Research On Deep Learning Based End-To-End Wireless Communication System Technology

As an important part of AI, deep learning is widely used in image classification and speech recognition. In particular, the application of deep neural networks with powerful digital signal processing capabilities in communication systems has become a research hotspot in recent years. As a common unsupervised learning model in deep learning, the autoencoder is similar to the traditional wireless communication system and can be used as a design scheme for the physical layer of the wireless communication system. From the perspective of “global optimization” of the wireless communication system, this paper is based on deep learning autoencoder and uses the MATLAB deep learning toolbox to design an end-to-end wireless communication system and conducts simulation under AWGN. The results show that the proposed system is similar to the traditional wireless communication system in terms of performance and has certain “generalization” capability for coding rate, EbNo and other parameters.