The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Rodrigo C De Lamare - One of the best experts on this subject based on the ideXlab platform.

  • adaptive widely linear constrained Constant Modulus reduced rank beamforming
    IEEE Transactions on Aerospace and Electronic Systems, 2017
    Co-Authors: Yunlong Cai, Rodrigo C De Lamare, Minjian Zhao, Benoit Champagne
    Abstract:

    We propose a blind adaptive reduced-rank widely linear beamforming algorithm using the generalized sidelobe canceller structure for interference suppression. A structured Krylov-subspace-based approach is devised to construct the dimensionality reducing transformation matrix, and a recursive least-squares algorithm is developed according to the widely linear constrained Constant Modulus criterion to update the reduced-rank filter. We analyze the convergence and complexity of the proposed algorithm and validate its performance gains through simulations.

  • a low complexity variable forgetting factor Constant Modulus rls algorithm for blind adaptive beamforming
    Signal Processing, 2014
    Co-Authors: Boya Qin, Benoit Champagne, Rodrigo C De Lamare, Yunlong Cai, Minjian Zhao
    Abstract:

    Abstract In this paper, a recursive least squares (RLS) based blind adaptive beamforming algorithm that features a new variable forgetting factor (VFF) mechanism is presented. The beamformer is designed according to the constrained Constant Modulus (CCM) criterion, and the proposed adaptive algorithm operates in the generalized sidelobe canceler (GSC) structure. A detailed study of its operating properties is carried out, including a convexity analysis and a mean squared error (MSE) analysis of its steady-state behavior. The results of numerical experiments demonstrate that the proposed VFF mechanism achieves a superior learning and tracking performance compared to other VFF mechanisms.

  • robust adaptive beamforming algorithms using the constrained Constant Modulus criterion
    Iet Signal Processing, 2014
    Co-Authors: Lukas T N Landau, Rodrigo C De Lamare, Martin Haardt
    Abstract:

    The authors present a robust adaptive beamforming algorithm based on the worst-case (WC) criterion and the constrained Constant Modulus (CCM) approach, which exploits the Constant Modulus property of the desired signal. Similar to the existing worst-case beamformer with the minimum variance design, the problem can be reformulated as a second-order cone programme and solved with interior point methods. An analysis of the optimisation problem is carried out and conditions are obtained for enforcing its convexity and for adjusting its parameters. Furthermore, low-complexity robust adaptive beamforming algorithms based on the modified conjugate gradient and an alternating optimisation strategy are proposed. The proposed low-complexity algorithms can compute the existing WC constrained minimum variance and the proposed WC-CCM designs with a quadratic cost in the number of parameters. Simulations show that the proposed WC-CCM algorithm performs better than existing robust beamforming algorithms. Moreover, the numerical results also show that the performances of the proposed low-complexity algorithms are equivalent or better than that of existing robust algorithms, whereas the complexity is more than an order of magnitude lower.

  • reduced rank adaptive constrained Constant Modulus beamforming algorithms based on joint iterative optimization of filters
    arXiv: Information Theory, 2013
    Co-Authors: Lei Wang, Rodrigo C De Lamare
    Abstract:

    This paper proposes a reduced-rank scheme for adaptive beamforming based on the constrained joint iterative optimization of filters. We employ this scheme to devise two novel reduced-rank adaptive algorithms according to the Constant Modulus (CM) criterion with different constraints. The first devised algorithm is formulated as a constrained joint iterative optimization of a projection matrix and a reduced-rank filter with respect to the CM criterion subject to a constraint on the array response. The constrained Constant Modulus (CCM) expressions for the projection matrix and the reduced-rank weight vector are derived, and a low-complexity adaptive algorithm is presented to jointly estimate them for implementation. The second proposed algorithm is extended from the first one and implemented according to the CM criterion subject to a constraint on the array response and an orthogonal constraint on the projection matrix. The Gram-Schmidt (GS) technique is employed to achieve this orthogonal constraint and improve the performance. Simulation results are given to show superior performance of the proposed algorithms in comparison with existing methods.

