Abstract: A joint link-level and network-level intelligent system and method for dynamic spectrum anti-jamming are provided. The system includes a link-level anti-jamming subsystem and a network-level anti-jamming subsystem. The link-level anti-jamming subsystem sets a reward value as system transmission throughput in a single decision cycle, and a user makes an intelligent frequency usage decision based on the obtained reward value to skip a frequency band in which jamming exists. The network-level anti-jamming subsystem performs reasonable frequency band allocation and management for lower-level sub-users when link-level anti-jamming fails to further enhance a frequency domain anti-jamming capability of the entire system. The users make intelligent frequency usage decisions through a dynamic spectrum anti-jamming algorithm based on reinforcement learning to effectively avoid external malicious jamming, realize dynamic spectrum access, and enhance a frequency domain anti-jamming capability of the system.

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.

Abstract: A joint link-level and network-level intelligent system and method for dynamic spectrum anti-jamming are provided. The system includes a link-level anti-jamming subsystem and a network-level anti-jamming subsystem. The link-level anti-jamming subsystem sets a reward value as system transmission throughput in a single decision cycle, and a user makes an intelligent frequency usage decision based on the obtained reward value to skip a frequency band in which jamming exists. The network-level anti-jamming subsystem performs reasonable frequency band allocation and management for lower-level sub-users when link-level anti-jamming fails to further enhance a frequency domain anti-jamming capability of the entire system. The users make intelligent frequency usage decisions through a dynamic spectrum anti-jamming algorithm based on reinforcement learning to effectively avoid external malicious jamming, realize dynamic spectrum access, and enhance a frequency domain anti-jamming capability of the system.