Design and Performance Analysis of Communication Signal Processing Algorithm Based on Cognitive Radio

This article aims to propose an effective solution to the problem of signal anomaly identification in wireless communication networks. Therefore, a communication signal processing algorithm based on Cognitive Radio (CR) is designed and implemented, and it is optimized with Differential Evolution (DE) algorithm to improve the recognition accuracy and data recovery ability of abnormal signals. The effectiveness and superiority of this method are verified by collecting a large number of wireless communication network signal data for experimental test. The experimental results show that this method can maintain high recognition accuracy and effectively identify and filter out abnormal signals in the network when dealing with a large number of signal data. Furthermore, this method also shows strong ability in error data repair, which can restore the original data more effectively. In addition, the energy efficiency simulation experiment shows that the proposed algorithm has higher detection rate and energy efficiency ratio than the traditional algorithm. Finally, through the signal coverage performance test, the advantages of this method in wireless communication network signal coverage are further verified.