Deep Reinforcement Learning-Based UAV Data Collection and Offloading in NOMA-Enabled Marine IoT Systems

Yanpeng Dai, Ziyi Liang, Ling Lyu, Bin Lin
2022 Wireless Communications and Mobile Computing  
The rapid growth of maritime wireless communication demand and the complex offshore wireless communication environment have brought challenges to ensure the real-time and reliability of data transmission in the marine Internet of Things (MIoT). Unmanned aerial vehicles (UAVs) have great advantages in enhancing coverage and channel quality. Hence, we investigate a UAV-assisted data collection and data offloading system based on nonorthogonal multiple access (NOMA) technology in this paper. We
more » ... ntly optimize the buoy-UAV association relationship, transmit powers, and the UAV trajectory to minimize the total mission completion time while ensuring data transmission requirements. We first propose a UAV trajectory optimization algorithm based on deep reinforcement learning (DRL). Then, we design a heuristic algorithm to effectively solve the subproblem of power control and the association relationship. Finally, we propose a joint optimization scheme to solve the minimization problem. Simulation results show the effectiveness of the proposed scheme.
doi:10.1155/2022/8805416 doaj:c657a694a2ed44238c1849881109d7b2 fatcat:bsr5y3anovhihcmyn76qnbs5bq