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Cherki Daoui
Faculty of Sciences and Techniques

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A Blind Identification and Equalization for MC-CDMA Transmission Channel using a New of Adaptive Filter Algorithm ATIFY Elmostafa; Cherki Daoui; Ahmed BOUMEZZOUGH
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 2: February 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i2.pp352-362

Abstract

A review of literature shows that there are a variety of adaptive filters. In this research study, we propose a new type of adaptive filter that increases the diversification used to compensate the channel distortion effect in the MC-CDMA transmission. First, we show expressions of the impulse responses of the filter in the case of a perfect channel. The adaptive filter  was simulated was experienced by blind equalization for different cases of Gaussian white noise in the case of an MC-CDMA transmission  with orthogonal frequency baseband for mobile radio downlink channel Bran A. Simulation Results  of the proposed model shows the performance of the identification and blind equalization algorithm for MC-CDMA transmission chain using IFFT.
Using A Fuzzy Number Error Correction Approach to Improve Algorithms in Blind Identification Elmostafa ATIFY; Cherki DAOUI; Ahmed BOUMEZZOUGH
Indonesian Journal of Electrical Engineering and Computer Science Vol 3, No 2: August 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v3.i2.pp410-419

Abstract

As part of a detailed study on blind identification of Gaussian channels, the main  purpose was  to propose an algorithm based on cumulants and  fuzzy number approach  involved throughout the whole process of identification. Our objective was to compare the new design of the algorithm to the old one using the  higher order cumulants, namely  Alg1, Algat  and the Giannakis  algorithm. We were  able to demonstrate that the proposed method -fuzzy number error correction- increases the performance of the algorithm by calculating the ratio of squared errors of ALGaT and  AlgatF. The method can be applied to any algorithm for more improvement and effinciency.
Co-Authors Ahmed BOUMEZZOUGH ATIFY Elmostafa Elmostafa ATIFY