Blind equalization of square-QAM signals: a multimodulus approach

Abrar, Shafayat; Nandi, Asoke K.

doi:10.1109/tcomm.2010.06.0900552

Cited by 72 publications

(38 citation statements)

References 43 publications

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“…A generalized dispersion-directed (split) costfunction of generic MMAp-q equalizers is given as follows [22]:…”

Section: The Multimodulus Equalizersmentioning

confidence: 99%

“…The cost function defined in (4) can be considered as a generalization of Wesolowski's cost-function [23] with two degrees of freedom or the split version of Larimore and Treichler (CM) cost-function [57]. The corresponding stochastic gradientbased adaptive algorithm is [22] w n = w n−1 + μ |y p R,n | − R …”

Section: The Multimodulus Equalizersmentioning

confidence: 99%

“…z is the smallest positive integer greater than or equal to z [22]. The parameter z is given by z = (z 1 /12) + (1/z 1 ) where z 1 is given as 3 108z 2 + 12 81z 2 2 − 12,…”

Section: The Multimodulus Equalizersmentioning

confidence: 99%

“…By selecting appropriate values of p and q, the generic split cost-function leads to the respective cost-functions of several existing blind equalization algorithms [18][19][20][21]. Interested readers are referred to [22] for detailed discussion on MMAp-q. The update expressions of these algorithms are inherently nonlinear in nature due to the presence of nonlinear error-functions [20,[23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

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Performance analysis of a family of adaptive blind equalization algorithms for square-QAM

Azim

Abrar

Zerguine

et al. 2016

Digital Signal Processing

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“…A generalized dispersion-directed (split) costfunction of generic MMAp-q equalizers is given as follows [22]:…”

Section: The Multimodulus Equalizersmentioning

confidence: 99%

Section: The Multimodulus Equalizersmentioning

confidence: 99%

“…z is the smallest positive integer greater than or equal to z [22]. The parameter z is given by z = (z 1 /12) + (1/z 1 ) where z 1 is given as 3 108z 2 + 12 81z 2 2 − 12,…”

Section: The Multimodulus Equalizersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Performance analysis of a family of adaptive blind equalization algorithms for square-QAM

Azim

Abrar

Zerguine

et al. 2016

Digital Signal Processing

Self Cite

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“…Moreover, many researchers are paying their attention to CMA such as its convergence properties, convergence rate (Fatadin, Ives and Savory, 2009;Abrar and Nandi, 2010;Xiang, Nguyen and Gu, 2006;Chen, Wang and Wang, 2014). Most of them are focusing on the updating of the tap weight vectors.…”

Section: Introductionmentioning

confidence: 99%

A Fast Converge Dual-Mode Modified Constant Norm Blind Equalization Algorithm

2016

Rev. Téc. Ing. Univ. Zulia

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A dual-mode blind equalization algorithm for quadrature amplitude modulation signals is proposed in this paper. It is well known that the famous constant modulus algorithm presents a large steady-state mean square error. The new family of norm algorithm which takes advantage of CMA is included with the simple decision-directed algorithm. The proposed algorithm firstly starts the equalization by CNA and then introduces DD when the eyediagram is convergent. The switching rule is carried out by the mixed gradient. Simple simulation experiments are also proposed to validate the new algorithm.

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A New Dual Mode Blind Equalization Method Based on Neighborhood Symbol‐Based Decision and Decision‐Directed Algorithm

Zhou

Qin

et al. 2023

IEEJ Transactions Elec Engng

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In this paper, a new dual mode blind equalization method using neighborhood symbol‐based decision and decision‐directed (NSBD‐DD) algorithm is proposed to equalize the satellite communication signals. The proposed algorithm adopts the combined cost function to employ the advantages of symbol decision algorithm and the decision‐directed algorithm, which can further improve the universality of the proposed algorithm. Compared with the conventional blind equalization algorithm, the compensation ability of intersymbol interference and convergence speed of the proposed algorithm can be improved simultaneously. To verify the performance of the proposed algorithm, the computer simulation is performed, and the simulation results show that the residual intersymbol interference of the 64QAM signals can be decreased to −50 dB under the satellite channel, which has 30 dB lower than multi‐modulus algorithm (MMA), 26 dB lower than NSBD algorithm, and 10 dB lower than SBD algorithm. And compared with SBD algorithm, the number of iterations required for the NSBD‐DD algorithm can be decreased from 8000 iterations to 6000 iterations, which convergence speed is increased by 25%. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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Blind equalization of square-QAM signals: a multimodulus approach

Cited by 72 publications

References 43 publications

Performance analysis of a family of adaptive blind equalization algorithms for square-QAM

Performance analysis of a family of adaptive blind equalization algorithms for square-QAM

A Fast Converge Dual-Mode Modified Constant Norm Blind Equalization Algorithm

A New Dual Mode Blind Equalization Method Based on Neighborhood Symbol‐Based Decision and Decision‐Directed Algorithm

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