Spectrum sensing using Markovian models

Abstract

Markovian models, as well as other statistical models, have been applied in the context of cognitive radio communications to characterize user activity in a given spectrum band and to develop algorithms for temporal spectrum sensing. In this chapter, we discuss spectrum sensing based on Markovian models. We provide an overview of the related literature and then discuss the application of discrete-time Markov chain models to spectrum sensing, in particular the hidden bivariate Markov chain. We focus on the modeling of cognitive radio channels using Markov chains, spectrum detection, and parameter estimation. We then discuss various spectrum sensing scenarios in which the Markovian models are used. Finally, we discuss open problems and topics for further research related to spectrum sensing using Markovian models.