Integrating Fuzzy Logic into Cognitive Radio Systems

Authors

  • Zainab Riyadh Shaker Al_Yasiri Department of Mathematics and Computer Applications, College of Science, Al-Nahrain University, Jadiriya, Baghdad, Iraq .

DOI:

https://doi.org/10.22401/ANJS.29.2.12

Keywords:

Fuzzy sets, Triangular Model, Cognitive Radio, Fuzzy Logic System, Optimization, MATLAB

Abstract

This paper presents a mathematical formulation and implementation framework of Fuzzy Logic Controllers in cognitive radio operations. The approach is rooted in fuzzy set theory, enabling linguistic rule-based decision-making for spectrum sensing, power control, and channel selection. In Cognitive Radio Networks, a primary difficulty is determining how Cognitive Radio may utilize a licensed channel without disrupting Primary Users and when to relinquish that channel. In this work, we define a fuzzy logic model that manages the operation of Cognitive Radio to prevent interference with Primary Users. Our proposed model does not just decide the handover according to the Primary Users power but also on the performance of the Secondary User and achievement of quality of service on both Primary Users and Secondary User.

References

[1] Goldsmith, A.; Jafar, S.A.; Maric, I.; Srinivasa, S.; "Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective". Proc. IEEE, 97(5): 894–914, 2009. https://doi.org/10.1109/JPROC.2009.2015717.

[2] Zadeh, L.A.; "Fuzzy Sets". Inf. Control, 8(3): 338–353, 1965. https://doi.org/10.1016/S0019-9958(65)90241-X.

[3] Okeke, R.O.; Ezeofor, C.J.; "Dynamic Spectrum Allocation in Cognitive Radio Networks for IoT Devices Using Fuzzy Logic". Adv. J. Sci. Eng. Technol., 9(3): 1–14, 2024.

https://aspjournals.net/ajset/index.php/ajset/article/view/76.

[4] Riskiono, S.D.; Sulistiyo, S.; Mustika, I.W.; "Intelligent Spectrum Handoff Decision in Cognitive Radio Networks: A Fuzzy System Approach with Adaptive Membership Functions". J. Commun., 19(9): 411–418, 2024.

[5] Fraz, M.; Alam, M.M.; Hussain, M.; Amin, R.; Xie, J.; "Smart Sensing Enabled Dynamic Spectrum Management for Cognitive Radio Networks". Front. Comp. Sci., 5: 1271899, 2023. https://doi.org/10.3389/fcomp.2023.1271899.

[6] Lone, M.A.; Mir, S.A.; Kumar, S.; Rather, A.A.; Qayoom, D.; Ramki, S.; "Application of Fuzzy Logic in Agricultural Network Analysis for Optimizing Crop Production". Reliab. Theory Appl., 20(1): 363–372, 2025.

[7] Giupponi, L.; Pérez-Neira, A.I.; "Fuzzy-Based Spectrum Handoff in Cognitive Radio Networks". In: Proc. 3rd Int. Conf. Cogn. Radio Oriented Wirel. Netw. Commun. (CROWNCOM), Singapore, 15–17 May; IEEE: Piscataway, NJ, USA, 1–6, 2008.

https://hdl.handle.net/2117/9122.

[8] Cabric, D.; Mishra, S.M.; Willkomm, D.; Brodersen, R.; Wolisz, A.; "A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum". In: Proceedings of the 14th IST Mobile and Wireless Communications Summit, Dresden, Germany, 19–23 June 2005; Herhold, P.; Schlager, R.; Eds.; Technische Universität Dresden: Dresden, Germany, 2005.

[9] Vasant, P.; Kale, H.S.; "Introduction to Fuzzy Logic and Fuzzy Linear Programming". In Encyclopedia of Decision Making and Decision Support Technologies, 1st ed.; Adam, F.; Humphreys, P.; Eds.; IGI Global: Hershey, PA, USA, 539–553, 2008.

https://doi.org/10.4018/978-1-59904-843-7.ch060.

[10] Ahmed, E.; Gani, A.; Abolfazli, S.; Yao, L.J.; Khan, S.U.; "Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges". IEEE Comm. Sur. Tutor., 18(1): 795–823, 2016.

https://www.researchgate.net/publication/266855775.

[11] Lee, C.C.; "Fuzzy Logic in Control Systems: Fuzzy Logic Controller—Part I & II". IEEE Trans. Syst. Man Cybern., 20(2): 404–435, 1990.

[12] Tanaka, K.; Wang, H.O.; "Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach". 1st ed.; John Wiley & Sons: Hoboken, NJ, USA, 2001.

https://doi.org/10.1002/0471224596.

[13] Mitola, J.; Maguire, G.Q. Jr.; "Cognitive Radio: Making Software Radios More Personal". IEEE Pers. Commun., 6(4): 13–18, 1999.

https://www.academia.edu/2489582.

[14] Kosko, B.; "Neural Networks and Fuzzy Systems: A Dynamical Systems Approach". 1st ed.; Prentice Hall: Englewood Cliffs, NJ, USA, 1992.

[15] Haykin, S.; "Cognitive Radio: Brain-Empowered Wireless Communications". IEEE J. Sel. Areas Commun., 23(2): 201–220, 2005. https://doi.org/10.1109/JSAC.2004.839380.

[16] Wild, B.; Ramchandran, K.; "Detecting Primary Receivers for Cognitive Radio Applications". In: Proceedings of the IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD, USA, 8–11 November 2005; Kolodzy, P.; Bahl, V.; Eds.; IEEE: New York, USA, 2005.

https://doi.org/10.1109/DYSPAN.2005.1542626.

[17] Hoven, N.; Sahai, A.; "Power Scaling for Cognitive Radio". In: Proceedings of the IEEE International Conference on Wireless Networks, Communications and Mobile Computing (WirelessCom), Maui, HI, USA, 13–16 June 2005; Guizani, M.; Ed.; IEEE: New York, USA, Vol. 1, 250–255, 2005.

https://ieeexplore.ieee.org/document/1549418.

Downloads

Published

2026-06-15

Issue

Section

Articles

How to Cite

(1)
Riyadh Shaker Al_Yasiri, Z. . Integrating Fuzzy Logic into Cognitive Radio Systems. Al-Nahrain J. Sci. 2026, 29 (2), 147-156. https://doi.org/10.22401/ANJS.29.2.12.