Intelligent Radio Signal Processing: A Survey
Quoc-Viet Pham, Nhan Thanh Nguyen, Thien Huynh-The, Long Bao, Le, Kyungchun Lee, Won-Joo Hwang

TL;DR
This survey reviews recent advances in applying artificial intelligence techniques to radio signal processing tasks in wireless communications, highlighting challenges and future research directions.
Contribution
It provides a comprehensive overview of AI-based methods for modulation classification, signal detection, beamforming, and channel estimation in wireless physical layers.
Findings
AI techniques improve signal processing accuracy
Recent studies show enhanced beamforming performance
Identifies key challenges and future research directions
Abstract
Intelligent signal processing for wireless communications is a vital task in modern wireless systems, but it faces new challenges because of network heterogeneity, diverse service requirements, a massive number of connections, and various radio characteristics. Owing to recent advancements in big data and computing technologies, artificial intelligence (AI) has become a useful tool for radio signal processing and has enabled the realization of intelligent radio signal processing. This survey covers four intelligent signal processing topics for the wireless physical layer, including modulation classification, signal detection, beamforming, and channel estimation. In particular, each theme is presented in a dedicated section, starting with the most fundamental principles, followed by a review of up-to-date studies and a summary. To provide the necessary background, we first present a…
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Taxonomy
TopicsWireless Signal Modulation Classification · Radar Systems and Signal Processing · Advanced SAR Imaging Techniques
