M. Mahdi Azari , Atefeh Hajijamali Arani, Fernando Rosas
Abstract—A cellular-connected unmanned aerial vehicle (UAV) faces several key challenges concerning connectivity and energy efficiency. Through a learning-based strategy, we propose a general novel multi-armed bandit (MAB) algorithm to reduce disconnectivity time, handover rate, and energy consumption of UAV by taking into account its time of task completion. By formulating the problem as a function of UAV’s velocity, we show how each of these performance...
Session: TS PHY-FUN 08: UAV and Vehicular communications 'Learning in the Sky: Towards Efficient 3D Placement of UAVs' | Atefeh Hajijamali Arani; M. Mahdi Azari; William Melek; Safieddin Safavi Naeini
Atefeh Hajijamali Arani, M. Mahdi Azari, William Melek, and Safieddin Safavi-Naeini
Abstract—Deployment of unmanned aerial vehicles (UAVs) as aerial base stations to support cellular networks can deliver a fast and flexible solution for serving high and varying traffic demand. In order to adequately leverage the benefit of UAVs deployment, their efficient placement is of utmost importance, and requires to intelligently adapt to the environment changes. In this paper, we propose novel learning-based mechanisms...