Cognitive radio is an emerging wireless technology that is capable of coordinating efficiently the use of the currently scarce spectrum resources and spectrum sensing constitutes its most crucial operation. The present work proposes wideband multichannel spectrum sensing methods utilizing fast Fourier transform or filter bank based methods for spectrum analysis. Fine-grained spectrum analysis facilitates optimal energy detection in practical scenarios where the transmitted signal, channel frequency response, and/or receiver frequency response do not follow the commonly assumed boxcar model which typically assumes, among others, narrowband communications with flat spectral characteristics. Such sensing schemes can be tuned to the spectral characteristics of the target primary user signals, allowing simultaneous sensing of multiple target primary signals with low additional complexity. This model is also extended for accounting for the specific scenario of detecting a reappearing primary user during secondary transmission, as well as in spectrum sensing scenarios where the frequency range of a primary user is unknown. Novel analytic expressions are derived for the corresponding probability of false alarm and probability of detection in each case while the useful concept of the area under the receiver operating characteristics curve is additionally introduced as a single scalar metric for evaluating the overall performance of the proposed spectrum sensing algorithms and scenarios. The derived expressions have a rather simple algebraic representation which renders them convenient to handle both analytically and numerically. The offered results are also validated extensively through comparisons with respective results from computer simulations and are subsequently employed in evaluating each technique analytically which provides meaningful insights that are anticipated to be useful in future deployments of cognitive radio systems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.