Spectrum-Aware Routing for Reliable End-to-End Communications in Cognitive Sensor Network

Sensor nodes in Cognitive Sensor Networks (CSNs) can work on different frequency bands (or channels) according to dynamically available wireless resources. This paper proposes a spectrum-aware routing scheme for CSNs, which jointly considers traffic balance, route configuration and power control for reliable end-to-end communications. Bayesian learning method is used to estimate the number of neighboring Primary Users (PUs) and Secondary Users (SUs). The estimated results effectively reflect the spectrum utilization and provide important information for route configuration. Multiple Attribute Decision Making (MADM) method is employed to combine the routing objectives of reliability, energy efficiency and path delay into a single target function. Randomized route selection strategy is adopted for traffic balance. The simulation results demonstrate that the proposed spectrum-aware routing scheme significantly improves the communication reliability, and simultaneously has satisfying performances in energy efficiency and end-to-end delay.