In the near future, unmanned aerial vehicles (UAVs)
will have enormous potential applications for next-generation
wireless communication systems, in which they can collaborate to
serve several user equipment (UE) for communication purposes.
Disaster scenarios are a relevant research topic, in which UAVs
can aid establishing connections in circumstances where base
stations (BS) may be inoperative.
The resulting UAV positioning affects the overall spectral
efficiency (SE) in each UAV-UE link. Moreover, UEs energy
consumption must be optimized since the finite amount of energy
available is one of the most significant limitations of these
devices. Therefore, it is essential to determine the lowest power
consumption necessary to guarantee a minimum SE throughput
in a disaster location.
In this paper, we investigate a cooperative Meta-Heuristic
(MH) optimization algorithm for both the UAVs and UEs. We
propose two parallel optimization approaches: one is the UAV
search position process to find the best possible location to serve
its pre-allocated UEs; the other is finding the lowest possible
uplink (UL) power values for each user’s equipment.
The preliminary results show that the Differential Evolution
(DE) algorithm reaches good quality solutions in acceptable
computation runtime.