AI-Based RF Signal Classification and Direction Estimation Using SDR: A Comprehensive Survey

Author(s)	Ms. Namratha V, Mr. Harrsha R, Mr. Jathin M, Mr. Praneeth N, Nivedita Desai
Country	India
Abstract	Recent advances in Software Defined Radio (SDR), Artificial Intelligence (AI), Machine Learning (ML), and Digital Signal Processing (DSP) have enhanced intelligent RF monitoring systems. This paper presents a comprehensive survey of AI-based RF signal classification, spectrum sensing, direction estimation, RF interference detection, and intelligent SDR systems. It reviews traditional and deep learning techniques, including CNN, LSTM, and hybrid CNN-LSTM models, along with SDR-based implementations. The paper also discusses challenges such as low SNR, computational complexity, dataset dependency, hardware constraints, synchronization issues, and environmental noise. Future directions including Edge AI, TinyML, and integrated intelligent SDR systems are also discussed.
Keywords	Software Defined Radio (SDR), RF Signal Classification, Direction of Arrival (DoA), Artificial Intelligence, Machine Learning, Spectrum Sensing, Deep Learning, RF Monitoring
Field	Engineering
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-10-18

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