Abstract: An unmanned aerial vehicle (UAV) task cooperation method based on an overlapping coalition formation (OCF) game includes: constructing a sequential OCF game model for a UAV multi-task cooperation problem; using a bilateral mutual benefit transfer (BMBT) order that is biased toward the utility of a whole coalition to evaluate a preference of a UAV for a coalitional structure; optimizing task resource allocation of the UAV under an overlapping coalitional structure by using a preference gravity-guided Tabu Search algorithm to form a stable coalitional structure; and optimizing a transmission strategy based on the current coalitional structure, an updated status of a task resource allocation scheme of the UAV, and a current fading environment, so as to maximize task execution utility of a UAV network. The method quantifies characteristics of resource properties of the UAV and a task, and optimizes the task resource allocation of the UAV under the overlapping coalitional structure.

Abstract: An unmanned aerial vehicle (UAV) task cooperation method based on an overlapping coalition formation (OCF) game includes: constructing a sequential OCF game model for a UAV multi-task cooperation problem; using a bilateral mutual benefit transfer (BMBT) order that is biased toward the utility of a whole coalition to evaluate a preference of a UAV for a coalitional structure; optimizing task resource allocation of the UAV under an overlapping coalitional structure by using a preference gravity-guided Tabu Search algorithm to form a stable coalitional structure; and optimizing a transmission strategy based on the current coalitional structure, an updated status of a task resource allocation scheme of the UAV, and a current fading environment, so as to maximize task execution utility of a UAV network. The method quantifies characteristics of resource properties of the UAV and a task, and optimizes the task resource allocation of the UAV under the overlapping coalitional structure.