A game theoretic approach of deployment a multiple UAVs for optimal coverage

In this paper, a game-theoretical autonomous decision-making approach for efficient deployment of unmanned aerial vehicles (UAVs) in a multi-level and multi-dimensional assisted network is analyzed. The UAVs have directional antennas that work as wireless stations, which provide the best coverage for multiple ground mobile/fixed users. In general, UAVs work in a cooperative manner for achieving the suitable deployment with the optimal coverage values for the candidate region. In this paper, a game theory concept is used and the payoff function for each UAV is defined based on the coverage probability value, which depends on the altitude and the characteristic of antennas in the UAVs. We introduce a mathematical formulation for evaluating the payoff values based on a set of actions for each UAV, and the Nash equilibrium for this kind of game. This approach works in an intelligent way based on the interactions between the UAVs and their neighbors in a connected network and it might work even in harsh environments. In order to minimize interference, the UAVs' altitudes are adjusted based on the antennas and other deployment requirements (i.e. search and surveillance purposes) by using the minimum number of UAVs to cover the candidate geographical region. The simulation results show that the proposed approach achieves the maximum coverage value, converges fast with the environmental changes based on the power levels, and robust for failure scenarios. Finally, we compare our approach against one of the traditional approaches called Collaborative Visual Area Coverage Approach (CVACA) based on uniform coverage quality. The simulation results show that the game approach outperforms the traditional approach in term of the coverage value and the computational time.