Proactive Channel Assignment and Modified CR-AODV for Stability-Driven Multi-hop Routing in Cognitive Radio Networks

Abstract

Cognitive Radio Networks (CRNs) allow efficient spectrum usage by allowing Secondary Users (SUs) to exploit underused frequency bands allocated to a Primary User (PU). Current channel assignment techniques only document real-time channel availability without knowledge of future activity or channel availability warnings. This work proposes a proactive channel allocation framework for SU to predict long-term stability based upon route reliability. The framework simulates the activities of PU by using the logistic map to model non-linear, time-varying PU behavior. The bifurcation theory is used to determine the threshold point at which channel behavior begins to become chaotic. Then, a modified Cognitive Radio Ad hoc On-Demand Distance Vector (AODV) routing protocol is incorporated that allows possible links in route discovery to be restricted to stable channels. Our simulation results show that the framework improves channel allocation and routing efficiency, ensuring energy-efficient and reliable communication in dynamic CRN environments.