Dynamic Spectrum Access for Ambient Backscatter Communication-assisted D2D Systems with Quantum Reinforcement Learning

no code implementations • 23 Oct 2024 • Nguyen Van Huynh, Bolun Zhang, Dinh-Hieu Tran, Dinh Thai Hoang, Diep N. Nguyen, Gan Zheng, Dusit Niyato, Quoc-Viet Pham

For that, we develop a novel quantum reinforcement learning (RL) algorithm that can achieve a faster convergence rate with fewer training parameters compared to DRL thanks to the quantum superposition and quantum entanglement principles.

Deep Reinforcement Learning Reinforcement Learning (RL)

Multi-Agent Deep Reinforcement Learning for Resilience Optimization in 5G RAN

no code implementations • 25 Jul 2024 • Soumeya Kaada, Dinh-Hieu Tran, Nguyen Van Huynh, Marie-Line Alberi Morel, Sofiene Jelassi, Gerardo Rubino

Extensive simulations then demonstrate that with our proposed solution, the average service availability in terms of user throughput can be increased by up to 50-60% on average, while reaching a coverage availability of 99% in best cases.

Deep Reinforcement Learning

UAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization

no code implementations • 1 Aug 2020 • Dinh-Hieu Tran, Van-Dinh Nguyen, Sumit Gautam, Symeon Chatzinotas, Thang X. Vu, Bjorn Ottersten

In this context, we aim to maximize the number of served IoT devices by jointly optimizing bandwidth, power allocation, and the UAV trajectory while satisfying each device's requirement and the UAV's limited storage capacity.