A novel class of fast multi-modulus algorithms (fastMMA) for Blind Source Separation (BSS) and deconvolution are presented in this work. These are obtained through a fast fixed-point optimization rule used to minimize...
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A novel class of fast multi-modulus algorithms (fastMMA) for Blind Source Separation (BSS) and deconvolution are presented in this work. These are obtained through a fast fixed-point optimization rule used to minimize the multi-modulus (MM) criterion. Here, two BSS versions are provided to separate the sources either by finding the separation matrix at once or by separating a single source each time using a fast deflation technique. Further, the latter method is extended to cover systems of convolutive nature. Interestingly, these algorithms are implicitly shown to belong to the fixed step-size gradient descent family, henceforth, an algebraic variable step-size is proposed to make these algorithms converge even much faster. Apart from being computationally and performance-wise attractive, the new algorithms are free of any user-defined parameters.
To improve the equalization performance for sparse underwater acoustic channel, an l(0)-norm constraint multi-modulus blind decision feedback equalization algorithm with adaptive zero attractor (l(0)-MMBDFE-AZA) is pr...
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ISBN:
(纸本)9781728186160
To improve the equalization performance for sparse underwater acoustic channel, an l(0)-norm constraint multi-modulus blind decision feedback equalization algorithm with adaptive zero attractor (l(0)-MMBDFE-AZA) is proposed. In contrast to the existent algorithms, the proposed approach incorporates the l(0)-norm constraint into the cost function of multi-modulus blind equalization algorithm, the identification ability for sparse system can be improved. In addition, the proposed algorithm can adaptively adjust the value of zero attractor according to the power of the measurement noise signal, and thus is more suitable for time-varying underwater acoustic environment. Simulation results validate the proposed algorithm and show that the equalization performance of proposed algorithm outperforms that of existing counterparts.
This paper targets the blind deconvolution problem for multiple-input multiple-output communication systems, using small and moderate constellation's size signals, i.e. PSK and QAM. We introduce four different bli...
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This paper targets the blind deconvolution problem for multiple-input multiple-output communication systems, using small and moderate constellation's size signals, i.e. PSK and QAM. We introduce four different blind deconvolution algorithms based on four different techniques. These algorithms come as a natural extension of the successful work done by Shah et al in 2018 for blind source separation (BSS). The first two methods are considered as two-step based methods, where the first one performs the BSS for the spatio-temporal system followed by a pairing and sorting phase. While the second is accomplished by performing a cascaded linear equalization, using one of the existing subspace-methods, followed by the BSS routine. The third method is based on the minimization of a hybrid cost function, and the last one is a deflation-based method. These solutions summarize the main possible paths that can be followed to extend any of the existing instantaneous de-mixing algorithms. Experimental results are provided to compare and highlight the unique characteristics of each of the four different methods. (C) 2020 Elsevier B.V. All rights reserved.
40-Gb/s/lambda multi-band carrierless amplitude and phase (CAP) modulation long-reach passive optical networks were demonstrated using 10-G class transceivers only. A major issue of multi-band CAP is that it is vulner...
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40-Gb/s/lambda multi-band carrierless amplitude and phase (CAP) modulation long-reach passive optical networks were demonstrated using 10-G class transceivers only. A major issue of multi-band CAP is that it is vulnerable to timing error, and this work has offered quantitative analysis about it in detail for the first time. A novel simple timing recovery approach, partial differential quadrature amplitude modulation constellation encoding and decoding schemes together with blind multimodulusalgorithm equalization are proposed to address the issue efficiently, enabling zero-overhead signal recovery. Results show that it can offer excellent system tolerance to timing error of at least +/- 0.1 symbol period even for the highest frequency CAP sub-band. The characteristics of the transceiver are measured, and optimization of critical system parameters is performed including the CAP sub-band count, 10-G Mach-Zehnder intensity modulator operation conditions, optical launch power, and wavelength offset asymmetrical optical filtering. For downlink using erbium-doped fiber amplifier preamplifiers, successful 40-Gb/s multi-band CAP signal transmission over an 80-km (90-km) single-mode fiber is achieved with a link power budget of 33 dB (29 dB) considering a forward error correction threshold bit error ratio of 3.8 x 10(-3).
In order to overcome the inter-symbol interference generated by multipath effect and improve the frequency band utilization ratio in the underwater acoustic communication system, the blind equalization problem of the ...
