Blind spectrum sensing using symmetry property of cyclic autocorrelation function: from theory to practice

Abstract

Spectrum sensing has been identified as the key step of the cognition cycle and the most important function for the establishment of cognitive radio. In this paper, a blind cyclostationary feature detector, which is based on the symmetry property of cyclic autocorrelation function (SP-CAF), is implemented and tested using universal software radio peripheral platform and GNU Radio open-source software development toolkit. Performance of the SP-CAF is compared to the classical energy detector via various tests conducted in real scenarios where both detection algorithms are employed to blindly sense the spectrum for opportunistic access. This study shows that the blind cyclostationary feature detector outperforms the classical energy detector while guaranteeing acceptable complexity and low sensing time. Moreover, different experimental results indicate that the blind sensing detector can achieve high detection probability at a low false alarm probability under real channel conditions and low signal-to-noise ratio.

Feature Extraction in Local SpectrumSensing for Next Generation CognitiveRadios � A Review

“…It involves the decimation and separation of the signal into fragments on which a Fourier transform is performed to estimate the SCF so that the CD-based sensing can be applied. High-probability detection at low SNR is achieved in [67], where the signal is pre-processed by the compressed sensing method. The test statistic is formed by the symmetry index, which is defined as the average of all cyclic frequencies.…”

A methodology for experimental evaluation of signal detection methods in spectrum sensing

“…For instance, evaluation in [ 26 ] does not document the parameter N ′ of the FAM method used for cyclostationary detection and the number of trials used to obtain probability estimates. In [ 29 ], a cyclostationary detector based on compressive sensing is experimentally evaluated, however signal models used in the evaluation are not presented and confidence estimates of the results are not given.…”

Cyclostationarity: New trends and applications

“…Other ad hoc receivers are presented in [4,22,87,179,181,243,260,263,288,304,326,368,370,375] for communication signals and in [215] for radar signals. Spectrum sensing is performed by exploiting first-order cyclostationarity in [83] and frequency shift filtering in [52].…”