Evolutionary Hypernetworks based Radio Spectrum Profiling in Cognitive Radio Ad hoc Networks

Abstract

In this paper we present a novel idea of evolutionary hypernetworks based radio spectrum profiling for Cognitive Radio (CR) ad hoc networks. Spectrum profiling enables CR nodes to abstract and predict secondary channel access opportunities from primitive spectrum sensing data. The abstracted information can be used for channel characterization which facilitates better channel selection and mobility in CR nodes. We use Evolutionary Hypernetworks for realizing the proposed concept which can also be viewed as a distributed network support architecture. We present the main concepts, their application to CR ad hoc networks, and an analysis of its impact on overall network performance. The results indicate that hypernetwork based radio spectrum profiling achieves considerable performance advantages over existing approaches.