Communication capacity maximization in drone swarms

Employment of unmanned aerial vehicles (UAVs) or drones as swarms coordinating nodes offers multiple advantages for commercial well military applications. However, the complex communication requirements these swarms, coupled with high data rates advanced UAV payloads, require innovative techniques optimizing throughput. Channel capacity being key resource, optimum architecture and network topology is critical to ensure quality service while remaining within transmission power constraints. This paper proposes a maximization approach swarm architectures using mixed-integer nonlinear programming (MINLP). These are designed tackle optimization applications involving both discrete variables system dynamics. Mathematical model formulated considering constraints desired objective function establishes applicability MINLP. Since MINLP problems NP-hard in general, computational overheads search space exponentially grow number swarm. Therefore, outer approximation algorithm has been applied that achieves near-optimal solutions reduced convergence time complexity compared exhaustive search. Applicability regardless selected established through realistic simulations.