Journal
IEEE ACCESS
Volume 7, Issue -, Pages 180532-180543Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2958328
Keywords
Intelligent UAV swarm; anti-jamming communication; multi-parameter joint programming; antenna pattern; motion cost
Categories
Funding
- National Natural Science Foundation of China [91648204, 61601486]
- Research Programs of National University of Defense Technology [ZDYYJCYJ140601]
- State Key Laboratory of High Performance Computing Project Fund [1502-02]
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Intelligent unmanned aerial vehicle (UAV) swarm may accomplish complex tasks through cooperation, relying on inter-UAV communications. This paper aims to improve the communication performance of intelligent UAV swarm system in the presence of jamming, by multi-parameter programming and reinforcement learning. This paper considers a communication system, where the communication between a UAV swarm and the base station is jammed by multiple interferers. Compared with the existing work, the UAVs in the system can exploit degree-of-freedom in frequency, motion and antenna spatial domain to optimize the communication quality in the receiving area. This paper proposes a modified Q-Learning algorithm based on multi-parameter programming, where a cost is introduced to strike a balance between the motion and communication performance of the UAVs. The simulation results show the effectiveness of the algorithm.
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