Crowd-based positioning of UAVs as Access Points

Unmanned Aerial Vehicles (UAVs) can be a cost saving and easy to deploy solution to implement a temporary network infrastructure. They can act as access points in scenarios such as emergency situations, special events, or specific area monitoring. Two main deployment families can be found in the literature. The first one, the location-based family, is based on the fundamental assumption that the network user positions are known. We do believe that this could not suit the most general scenarios. On the other hand, the location-independent family can not be as efficient as the first one. The main idea in this paper is to introduce a new crowd-based family, based on a probabilistic knowledge of user positions. We then propose a self-deployment method built on a Coulomb's law analogy where users and UAVs act as electrical charges. Short range interactions are implemented through network sensing, while long range ones use a crowd-based approach. Some numerical results are depicted, showing the performance of this self-deploying mechanism as well as a comparison with a well-known clustering algorithm