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.
In this letter, a new multimodulusalgorithm for blind equalization of complex communication channels is derived by solving a constrained optimization problem with relaxation. The intersymbol interference (ISI) optimi...
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In this letter, a new multimodulusalgorithm for blind equalization of complex communication channels is derived by solving a constrained optimization problem with relaxation. The intersymbol interference (ISI) optimization and phase-recovery capabilities of the proposed algorithm are analyzed. It is shown from computer simulations that superior performance for the derived algorithm over Lin's algorithm is obtained.
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.
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.
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.
The main disadvantage of constant modulusalgorithm (CMA) equalizer is that the output error is very large for the transmitted signals with non-constant modulus. So a new dual-mode CMA equalizer is proposed. This equa...
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The main disadvantage of constant modulusalgorithm (CMA) equalizer is that the output error is very large for the transmitted signals with non-constant modulus. So a new dual-mode CMA equalizer is proposed. This equalizer operates with switching the algorithm from traditional CMA to multi-modulus CMA and the condition of switching is based on the decision of the equalizer's output. Comparing with the CMA, the proposed method has the lower residual mean square error (MSE). The efficiency of the method is proved by computer simulations.
The main disadvantage of constant modulusalgorithm (CMA) equalizer is that the output error is very large for the transmitted signals with non-constant modulus. So a new dual-mode CMA equalizer is proposed. This equa...
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The main disadvantage of constant modulusalgorithm (CMA) equalizer is that the output error is very large for the transmitted signals with non-constant modulus. So a new dual-mode CMA equalizer is proposed. This equalizer operates with switching the algorithm from traditional CMA to multi-modulus CMA and the condition of switching is based on the decision of the equalizer's output. Comparing with the CMA, the proposed method has the lower residual mean square error (MSE). The efficiency of the method is proved by computer simulations.
The main disadvantage of constant modulusalgorithm(CMA) equalizer is that the output error is very large for the transmitted signals with non-constant modulus. So a new dual-mode CMA equalizer is proposed. This equal...
详细信息
The main disadvantage of constant modulusalgorithm(CMA) equalizer is that the output error is very large for the transmitted signals with non-constant modulus. So a new dual-mode CMA equalizer is proposed. This equalizer operates with switching the algorithm from traditional CMA to multi-modulus CMA and the condition of switching is based on the decision of the equalizer's output. Comparing with the CMA, the proposed method has the lower residual mean square error(MSE). The efficiency of the method is proved by computer simulations.
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