Adaptive Coding and Modulation-Aided Mobile Relaying for Millimeter-Wave Flying Ad-Hoc Networks.

Abstract

The emerging drone swarms are capable of carrying out sophisticated tasks in support of demanding Internet of Things (IoT) applications by synergistically working together. However, the target area may be out of the coverage of the ground station (GS) and it may be impractical to deploy a large number of drones in the target area due to cost, electromagnetic interference, and flight-safety regulations. By exploiting the innate agility and mobility of unmanned aerial vehicles (UAVs), we conceive a mobile relaying-assisted drone swarm network architecture, which is capable of extending the coverage of the GS and enhancing the effective end-to-end throughput. Explicitly, a swarm of drones forms a data-collecting drone swarm (DCDS) designed for sensing and collecting data with the aid of their mounted cameras and/or sensors, and a powerful relay-UAV (RUAV) acts as a mobile relay for conveying data between the DCDS and a GS. Given a time period, in order to maximize the data delivered while minimizing the delay imposed, we harness an ϵ -multiple-objective genetic algorithm ( ϵ -MOGA)-assisted Pareto-optimization scheme. Our simulation results demonstrate that the proposed mobile relaying is capable of delivering more data. As specific examples investigated in our simulations, our mobile relaying-assisted drone swarm network is capable of delivering 45.38% more data than the benchmark solutions, when a stationary relay is available, and it is capable of delivering 26.86% more data than the benchmark solutions when no stationary relay is available.