The recent advances in drone technology significantly improved the effectiveness of applications such as border surveillance, disaster management, seismic surveying, and precision agriculture. The use of drones as bas...
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The recent advances in drone technology significantly improved the effectiveness of applications such as border surveillance, disaster management, seismic surveying, and precision agriculture. The use of drones as base stations to improve communication in the next generation wireless networks is another attractive application. However, the deployment of drone base stations (dbss) is not an easy task and requires a carefully designed strategy. fairness is one of the most important metrics of tactical communications or a disaster-affected network and must be considered for the efficient deployment of dbss. In this study, a fairness-aware multiple dbs deployment algorithm is proposed. As the proposed algorithm uses particle swarm optimisation (PSO) that requires significant processing power, simpler algorithms with faster execution times are also proposed and the results are compared. The simulations are performed to evaluate the performance of the algorithms in two different network scenarios. The simulation results show that the proposed PSO-based method finds the three-dimensional locations of dbss, achieving the best fairness performance with a minimum number of dbss for deployment. However, it is shown that the proposed suboptimal algorithm performs very close to the PSO-based solution and requires significantly less processing time.
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