Abstract
This paper proposes a new physical layer approach for stealthy jammer detection in wide-band (WB) cognitive radio networks. We consider a WB which consists of multiple narrow-band sub-bands (SB), which can be occupied by licit signals or jammer. To alleviate the overhead of analog-to-digital conversion (ADC), compressed sensing is applied first to recover the WB from sub-Nyquist rate samples. Then, cyclostationary spectral analysis is performed on this estimated WB signal to compute spectral correlation function (SCF). The alpha profile is extracted from the SCF and used to classify each NB signal as a licit signal or a jamming signal. In the end, the performance of the proposed approach is shown with the help of Monte-Carlo simulations under different empirical setups.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
