Intelligent dynamic spectrum access using fuzzy logic in cognitive radio networks

Abstract

Cognitive radio networks have emerged as a promising solution to the growing problem of spectrum scarcity and inefficient spectrum utilization. By enabling secondary users to opportunistically access underutilized frequency bands while avoiding harmful interference to primary users, cognitive radio networks offer the potential for more efficient and dynamic spectrum allocation. In this paper, we propose an intelligent approach to dynamic spectrum access using fuzzy logic in cognitive radio networks. The key challenge in cognitive radio networks lies in spectrum sensing, decision-making, and channel selection, where uncertainties and variations in the radio frequency spectrum are prevalent. To address these challenges, we employ fuzzy logic as a powerful tool to handle the inherent imprecision and ambiguity in the decision-making process. Fuzzy-based spectrum sensing algorithms allow for robust detection of spectrum opportunities by considering the “fuzziness” in the received signal strength and noise conditions.