Spectrum Sensing Techniques Based on Last Status Change Point Estimation for Dynamic Primary User in Additive Laplacian Noise
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-021-08984-1.pdf
Reference21 articles.
1. Yang, L., Fang, J., Duan, H., & Li, H. (2020). Fast compressed power spectrum estimation: toward a practical solution for wideband spectrum sensing. IEEE Trans. Wirel. Commun., 19(1), 520–532.
2. Liu, M., Zhao, N., Li, J., & Leung, V. C. M. (2019). Spectrum sensing based on maximum generalized correntropy under symmetric alpha stable noise. IEEE Trans. Veh. Technol., 68(10), 10262–10266.
3. Hu, F., Chen, B., & Zhu, K. (2018). Full spectrum sharing in cognitive radio networks toward 5g: a survey. IEEE Access, 6, 15754–15776.
4. Venkateshkumar, U., & Ramakrishnan, S. (2020). Detection of spectrum hole from n-number of primary users using machine learning algorithms. J. Eng., 2020(5), 175–188.
5. MacDonald, S., Popescu, D. C., & Popescu, O. (2017). Analyzing the performance of spectrum sensing in cognitive radio systems with dynamic pu activity. IEEE Commun. Lett., 21(9), 2037–2040.
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