A novel radius-adjusted approach for blind adaptive equalization

Banovic, Kevin; Abdel-Raheem, Esam; Khalid, Mohammed

doi:10.1109/lsp.2005.860544

Cited by 26 publications

(11 citation statements)

References 8 publications

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“…For the square QAM constellation and a cosine-square CME function, the modified CMA (MCMA) cost function becomes (4) (see next page), where 2d is the minimum distance between the constellation symbols, β is a weighting factor governing the relative importance of the CMA and CME errors, and subscripts r and i denote real and imaginary components, respectively. As in the case of the MCMA, we can add a CME term to the cost functions of the GSA and MMA for QAM signaling [5]- [7]. This yields the modified GSA (MGSA) and modified MMA (MMMA) with cost functions (5) and (6) (see next page), where csgn (z k ) = sgn (z kr ) + jsgn (z ki ).…”

Section: Modified Gsa and Modified Mmamentioning

confidence: 99%

“…In the conditional Gaussian MSE analysis, the property that conditioned on s k and c k , the quantities z k and y k are jointly Gaussian is used extensively. The conditional Gaussian MSE analysis for the GSA, CMA and MMA is given in [7]- [10]. The Taylor series-based approximation was used by Garth [10] to derive the MSE of the GSA, CMA and MMA; it gives simpler but less accurate MSE expressions.…”

Section: Mse Convergence Analysis For Mgsa Mcmamentioning

confidence: 99%

“…We consider two channels: a typical voice-band communication channel [7], and a three-component real multipath channel with coefficients [0.27 1 0.27], which is a poor contender for the conditional Gaussian approximation. The transmitted signal is from a 64-QAM constellation and the minimum distance between symbols is 2.…”

Section: Simulationsmentioning

confidence: 99%

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Convergence analysis of blind equalization algorithms using constellation-matching

Kassam

2008

IEEE Trans. Commun.

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Two modified blind equalization algorithms are analyzed for performance. These algorithms add a constellation-matched error term to the cost functions of the generalized Sato and multimodulus algorithms. The dynamic convergence behavior and steady-state performance of these algorithms, and of a related version of the constant modulus algorithm, are characterized. The analysis establishes the improved performance of the proposed algorithms. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This journal article is available at ScholarlyCommons: http://repository.upenn.edu/ese_papers/492 Index Terms-Adaptive equalizer, blind equalization algorithms, convergence analysis.

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Section: Modified Gsa and Modified Mmamentioning

confidence: 99%

Section: Mse Convergence Analysis For Mgsa Mcmamentioning

confidence: 99%

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Convergence analysis of blind equalization algorithms using constellation-matching

Kassam

2008

IEEE Trans. Commun.

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“…Other works have proposed algorithms based on the CMA. Among them we may cite [17,18], that use dual-mode CM-based cost functions to improve the performance of the CMA. However, these works deal with cost functions with a high computational complexity compared with that of the CM.…”

Section: The Decision Directed Modulus Algorithmmentioning

confidence: 99%

Decision directed adaptive blind equalization based on the constant modulus algorithm

Fernandes

Favier

Mota

2007

SIViP

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International audienceIn this paper, new decision directed algorithms for blind equalization of communication channels are presented. These algorithms use informations about the last decided symbol to improve the performance of the constant modulus algorithm (CMA). The main proposed technique, the so called decision directed modulus algorithm (DDMA), extends the CMA to non-CM modulations. Assuming correct decisions, it is proved that the decision directed modulus (DDM) cost function has no local minima in the combined channel-equalizer system impulse response. Additionally, a relationship between the Wiener and DDM minima is established. The other proposed algorithms can be viewed as modifications of the DDMA. They are divided into two families: stochastic gradient algorithms and recursive least squares (RLS) algorithms. Simulation results allow to compare the performance of the proposed algorithms and to conclude that they outperform well-known methods

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“…The RMDA [11,12] is a hybrid algorithm that augments the MMA error signal with a decision-directed error term (DD). The RMDA error signal linearly weighs the MMA and DD error terms based on the radius-adjusted approach, which was discussed in Section 3.3 for RMMA.…”

Section: Radius-adjusted Multimodulus Decision-directed Algorithmmentioning

confidence: 99%

A configurable fractionally-spaced blind adaptive equalizer for QAM demodulators

Banovic

Khalid

Abdel-Raheem

2007

Digital Signal Processing

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A novel radius-adjusted approach for blind adaptive equalization

Cited by 26 publications

References 8 publications

Convergence analysis of blind equalization algorithms using constellation-matching

Convergence analysis of blind equalization algorithms using constellation-matching

Decision directed adaptive blind equalization based on the constant modulus algorithm

A configurable fractionally-spaced blind adaptive equalizer for QAM demodulators

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