Efficient Allocation of Mobile Resources using Fuzzy Systems for a QoS Planning

With mobile data growth and rapid urbanization trends, there will be an extremely high density of wireless communication links in cities, therefore users expect an environment where they can access the Internet to their devices anytime, anywhere. Due to CAPEX/OPEX problems, a small cell deployment is not an economic strategy in scenarios of intense data traffic, so the use of Unmanned Aerial Vehicles (UAVs) to improve network coverage and performance becomes feasible. In order to improve the Quality of Service of the network, a computational system was proposed to perform decision making that receives as input network information such as network throughput, packet loss rate, and delay, and returns the network quality for a specific type of network application. The system as a whole verifies the necessity or not of using UAVs to improve the quality of the network and the coverage of the area of highest demand. If UAVs are required, they are shifted to these areas. Otherwise, the UAVs remain in the base station. Through the proposed method there were significant improvements in the Quality of Service (QoS) of the network, allowing a reduction in packet loss ratio and delay, and an increase in the network throughput rate.