Optimized MAC Protocol Using Fuzzy-Based Framework for Cognitive Radio AdHoc Networks

Cognitive radio networks (CRNs) have been widely used in various applications for effective spectrum utilization recent years. It is essential to fend off the growing demand this finite natural resource next-generation communications. In CRNs, detecting activity of primary user requires opportunistic sensing efficient usage available spectrum, which a limited and exquisite resource. Thus, CRNs are key component solving scarcity issue presence bands through secondary users. AdHoc (CRAHNs) unique kind where infrastructures less cognitive (CR) nodes furnished. CRAHN, CR-MAC protocol works slightly differently from traditional wireless network MAC protocols. Particularly, proposed method includes high traffic scenario under contention-based IEEE 802.11 DCF protocol. Accordingly, it can be observed that both, throughput delay, increase as CW size packet length (DCF) CRAHN varies. Therefore, paper fuzzy-based optimization framework CRAHNs. Furthermore, optimized delay by training database input parameters, contention window, Mamdani Sugeno fuzzy inference system (FIS) models simultaneously. The experimental result with FIS shows altering window increases 25% reduces 38% compared IEEE802.11 CRAHNs without FIS. Moreover, also revealed increased 7% reduced 40% 50% due length.