Recently, we proposed a model for the steady-state estimation error of real-valued constant-modulus-based algorithms as a function of the a priori error and of a term that measures the variability in the modulus of th...
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ISBN:
(纸本)9781424414833
Recently, we proposed a model for the steady-state estimation error of real-valued constant-modulus-based algorithms as a function of the a priori error and of a term that measures the variability in the modulus of the transmitted signal. In this paper, we extend this model to complex-valued data and use it in conjunction with the feedback analysis method to obtain an analytical expression for the steady-state excess mean-square error (EMSE) of the constant modulus algorithm (CMA). Such expression is more accurate for larger step-sizes than the previous ones in the literature, as confirmed by the good agreement between analytical and simulation results. Furthermore, from the EMSE expression, we obtain an estimate for the CMA step-size interval to ensure its convergence and stability, when it is initialized sufficiently close to the zero-forcing solution.
One of the most popular algorithms for blind equalization is the constant modulus algorithm (CMA), due to its simplicity and low computational cost. However, if the step-size is not properly chosen or if the initializ...
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ISBN:
(纸本)9781424414833
One of the most popular algorithms for blind equalization is the constant modulus algorithm (CMA), due to its simplicity and low computational cost. However, if the step-size is not properly chosen or if the initialization is distant from the optimal solution, CMA can diverge or converge to undesirable local minima. In order to avoid divergence, we propose a dual-mode algorithm, which works as CMA with a time-variant step-size, but rejects non-consistent estimates of the transmitted signal. We present a deterministic analysis of the stability of the new algorithm for scalar filters. In the vector case, the good performance of the new algorithm is confirmed through numerical simulations.
The constant modulus algorithm is a widely used blind equalization algorithm. But it has a disadvantage for its initialization. Its convergence characteristics depends on its preliminary tap gains. The paper introduce...
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ISBN:
(纸本)9781424417186
The constant modulus algorithm is a widely used blind equalization algorithm. But it has a disadvantage for its initialization. Its convergence characteristics depends on its preliminary tap gains. The paper introduced the method of optimization and the technology of small swatch repetition to overcome the initialization's effect and accelerate the convergence. Computer simulation is implemented with QAM system. The algorithm achieves the goal and is proved successful.
For overcoming the low convergent rate and high mean square error of constant modulus algorithm (CMA) and utilizing the advantages of the Fractionally Spaced Equalizer (FSE) containing lots of channel information, a C...
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ISBN:
(纸本)9787506292207
For overcoming the low convergent rate and high mean square error of constant modulus algorithm (CMA) and utilizing the advantages of the Fractionally Spaced Equalizer (FSE) containing lots of channel information, a Cascaded Blind Equalizer based on CMA (CBE-CMA) is proposed. The proposed CBE-CMA is a combination of Baud Spaced Equalizer based on CMA (BSE-CMA) and T/2 Fractionally Spaced Equalizer based on CMA (T/2-FSE-CMA), uses T/2-FSE-CMA as its first level and employs BSE-CMA for its second level. Owing to the ability of the CBE-CMA to compensate for the distortion of channel, to suppress inter-symbol interference, and to recovery transmitted sequence twice, so it outperforms BSE-CMA and T/2-FSE-CMA in improving convergent rate and reducing mean square error. The efficiency of the proposed CBE-CMA is proved by computer simulation with multi-path water acoustic channels.
A new blind equalization method for constantmodulus (CM) signals based on Gaussian process for regression (GPR) by incorporating a constant modulus algorithm (CMA)-like error function into the conventional GPR framew...
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A new blind equalization method for constantmodulus (CM) signals based on Gaussian process for regression (GPR) by incorporating a constant modulus algorithm (CMA)-like error function into the conventional GPR framework is proposed. The GPR framework formulates the posterior density function for weights using Bayes' rule under the assumption of Gaussian prior for weights. The proposed blind GPR equalizer is based on linear-in-weights regression model, which has a form of nonlinear minimum mean-square error solution. Simulation results in linear and nonlinear channels are presented in comparison with the state-of-the-art support vector machine (SVM) and relevance vector machine (RVM) based blind equalizers. The simulation results show that the proposed blind GPR equalizer without cumbersome cross-validation procedures shows the similar performances to the blind SVM and RVM equalizers in terms of intersymbol interference and bit error rate. (C) 2011 Elsevier B.V. All rights reserved.
