Coverage Area Maximization for Multiple UAVs Using Co-Operative Game Theory
| International Journal of Electronics and Communication Engineering |
| © 2025 by SSRG - IJECE Journal |
| Volume 12 Issue 10 |
| Year of Publication : 2025 |
| Authors : Indu, Rishipal Singh |
10.14445/23488549/IJECE-V12I10P104
How to Cite?
Indu, Rishipal Singh, "Coverage Area Maximization for Multiple UAVs Using Co-Operative Game Theory," SSRG International Journal of Electronics and Communication Engineering, vol. 12, no. 10, pp. 27-38, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I10P104
Abstract:
Unmanned Aerial Vehicles (UAVs) have been gaining popularity with their distinctive features. A multi-UAV network has an advantage over a single UAV, and they can co-operatively accomplish a complex task. Ensuring full coverage of the communication area with the least possible UAV deployment is still underexplored. Non-game theoretic approaches focus on centralized solutions and require constant communication, which is difficult in high mobile UAV communication. Deployment of UAVs in a particular area leads to an increase in interference and therefore reduces network performance. Therefore, in this paper, with the objective of coverage area maximization, a co-operative game theory has been proposed for a multi-UAV scenario in communication with Ground Users (GU). A radio frequency propagation model has been adopted for coverage probability calculation. A Spatial Adaptive Play (SAP) driven algorithm has been formulated for the convergence of the potential game approach to select the game action for the next state. Interference has been mitigated by using the relative distance criterion among UAVs. Nash equilibrium has been proved, and it has been shown that convergence has been reached. Each UAV, according to the co-operative game scenario, tries to maximize utility/payoff. Simulation results demonstrate that the proposed game theory approach is both reliable and effective.
Keywords:
Co-operative Game Theory, Coverage Maximization, Nash Equilibrium, Potential Games, Unmanned Aerial Vehicle.
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