DYNAMIC SPECTRUM ALLOCATION IN COGNITIVE RADIO NETWORKS FOR IoT DEVICES USING FUZZY LOGIC

This research centers on the implementation of fuzzy logic for dynamic spectrum allocation (DSA) within cognitive radio networks (CRNs), specifically tailored for Internet of Things (IoT) applications. The ever-growing number of IoT devices and the limited availability of spectrum resources necessitate sophisticated and efficient spectrum allocation methods. Cognitive radio technology facilitates unlicensed secondary users in accessing underutilized spectrum bands, and DSA enables the dynamic assignment of spectrum resources based on demand and availability. Leveraging the capabilities of fuzzy logic, renowned for handling uncertainty and imprecise data, the system intelligently makes decisions concerning spectrum allocation, taking into account factors like signal strength, interference, user priority, and channel conditions. The outcomes demonstrate that the proposed Fuzzy Logic-based approach adeptly balances channel availability and interference levels, resulting in a substantial enhancement in Quality of Service (QoS) satisfaction. The QoS satisfaction percentage is computed over the simulation period, offering insights into the overall performance of the system. The simulation results are visually presented through a time-dependent spectrum allocation matrix, providing a lucid representation of how the system adapts to varying conditions. This study and its findings underscore the significance of adaptive and intelligent systems in optimizing spectrum usage, especially in the context of emerging IoT applications

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