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ISBN:
(纸本)9781728118598
In order to overcome the inter-symbol interference generated by multipath effect and improve the frequency band utilization ratio in the underwater acoustic communication system, the blind equalization problem of the underwater acoustic channel is expressed as the support vector regression problem. The error function of constant modulusalgorithm (CMA) and multi-modulus algorithm (MMA) are included in the penalty term of the SVR, and the iterative reweighted least squares (IRWLS) method is used to find the optimal equalizer coefficients, thus two batch blind equalization algorithms are proposed in this paper. The simulation experiments show that the proposed two batch algorithms can effectively realize the blind equalization of underwater acoustic channel, compared with the traditional online blind algorithm, they achieves fast convergence with small samples and have excellent blind equalization performance.
In this paper, we propose a variable step-size multi-modulus algorithm with quantized-error method (QE-VSSMMA), which benefits from a nonlinear quantized error method as well as the variable step-size method and thus ...
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ISBN:
(纸本)9780819489326
In this paper, we propose a variable step-size multi-modulus algorithm with quantized-error method (QE-VSSMMA), which benefits from a nonlinear quantized error method as well as the variable step-size method and thus holds reduced computational complexity and improved convergence rate compared to conventional multi-modulus algorithm (MMA). Simulation shows that the new algorithm has the characteristics of faster convergence, lower implementation cost while preserves the robustness property and the phase recovery functionality of MMA. The new algorithm is suitable for resource-limited environment.
The issue of blind multiple-Input and multiple-Output (MIMO) deconvolution of communication system is addressed. Two new iterative Blind Source Separation (BSS) algorithms are presented, based on the minimization of M...
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In this paper, we propose a demultiplexing method based on frequency-domain joint decision multimodulusalgorithm (FD-JDMMA) for mode division multiplexing (MDM) system. The performance of FD-JDMMA is compared with f...
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In this paper, we propose a demultiplexing method based on frequency-domain joint decision multimodulusalgorithm (FD-JDMMA) for mode division multiplexing (MDM) system. The performance of FD-JDMMA is compared with frequency-domain multi-modulus algorithm (FD-MMA) and frequency-domain least mean square (FD-LMS) algorithm. The simulation results show that FD-JDMMA outperforms FD-MMA in terms of BER and convergence speed in the cases of mQAM (m=4, 16 and 64) formats. And it is also demonstrated that FD-JDMMA achieves better BER performance and converges faster than FD-LMS in the cases of 16QAM and 64QAM. Furthermore, FD-JDMMA maintains similar computational complexity as the both equalization algorithms. (C) 2016 Elsevier B.V. All rights reserved.
The issue of blind multiple-Input and multiple-Output (MIMO) deconvolution of communication system is addressed. Two new iterative Blind Source Separation (BSS) algorithms are presented, based on the minimization of M...
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ISBN:
(纸本)9781467369985
The issue of blind multiple-Input and multiple-Output (MIMO) deconvolution of communication system is addressed. Two new iterative Blind Source Separation (BSS) algorithms are presented, based on the minimization of multi-modulus (MM) criterion. A pre-whitening filter is utilized to transform the problem into finding a unitary beamformer matrix. Then, applying iterative Givens and Hyperbolic rotations results in Givens multi-modulus algorithm (G-MMA) and Hyperbolic G-MMA (HG-MMA), respectively. Proposed algorithms are compared with several BSS algorithms in terms of Signal to Interference and Noise Ratio (SINR) and Symbol Error Rate (SER) and it was shown to outperform them.
In view of slow convergence speed, large steady mean square error(MSE), and existing blind phase for the constant modulus blind equalization algorithm(CMA), a multi-modulus blind equalization algorithm based on memeti...
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ISBN:
(纸本)9781510812055
In view of slow convergence speed, large steady mean square error(MSE), and existing blind phase for the constant modulus blind equalization algorithm(CMA), a multi-modulus blind equalization algorithm based on memetic algorithm(MA-MMA) is proposed, which combines the basic idea of intelligent optimization algorithm and introduces the individual own evolution and social behavior among individuals to the blind equalization technology. In this proposed algorithm, the reciprocal of the cost function of multi-modulus blind equalization algorithm(MMA) is defined as the fitness function of the memetic algorithm(MA), the initial optimal weight vector of the MMA is optimized by using the global information sharing mechanism and local depth search ability of the MA. When the initial optimum weight vector of the MMA is obtained, the weight vector of the MMA may be updated. The simulation results with the higher-order APSK multi-modulus signals show that, compared with the CMA, the MMA, and the multi-modulus blind equalization algorithm based on genetic algorithm(GA-MMA), the proposed MA-MMA has the fastest convergence speed, smallest mean square error(MSE), and clearest output constellations.
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