This paper addresses the problem of blind separation of convolutive mixtures of BPSK and circular linearly modulated signals with unknown (and possibly different) baud rates and carrier frequencies. In previous works,...
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This paper addresses the problem of blind separation of convolutive mixtures of BPSK and circular linearly modulated signals with unknown (and possibly different) baud rates and carrier frequencies. In previous works, we established that the constant modulus algorithm (CMA) is able to extract a source from a convolutive mixture of circular linearly modulated signals. We extend the analysis of the extraction capabilities of the CMA when the mixing also contains BPSK signals. We prove that if the various source signals do not share any non-zero cyclic frequency nor any non-conjugate cyclic frequencies, the local minima of the constantmodulus cost function are separating filters. Unfortunately, the minimization of the Godard cost function generally fai s when considering BPSK signals that have the same rates and the same carrier frequencies. This failure is due to the existence of non-separating local minima of the Godard cost function. In order to achieve the separation, we propose a simple modification of the Godard cost function which only requires knowledge of the BPSK sources frequency offsets at the receiver side. We provide various simulations of realistic digital communications scenarios that support our theoretical statements. (C) 2011 Elsevier B.V. AB rights reserved.
We propose a novel non-data-aided clock recovery method for differential quadrature phase-shift keying optical systems based on the coefficients of the constant modulus algorithm (CMA) adaptive equalizer. The new tech...
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We propose a novel non-data-aided clock recovery method for differential quadrature phase-shift keying optical systems based on the coefficients of the constant modulus algorithm (CMA) adaptive equalizer. The new technique exhibits a satisfactory performance under certain combinations of differential group delay (DGD) and state of polarization, in which the traditional Gardner algorithm fails. The robustness of the proposed algorithm against chromatic dispersion, DGD, and state of polarization variations is demonstrated experimentally.
Minimum output energy (MOE) algorithm is a widely used adaptive algorithm for blind adaptation of infinite impulse response (IIR) filters. In this paper, we show that the MOE algorithm is not suitable for blind adapta...
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Minimum output energy (MOE) algorithm is a widely used adaptive algorithm for blind adaptation of infinite impulse response (IIR) filters. In this paper, we show that the MOE algorithm is not suitable for blind adaptation of the complex-valued IIR equalizer for digital vestigial sideband signals, whereas the constant modulus algorithm successfully achieves blind adaptation of the IIR equalizers when MOE fails. Because of the difficulty in analyzing IIR equalizers, the analysis is limited to a simple two-tap channel case. For more general multitap channel cases, the performance of a complex constant modulus algorithm IIR is evaluated through simulation. Copyright (C) 2011 John Wiley & Sons, Ltd.
This paper investigates a blind space-time equaliser (STE) designed for single-input multiple-output (SIMO) systems that employ high-throughput quadrature amplitude modulation schemes. A constant modulus algorithm (CM...
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This paper investigates a blind space-time equaliser (STE) designed for single-input multiple-output (SIMO) systems that employ high-throughput quadrature amplitude modulation schemes. A constant modulus algorithm (CMA) aided soft decision-directed (SDD) scheme, originally derived for low-complexity blind equalisation of single-input single-output channels, is extended to the SIMO scenario. Simulations are conducted to compare the performance of this blind adaptive scheme with another low-complexity blind STE referred to as the CMA aided decision directed (DD) scheme. The results obtained demonstrate that for SIMO systems the CMA aided SDD scheme exhibits advantages over the CMA aided DD arragement, in terms of its faster convergence speed and lower computational complexity.(c) 2007 Elsevier B.V. All rights reserved.
a variable step size constant modulus algorithm (CMA) based on the gamma distribution is implemented as solutions to optimize the problem of blind equalization. The factor of step size in blind equalization algorithm ...
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ISBN:
(纸本)9783037853559
a variable step size constant modulus algorithm (CMA) based on the gamma distribution is implemented as solutions to optimize the problem of blind equalization. The factor of step size in blind equalization algorithm is varied with gamma variable, in terms of the characteristics of which, the algorithm can search for the globe optimal equalizer weight vector. Simulation results indicate that the convergence rate and the steady Mean Square Errors (MSE) performances of the algorithm proposed are much better than conventional CMA and modified CMA blind equalization algorithms.
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