ICC 2021 - IEEE International Conference on Communications | 2021
Online Trajectory and Radio Resource Optimization for Cache-enabled Multi-UAV Networks
Abstract
In this paper, we propose a novel joint trajectory and communication scheduling scheme for multiple unmanned aerial vehicles (UAVs) enabled wireless caching networks. To exploit the favorable propagation of air-to-ground channels and spatial multiplexing gains, we consider an ultra dense UAVs enabled content-centric wireless transmission network, where massive UAVs are deployed to transmit cached contents to a group of random distributed ground users. We formulate this problem as a infinite horizon ergodic stochastic differential game (SDG) for optimizing the users’ quality-of-experience (QoE) on the concept of request queues for cached contents. By means of mean-field game (MFG) analysis, we derive a reduced-complexity control solution. In addition, we further propose a novel model-specific deep neural network (DNN) to learn the PDEs numerically by exploiting a homotopy perturbation method (HPM).