Adaptive Step-Size Constant-Modulus Algorithm for High-Speed Optical Coherent Communication System

Xuejing, 邸雪静 Di; Cheng, 童程 Tong; Xia, 张霞 Zhang; Xiaoguang, 张晓光 Zhang; Lixia, 席丽霞 Xi

doi:10.3788/aos201232.1006004

Cited by 3 publications

(4 citation statements)

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“…CMA is a special case of the Godard algorithms which belong to Bussgang blind equalization algorithms.Fig. 1 shows the baseband model of CMA blind equalization [3].…”

Section: The Basic Principle Of Cmamentioning

confidence: 99%

Normalized p-Norm Blind Equalization Algorithm with Adaptive Momentum under Impulsive Noise Environment

Ruan

Xiao

2015

AMM

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Hereby a normalized p-norm blind equalization algorithm with adaptive momentum was proposed. Normalized p-norm LMS-CMA can obtain robust convergence performance under impulsive noise environment, however, the convergence rate is slow. To further improve the performance of the normalized p-norm LMS-CMA, adaptive momentum according to the instantaneous error is designed. If the instantaneous error based on CMA criterion and DD criterion has the same sign, the momentum factor remains unchanged. Otherwise, the momentum factor is set to 0. The simulation results show that, the proposed algorithm has faster convergence rate than the normalized p-norm blind equalization algorithm, furthermore, it has robust convergence performance under impulsive noise environment.

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“…CMA is a special case of the Godard algorithms which belong to Bussgang blind equalization algorithms.Fig. 1 shows the baseband model of CMA blind equalization [3].…”

Section: The Basic Principle Of Cmamentioning

confidence: 99%

Normalized p-Norm Blind Equalization Algorithm with Adaptive Momentum under Impulsive Noise Environment

Ruan

Xiao

2015

AMM

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“…Blind equalization technology can compensate the communication channel and eliminate inter-symbol interference which caused by multipath transmission effectively at the receiver by receiving signals without any training sequence, thus it can save on the channel bandwidth and improve the quality of communication [1]., Recently blind equalization technology have attracted many experts and researchers, and plentiful research achievements have been obtained. CMA blind equalization is the simplest algorithm through various blind equalization algorithms, also it is a robust and practical algorithm [2].CMA usually adopts the gradient descent algorithm to update the equalizer weight coefficient, thus causing low convergence rate and large steady state residual error after convergence.…”

Section: Introductionmentioning

confidence: 99%

CMA Blind Equalization with Variable Momentum Based on Nonlinear Transformation Function

Xiao

Ruan

2014

AMM

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For the contradiction between convergence rate and convergence precision in the CMA blind equalization with the fixed momentum factor, a variable momentum CMA blind equalization is proposed The output error power of the blind equalizer is acted as the parameter, which control the adjustment of the momentum factor adaptively based on nonlinear transformation function. The algorithm can obtain faster convergence rate and higher convergence precision, also the performance of the blind equalization is improved. The simulation results show that, compared with the CMA blind equalization with the fixed momentum factor, CMA blind equalization with variable momentum based on nonlinear transform can obtain better performance

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“…The condition (2) is to ensure that the gradient direction for the equalizer updating remain the same based on the cost function as Eq.2 and Eq.10. (1) and (2). But the received signal often beyond the definition domain as Eq.12, here a linear scale factor a is adopted to expand the definition domain.…”

Section: Nonlinear Transform Cmamentioning

confidence: 99%

“…Blind adaptive equalization can compensate and tracking the channel without any training sequence, which can save the underwater acoustic channel bandwidth, thus it has potential value in underwater acoustic communication system [1]. In all kinds of blind equalization algorithm, CMA is widely used for its simple structure and easy to implement [2]. CMA can obtain robust convergence performance if the channel interfered with additive white Gaussian noise.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Transform CMA for Underwater Acoustic Channel under Impulsive Noise Environment

Xiao¹,

Dong²,

Li³

2015

Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

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Abstract. The traditional constant modulus algorithm (CMA) can't ensure robust convergence performance under impulsive noise environment, hereby a blind equalization by CMA with nonlinear transformation carrying on the received signal was proposed. The impulsive noise can be suppressed effectively by sine transform, in which the linear interval factor and the scale factor are set to keep the scatter plot of the output consistent with the send signal. By embedding nonlinear transformation in CMA blind equalization, the robust convergence performance can be obtained under the impulsive noise environment. The simulation results under the shallow sea channel show that compared with fractional low order CMA and CMA improved by error nonlinear transforming, the nonlinear transformation CMA has the fastest convergence rate and the lowest steady-state residual error. Meanwhile, the nonlinear transformation CMA has highest convergence ratio under different general signal to noise ratio.

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Adaptive Step-Size Constant-Modulus Algorithm for High-Speed Optical Coherent Communication System

Cited by 3 publications

References 0 publications

Normalized p-Norm Blind Equalization Algorithm with Adaptive Momentum under Impulsive Noise Environment

Normalized p-Norm Blind Equalization Algorithm with Adaptive Momentum under Impulsive Noise Environment

CMA Blind Equalization with Variable Momentum Based on Nonlinear Transformation Function

Nonlinear Transform CMA for Underwater Acoustic Channel under Impulsive Noise Environment

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