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Advances in deep learning-based intelligent receivers
- 1 School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Hebei, China
- 2 School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Hebei, China
* Author to whom correspondence should be addressed.
Abstract
This paper presents a summary of the progress of deep learning in the research of intelligent receivers and predicts its future development direction. First, the background of the era of intelligent receivers is introduced. With the rapid development of communication technology, intelligent receivers show insufficient flexibility, low accuracy, and spectral efficiency in detecting current radio signals. This is a challenge that is difficult to overcome in order to meet the needs of modern signal recovery. With the advent of artificial intelligence technologies such as deep learning, academia and industry began to explore the potential of applying these techniques to the field of communication receivers, leading to the emergence of intelligent receivers. This paper then introduces the fundamentals of wireless communication systems and deep learning neural networks, laying the groundwork for a deeper understanding of the subsequent content. Chapter 3 provides a comprehensive overview of the application of intelligent receivers in signal reception, including channel estimation, signal detection, modulation identification, demodulation and decoding. Finally, the paper considers the practical applications of intelligent receivers and speculates on their future development.
Keywords
wireless communication, intelligent receivers, signal detection, deep learning.
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Cite this article
Hu,J.;Li,M. (2024). Advances in deep learning-based intelligent receivers. Applied and Computational Engineering,95,95-106.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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