alexa Blind Adaptive Cyclo-Stationarity Algorithm for Detecti
ISSN: 2320-2459

Research & Reviews: Journal of Pure and Applied Physics
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Research Article

Blind Adaptive Cyclo-Stationarity Algorithm for Detection of Signal with Gaussian Interference

Somayeh Nuri*

 Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran

*Corresponding Author:
Somayeh Nuri
Department of Electrical Engineering, Mahabad Branch, Islamic Azad University, Mahabad, Iran
E-mail: [email protected]

Received date: 21/11/2012 Revised date: 15/12/2012 Accepted date: 27/12/2012




Despite the generally accepted use of the LSCMA, few analytical results on its convergence have appeared in the open literature. The performance of the algorithm has instead been demonstrated through Monte Carlo simulation. The lack of analytical results is due to the difficulty of analyzing the non-linear CMA cost function. Existing work on the convergence behavior of CMA mostly deals with finding minima of the CMA cost function and finding undesirable stable equilibrium in equalization applications. We next examine an environment containing two complex sinusoids, and show that the LSCMA output SIR can be predicted for each iteration. It is shown that the average behavior of the LSCMA in this environment is similar to the deterministic behavior in the two-sinusoid environment. Finally, an environment containing a CM desired signal and Gaussian interference is examined


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