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Research on UAV Anti-Multi-type Interferences Strategy Based on Improved Q-Learning

UAVs have been widely used in military and civilian applications, and they play a huge role in many aspects. However, due to the open nature of the UAV communication link, it is susceptible to malicious or unintentional interference. Besides, the interference that UAVs are facing has developed from a single type of interference to multi-type interference. The traditional anti-interference method is designed to deal with single-dimensional interference and cannot meet the requirements of anti-Multi-type interference. The purpose of the paper is to improve the communication capabilities of UAVs by programming frequency-power (Change the transmission frequency and transmission power of the UAV)in Multi-type interference environment. Compared with the existing work, the UAVs in the system can exploit degree-of-freedom in frequency, power to optimize the communication quality in the receiving area and reduce energy costs. The paper propose a Anti-multi-type interference strategy based on improved and eligibility traces Q-learning algorithm, which is based on multi-parameters, and the simulation results show the effectiveness of the algorithm.