مشخصات پژوهش

عنوان	Intelligent Cellular Offloading with VLC-enabled Unmanned Aerial Vehicles
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	Unmanned aerial vehicle, visible light communication, deep reinforcement learning, joint EE-SE tradeoff, resource efficiency optimization, cellular offloading
چکیده	This paper discusses a cellular network assisted by an energy-and spectral-efficient unmanned aerial vehicle (UAV), in which the UAV is deployed to serve mobile users in the cellular network and enable mobile data offloading from a ground base station (GBS) by taking a circular flight route. We explore a visible light communication (VLC)-enabled UAV, in which a light-emitting diode (LED) is mounted on a rotary-wing UAV to offer communications to the users. Our aim is to simultaneously optimize both energy efficiency (EE) and spectral efficiency (SE) of the VLC-enabled UAV by jointly optimizing the common throughput of all users as well as the UAV’s trajectory and flying speed. We employ a unified metric, called resource efficiency (RE), and explore the RE optimization to obtain an adaptive EE-SE tradeoff. The problem posed is seen in a complex and non-convex shape, making it hard to solve. Motivated by the enormous achievement of deep reinforcement learning (DRL) in solving complex control problems, we propose a DRL-based approach to handle this non-convex and complicated optimization. The findings of the simulation reveal that the developed framework achieves a substantial performance in terms of the solution convergence as well as the promising quality of the solutions.
پژوهشگران	تومواکی اوتسوکی (نفر سوم)، فرزاد حسین پناهی (نفر دوم)، فریدون حسین پناهی (نفر اول)