Coverage Probability and Throughput Optimization in Integrated mmWave and Sub-6 GHz Multi-UAV-Assisted Disaster Relief Networks

In the disaster-hit areas where ground network infrastructure has been severely damaged, one challenging problem for multi-UAV-assisted disaster relief networks is how to improve the coverage probability of each UAV. On the basis of solving this problem, the second challenging problem is how to design a channel and power-beam allocation scheme to optimize system throughput while meeting spectrum-energy efficiency constraint. In this paper, we first propose a new method for measuring single UAV coverage quality, which considers both the ratio of effective coverage time to single loop flight time and that of the ground terminals with effective coverage time to the total ground terminals. Then, we develop a set of new algorithms to take advantage of the uneven distribution of ground terminals, which can achieve the total coverage probability improvement and the reduction of deployment costs of UAVs. Finally, we formulate the second problem as Markov decision process (MDP) and develop a solution based on deep deterministic policy gradient (DDPG). Simulation results demonstrate the validity and superiority of our proposed solutions compared with other benchmark strategies in different perspectives.