HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD

TL;DR

HyDRA is a novel hybrid neural network architecture that combines optimized VMD, CNNs, Transformers, and Mamba components to improve device recognition accuracy and robustness in both closed- and open-set wireless scenarios, enabling real-time security applications.

Contribution

This paper introduces HyDRA, a hybrid dual-mode RF architecture integrating optimized VMD with advanced neural modules for enhanced device recognition in wireless security.

Findings

Achieves state-of-the-art accuracy in closed-set device recognition.

Demonstrates robust open-set device identification capabilities.

Operates efficiently on NVIDIA Jetson Xavier NX with low latency.

Abstract

Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Fingerprint Identification (RFFI) offers a non-cryptographic solution by exploiting hardware-induced signal distortions. This paper proposes HyDRA, a Hybrid Dual-mode RF Architecture that integrates an optimized Variational Mode Decomposition (VMD) with a novel architecture based on the fusion of Convolutional Neural Networks (CNNs), Transformers, and Mamba components, designed to support both closed-set and open-set classification tasks. The optimized VMD enhances preprocessing efficiency and classification accuracy by fixing center frequencies and using closed-form solutions. HyDRA employs the Transformer Dynamic Sequence Encoder (TDSE) for global dependency modeling and the Mamba Linear Flow Encoder (MLFE) for linear-complexity processing, adapting to varying conditions. Evaluation on public datasets demonstrates state-of-the-art (SOTA) accuracy in closed-set scenarios and robust performance in our proposed open-set classification method, effectively identifying unauthorized devices. Deployed on NVIDIA Jetson Xavier NX, HyDRA achieves millisecond-level inference speed with low power consumption, providing a practical solution for real-time wireless authentication in real-world environments.