Cyclostationary spectrum sensing algorithm for maritime VHF radio system

• Published in: 2024 IEEE 6th International Conference on Civil Aviation Safety and Information Technology (ICCASIT) pp. 749 - 753
• Main Authors: Zhang, Qing, Mu, Rui, Zhao, Chensong, Hu, Qing
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23.10.2024
• Subjects: Classification algorithms; cyclostationary; Cyclostationary process; Entropy; factorization machine; Feature extraction; Frequency modulation; Gini coefficient; Machine learning algorithms; Multipath channels; Safety; Sensors; Signal to noise ratio; spectrum sensing
• DOI: 10.1109/ICCASIT62299.2024.10828106

In the development of maritime VHF digital communication, the access contention caused by analog voice and digital voice radio working in the same frequency range is a challenge. For this problem, spectrum sensing is an effective technique. However, the self-correlation characteristics of the received signal can be severely affected by the maritime multipath channel, which can make cyclostationary spectrum sensing perform poorly. In this paper, a novel cyclostationary spectrum sensing algorithm for maritime VHF radio system is proposed. The algorithm calculates the cyclic spectral density (CSD) of the received signal, extracts the features of CSD based on the priori information of the modulation bandwidth and carrier frequency, and accomplish spectrum sensing through the classifier based on factorization machine (FM). The simulation based on the maritime multipath channel scenario illustrates that the proposed algorithm has excellent detection performance compared with traditional algorithms.