:
Energy-Efficient User Association and Beamforming for 5G Fog Radio Access Networks. CCNC 2019: 1-6 - [c2]Thi Ha Ly Dinh, Megumi Kaneko, Keisuke Wakao, Hirantha Abeysekera, Yasushi Takatori:
Reinforcement Learning-Aided Distributed User-to-Access Points Association in Interfering Networks. GLOBECOM 2019: 1-6 - 2018
- [c1]Nicolas Pontois, Megumi Kaneko, Thi Ha Ly Dinh, Lila Boukhatem:
User Pre-Scheduling and Beamforming with Outdated CSI in 5G Fog Radio Access Networks. GLOBECOM 2018: 1-6 - [i1]Nicolas Pontois, Megumi Kaneko, Thi Ha Ly Dinh, Lila Boukhatem:
User Pre-Scheduling and Beamforming with Imperfect CSI in 5G Fog Radio Access Networks. CoRR abs/1802.01104 (2018)
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