A novel scheme for performing wireless distributed computing with strip spectral correlation algorithm

Various techniques are introduced for cognitive radio (CR) technology to perform on the spectrum sensing. The most important factor to distinguish between these techniques is the accuracy. However, computational complexity, consumed power and sensing duration are increasing proportionally with the higher accuracy rate. Cyclostationary feature detection is one of those accurate and computationally taxing approaches. To the best of our knowledge, this paper can be considered as the first research for applying wireless distributed computing (WDC) with spectrum sensing which introduces a novel technique to reduce the complexity of one of the practical methods used in cyclostationary feature detection i.e. the strip spectral correlation algorithm (SSCA) by performing WDC. First, the paper demonstrates the capability of distributing the workload for computing the spectral correlation function (SCF) between the cooperative CRs. Second, it discusses the channel effect on the reliability of SCF.