A Robust Routing Protocol in Cognitive Unmanned Aerial Vehicular Networks

The adoption of UAVs in military and civilian sectors necessitates robust communication networks. This paper presents a routing protocol for Cognitive Radio Unmanned Aerial Vehicles (CR-UAVs) in Flying Ad-hoc Networks (FANETs). It optimizes route selection based on various parameters, including distance, speed, link quality, and energy. The protocol introduces the Central Node Resolution Factor (CNRF) for efficient routing decisions and utilizes Received Signal Strength Indicator (RSSI) for distance estimation. Predictive algorithms address high mobility challenges, while link quality assessment prioritizes stability. The protocol enhances security by identifying malicious nodes and manages multiple routes for resilience. Furthermore, the route maintenance feature manages multiple routes and handles link failures. Simulation results demonstrate the protocol's efficiency, comparing it to existing methods in terms of throughput and communication delay.