Mohamed Sabri

Identification and equalization using higher order cumulants in MC-CDMA systems

In this paper we propose an algorithm based on fourth order cumulants for identification of linear systems with Non Minimum Phase (NMP) excited by independent identically distributed (i.i.d) non-Gaussian sequences. In order to test its efficiency, we consider one practical frequency-selective fading channel, called Broadband Radio Access Network (BRAN E), normalized for Multi-Carrier Code Division Multiple Access (MC-CDMA) systems. IOn the other hand, we use the Minimum Mean Square Error (MMSE) equalizer after the channel identication to correct the channel distortion. Our simulation results show that, the proposed algorithm provides overall a good channel estimation and a good BER performance.

Measured and estimated data of non-linear BRAN channels using HOS in 4G wireless communications

The aim of this research is to develop a non-linear blind estimator able to represents a Broadband Radio Access Networks (BRAN) channels. In the one hand, we have used Higher Order Statistics (HOS) theory to build our algorithm. Indeed, we develop a non-linear method based only on fourth order cumulants for identifying the diagonal parameters of quadratic systems. In the other hand, the developed approach is applied to estimate the experimental channels, BRAN A, C and E data normalized for MC-CDMA, in non-linear case. However, the estimated data will be used in the blind equalization. The simulation results in noisy environment and for different signal to noise ratio (SNR) show the accuracy of develop estimator blindly (i.e., without any information about the input) with non-Gaussian signal input. Furthermore, in part of blind equalization problem the obtained results, using Zero forcing (ZF) and Minimum Mean Square Error (MMSE) equalizers, demonstrate that the proposed algorithm is very adequate to correct channel distortion in term the Bit Error Rate (BER). Finally, these estimated data present a necessary asset for conducting validation experiments, and can be also used as a baseline.

Comparative study between blind identification algorithms and least mean square algorithm for non minimum phase channel

In this paper we present a comparative study between four algorithms for identification of linear non minimum phase systems in noise environment case. The input sequence is assumed to be independent and identically distributed (i.i.d), zero mean and must be non-gaussian. In order to test the efficiency of these algorithms we have selected the Macchi channel. The simulation results in noisy environment and for different data input channel, demonstrates that the presented methods could estimate the phase and magnitude with different precision.