Research on Efficient Signal Processing Algorithm in Long-Distance Broadband Communication of Unmanned Aerial Vehicles

This study aims at the signal processing problem of long-distance broadband communication of unmanned aerial vehicles and proposes an efficient processing solution based on denoising autoencoder algorithm. This paper first analyzes the channel model of broadband communication of unmanned aerial vehicles and designs an adaptive denoising autoencoder algorithm. It accurately extracts the characteristics of target signals through nonlinear mapping and effectively suppresses noise interference. The algorithm combines channel estimation and noise dimension reduction technology to further optimize the transmission quality of the signal. In this paper, communication simulation is used in different SNR conditions to evaluate its performance under complicated communication environment. Simulation results indicate that the proposed denoising algorithm is superior to the SNR. Compared with the conventional method, the SNR is increased by 15%, BER is decreased by 30%, and the communication stability and transfer speed are improved obviously. The results show that the proposed algorithm is effective and practical in UAV long distance broadband communication.