Comparison of Mamdani and Sugeno Inference Systems for Dynamic Spectrum Allocation in Cognitive Radio Networks

Dynamic spectrum access and cognitive radio are emerging technologies to utilize the scarce frequency spectrum in an efficient and opportunistic manner. Cognitive radio, built on software defined radio, is an intelligent radio technology that updates its operating parameters to locate the unused spectrum segments. To assign these vacant bands to unlicensed users without causing harmful interference to licensed users, a novel approach is proposed in this article based on fuzzy logic. Two different fuzzy inference system models i.e. Mamdani and Sugeno systems are developed that compute spectrum access decision based on the secondary user parameters such as signal strength, distance between the primary and secondary user, spectrum utilization efficiency and degree of mobility. 81 fuzzy rules are used to obtain the output of proposed system stating the possibilities of allotment of white spaces to secondary users.