Research on communication signal interference suppression based on deep learning

Abstract

With the development of modern communication technology, people have higher and higher requirements for wireless communication. In practical applications, communication signals are vulnerable to noise and interference signals. Taking effective measures to suppress interference signals can ensure the communication quality. Deep learning technology has strong nonlinear mapping and data expression capabilities, so it can be applied to the field of communication interference suppression. Aiming at the problem that the interference reconstruction algorithm in the traditional interference suppression requires high accuracy of parameter estimation, this paper studies the interference suppression of communication signals combined with the deep learning U-Net network. Through BER simulation analysis, the traditional interference suppression method is compared with the communication signal interference suppression method based on deep learning. The results show that the communication signal interference suppression network based on deep learning can adaptively suppress interference.