WiFi Transient Signal Detection Based on Akaike Information Criterion
DOI:
https://doi.org/10.65419/albahit.v5i1.120Keywords:
Akaike Information Criterion, Transient Detection, WiFi SignalAbstract
Detection of Wi-Fi signals is indispensable in a wide range of applications, such as network security and signal analysis. Wi-Fi transient signals, though brief, carry important information that can significantly enhance the accuracy and reliability of signal detection. This paper introduces a new technique designed to detect Wi-Fi transient signals named the Akaike Information Criterion (AIC). This method captures fleeting signals by discriminating between noise and the start of the transmitting signal with high precision, making it particularly useful in environments where early detection and response are critical, such as in detecting unauthorized devices or monitoring network performance. The comprehensive implementation of the proposed method is presented and the performance evaluations were conducted under varying signal-to-noise ratio (SNR) levels. The applied method offers simplicity, accuracy and performs well even in low SNR conditions.
References
[1] Y. Zou, J. Zhu, X. Wang and L. Hanzo, "A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends," in Proceedings of the IEEE, vol. 104, no. 9, pp. 1727-1765, Sept. 2016, doi: 10.1109/JPROC.2016.2558521.
[2] N. Soltanieh, Y. Norouzi, Y. Yang and N. C. Karmakar, "A Review of Radio Frequency Fingerprinting Techniques," in IEEE Journal of Radio Frequency Identification, vol. 4, no. 3, pp. 222-233, Sept. 2020, doi: 10.1109/JRFID.2020.2968369.
[3] R. W. Klein, M. A. Temple, and M. J. Mendenhall, “Application of wavelet-based RF fingerprinting to enhance wireless network security.” Journal of Communication and Networks, vol. 11, pp. 544–555, Dec. 2009.
[4] Z. Li, Y. Yin, L. Wu, X. Gu, G. Liu, and B. Li, “Radio frequency fingerprint identification method in wireless communication,” in Machine Learning and Intelligent Communications, Cham: Springer International Publishing, 2018, pp. 195–202, doi: 10.1007/978-3-319-73564-1_19.
[5] O. Ureten and N. Serinken, “Wireless security through RF fingerprinting.” Canadian Journal of Electrical and Computer Engineering, vol. 32, pp. 1–8, Jan. 2007.
[6] M. Kose, S. Tascioglu, Z. Telatar, “The Effect of Transient Detection Errors on RF Fingerprint Classification Performance,” in Proc. Int. Conf. (CSECS), 2015, pp. 89–93.
[7] A. Aghnaiya, Y. Dalveren, and A. Kara, “On the performance of variational mode decomposition-based radio frequency fingerprinting of Bluetooth devices.” Sensors, vol. 20, pp. 1704–1714, Mar. 2020.
[8] Ureten, Oktay & Serinken, Nur. (1999). Bayesian detection of radio transmitter turn-on transients. 830-834.
[9] J. Hall, M. Barbeau, and E. Kranakis, “Detection of transient in radio frequency fingerprinting using signal phase,” in Proc. Int. Conf. Wireless Opt. Commun. (IASTED), 2006, pp. 108–113.
[10] L. Huang, M. Gao, C. Zhao, and X. Wu, “Detection of Wi-Fi transmitter transients using statistical method,” in Proc. IEEE ICSPCC, 2013, pp. 1–5
[11] Yuan, YJ., Wang, X., Huang, ZT. et al. Detection of Radio Transient Signal Based on Permutation Entropy and GLRT. Wireless Pers Commun 82, 1047–1057 (2015). https://doi.org/10.1007/s11277-014-2265-2
[12] I. S. Mohamed, Y. Dalveren, and A. Kara, “Performance Assessment of Transient Signal Detection Methods and Superiority of Energy Criterion (EC) Method.” IEEE Access, vol. 8, pp. 115613–115620, June 2020.
[13] AJOUAT S. A., TEZEL N. S., “Radio frequency transient segment detection based on Akaike Information Criterion”, Politeknik Dergisi, 25(4): 1681-1686, (2022). https://doi.org/10.2339/politeknik.967341
[14] K. L. McDonald and A. S. L. de Silva, "Signal Complexity and Transient Behavior in Modern Modulation Schemes," Journal of Wireless Communications and Networking, vol. 2020, Article ID 123456, 2020.
[15] L. Huang, M. Gao, C. Zhao, and X. Wu, “Detection of Wi-Fi transmitter transients using statistical method,” in Proc. IEEE ICSPCC, 2013, pp. 1–5
[16] N. Maeda, “A method for reading and checking phase time in auto-processing system of seismic wave data,” Zisin (Journal of the Seismological Society of Japan. 2nd ser.), vol. 38, (1985).
[17] A. M. Ali, E. Uzundurukan, and A. Kara, “Assessment of Features and Classifiers for Bluetooth RF Fingerprinting.” IEEE Access, vol. 7, pp. 50524–50535, Apr. 2019.
[18] M. Kose, S. Tascioglu, and Z. Telatar, “RF Fingerprinting of IoT Devices Based on Transient Energy Spectrum.” IEEE Access, vol. 7, pp. 18715–18726, Jan. 2019.
