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

Zidane, Mohammed; Safi, Saïd; Sabri, Mohamed; Boumezzough, Ahmed

doi:10.1109/wcccs.2014.7107925

Cited by 7 publications

(1 citation statement)

References 3 publications

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“…The synchronization required between the transmitter and the receiver is also a problem in the communication process. To handle this phase estimation problem, some authors have employed higher-order cumulants (HOCs) in order to investigate the reliability of these techniques if the channel is influenced by a colored noise [2,[9][10][11][12][13][14][15][16]. HOCs are a significant topic with multiple applications in the field of systems theory, such as in digital signal recognition [17], automatic modulation classification of real signals [18], and space-time block code identification [19].…”

Section: Introductionmentioning

confidence: 99%

Channel Identification Based on Cumulants, Binary Measurements, and Kernels

Oualla

Fateh

Darif

et al. 2021

Systems

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In this paper, we discuss the problem of channel identification by using eight algorithms. The first three algorithms are based on higher-order cumulants, the next three algorithms are based on binary output measurement, and the last two algorithms are based on reproducing kernels. The principal objective of this paper is to study the performance of the presented algorithms in different situations, such as with different sizes of the data input or different signal-to-noise ratios. The presented algorithms are applied to the estimation of the channel parameters of the broadband radio access network (BRAN). The simulation results confirm that the presented algorithms are able to estimate the channel parameters with different accuracies, and each algorithm has its advantages and disadvantages for a given situation, such as for a given SNR and data input. Finally, this study provides an idea of which algorithms can be selected in a given situation. The study presented in this paper demonstrates that the cumulant-based algorithms are more adequate if the data inputs are not available (blind identification), but the kernel- and binary-measurement-based methods are more adequate if the noise is not important (SNR≥16 dB).

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Section: Introductionmentioning

confidence: 99%

Channel Identification Based on Cumulants, Binary Measurements, and Kernels

Oualla

Fateh

Darif

et al. 2021

Systems

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Mixed third- and fourth-order cumulants-based algorithm for nonlinear kernels identification in cubic systems

Zidane¹,

Dinis

2021

SIViP

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

2018

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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.

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

Cited by 7 publications

References 3 publications

Channel Identification Based on Cumulants, Binary Measurements, and Kernels

Channel Identification Based on Cumulants, Binary Measurements, and Kernels

Mixed third- and fourth-order cumulants-based algorithm for nonlinear kernels identification in cubic systems

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

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