The UAVs and base stations are to serve mobile users in multiple continuous time slots, and machine learning is leveraged to facilitate joint resource ...
We thus propose a deep reinforcement learning algorithm to solve this problem by considering UAV path planning, user assignment, bandwidth and computing ...
UAV-aided MEC has been used to improve the performance of MEC, which has high mobility, high maneuverability and flexibility of deployment. ▫ 6G will bring a ...
A Spiking Neural Network (SNN)-based computing framework is proposed, which exploits sparsity in disturbances and promotes local event driven operation for ...
The UAVs and base stations are to serve mobile users in multiple continuous time slots, and machine learning is leveraged to facilitate joint resource ...
Apr 10, 2022 · The UAVs and base stations are to serve mobile users in multiple continuous time slots, and machine learning is leveraged to facilitate joint ...
We demonstrate that the deep reinforcement learning algorithms perform better than all baseline cases. Index Terms—Machine learning, unmanned aerial vehicle. ( ...
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The main aim of this proposed book chapter is to exploit algorithms that can provide optimal deployment and path-planning solutions for UAVs based on machine ...
Aug 20, 2024 · We propose a novel IRS-and-unmanned aerial vehicle (UAV)-Assisted mobile edge computing (MEC) framework, where a MEC server installing on an UAV to facilitate ...
Dec 15, 2022 · We demonstrate that the deep reinforcement learning algorithms perform better than all baseline cases. AB - Unmanned aerial vehicles (UAVs) are ...