Specifically, the UAV performs as base station (BS) to collect the sensory information of the IoT devices as well as to broadcast energy signals to charge them.

In this section, we will propose a DQN-based reinforcement learning framework, in which the UAV will learn and build knowledge about the IoT networking ...

In this paper, a UAV-assisted wireless powered communication system for IoT network is studied. Specifically, the UAV performs as base station (BS) to ...

We propose an AoI-oriented unmanned aerial vehicle (UAVs)-enabled wireless power transmission scheme, where UAVs are deployed to wirelessly charge IoT devices.

This paper transforms the trajectory optimization problem into a Markov decision process (MDP), and deep reinforcement learning (DRL) is applied to the data ...

Oct 22, 2024 · In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted Internet-of-Things (IoT) system in a sophisticated three-dimensional ...

This paper proposes a deep reinforcement learning-based trajectory planning approach for multi-UAVs that permits UAVs to extract the required information ...

A novel deep reinforcement learning (DRL) technique is proposed, pointer networkA* (Ptr-A*), which can efficiently learn from experiences the UAV trajectory ...

Accordingly, it has been a promising paradigm to use the UAV to provide the edge computing service for massive IoT devices. This paper studies the path planning ...

May 12, 2023 · In this paper, we focus on the joint optimization of UAV trajectory, transmission-scheduling, and access-control strategies in a wireless ...