Distributed Spectrum Sensing for Cognitive Radio Systems

Abstract

Cognitive radio is a candidate technology for more efficient spectrum utilization systems based on opportunistic spectrum sharing. Because this new technology does not rely on traditional license-based spectrum allocation policies, it could disrupt existing systems if the spectrum utilization decision is based on unreliable spectral estimation. Distributed sensing methods have the potential to increase the spectral estimation reliability and decrease the probability of interference of cognitive radios to existing radio systems. In this paper, we consider different aspects of the processing and fusion of spectrum sensing information of cognitive radio systems. The use of cyclic feature- based methods for distributed signal detection and classification is discussed and recent results are presented.