Aerial Video Streaming Over 3D Cellular Networks: An Environment and Channel Knowledge Map Approach

Aerial video streaming is a promising application of unmanned aerial vehicles (UAVs), which extends video service from ground to three-dimensional (3D) airspaces. However, high data rates and smooth transmission are required along with ubiquitous and environment-aware communications. To this end, we study the quality of experience (QoE) maximization problem in this paper for aerial video streaming over 3D cellular networks in urban environments with building avoidance. Different from the typical channel model based optimization in prior works, we tackle the joint design of 3D UAV trajectory and transmission scheduling as well as playback rate adaption with an environment and channel knowledge map (ECKM) approach, which provides rich information about the location-specific channel for enabling environment-aware communications. Specifically, we first consider the scenario with perfect ECKM, and propose efficient algorithms to obtain suboptimal solutions by utilizing two graph models and the iterative parameter-enabled block coordinate descent method. For the scenario without such map information, we propose a dueling Deep Q-learning (DQL) solution with map construction such that the learning process can be facilitated for path planning. Simulation results are provided to demonstrate the improvement in QoE by the proposed solutions over baseline schemes, as well as a tradeoff between video quality and rate variation.