  • low complexity variable forgetting factor mechanism for blind adaptive constrained Constant Modulus algorithms
    IEEE Transactions on Signal Processing, 2012
    Co-Authors: Yunlong Cai, Rodrigo C De Lamare, Minjian Zhao, Jie Zhong
    Abstract:

    In this paper, we propose a novel low-complexity variable forgetting factor (VFF) mechanism for blind adaptive constrained Constant Modulus (CCM) recursive least squares (RLS) algorithms applied to linear interference suppression in direct-sequence code-division multiple access (DS-CDMA) systems. The proposed variable forgetting factor mechanism employs an updated component related to the time average of the Constant Modulus (CM) cost function to automatically adjust the forgetting factor in order to ensure good tracking of the interference and the channel. Convergence and tracking analyses are carried out. Analytical expressions for predicting the mean-squared error of the proposed adaptation technique are obtained. Simulation results are presented for nonstationary environments and show that the proposed variable forgetting factor mechanism achieves superior performance to previously reported methods at a reduced complexity.

Pierre Comon - One of the best experts on this subject based on the ideXlab platform.

  • Optimal Step-Size Constant Modulus Algorithm
    IEEE Transactions on Communications, 2008
    Co-Authors: Vicente Zarzoso, Pierre Comon
    Abstract:

    The step size leading to the absolute minimum of the Constant Modulus (CM) criterion along the search direction can be obtained algebraically at each iteration among the roots of a third-degree polynomial. The resulting optimal step-size CMA (OS-CMA) is compared with, other CM-based iterative techniques in terms of performance-versus-complexity trade-off.

  • semi blind Constant Modulus equalization with optimal step size
    International Conference on Acoustics Speech and Signal Processing, 2005
    Co-Authors: Vicente Zarzoso, Pierre Comon
    Abstract:

    Channel equalization is an important problem in digital communications. The paper studies a hybrid equalization criterion combining the Constant Modulus (CM) property and the minimum mean square error (MMSE) between the equalizer output and the known pilot sequence. An efficient semi-blind block gradient-descent algorithm is proposed, in which the step size globally minimizing the cost function along the search direction is algebraically computed at each iteration. The use of the optimal step size notably accelerates convergence and can further reduce the impact of local extrema on the semi-blind algorithm's performance. The proposed approach is not restricted to the CM-MMSE principle, but it can benefit other equalization criteria as well.

J Ibanez - One of the best experts on this subject based on the ideXlab platform.

  • blind equalization of Constant Modulus signals using support vector machines
    IEEE Transactions on Signal Processing, 2004
    Co-Authors: Ignacio Santamaria, C Pantaleon, Luis Vielva, J Ibanez
    Abstract:

    In this paper, the problem of blind equalization of Constant Modulus (CM) signals is formulated within the support vector regression (SVR) framework. The quadratic inequalities derived from the CM property are transformed into linear ones, thus yielding a quadratic programming (QP) problem. Then, an iterative reweighted procedure is proposed to blindly restore the CM property. The technique is suitable for real and complex modulations, and it can also be generalized to nonlinear blind equalization using kernel functions. We present simulation examples showing that linear and nonlinear blind SV equalizers offer better performance than cumulant-based techniques, mainly in applications when only a small number of data samples is available, such as in packet-based transmission over fast fading channels.

  • blind equalization of Constant Modulus signals via support vector regression
    International Conference on Acoustics Speech and Signal Processing, 2003
    Co-Authors: Ignacio Santamaria, Luis Vielva, J Ibanez, C Pantaleon
    Abstract:

    In this paper the problem of blind equalization of Constant Modulus (CM) signals is formulated within the support vector (SV) regression framework. The quadratic inequalities derived from the CM property are transformed into linear ones, thus yielding a quadratic programming (QP) problem. Then an iterative reweighted procedure is proposed to blindly restore the CM property. The technique can be generalized to nonlinear blind equalization using kernel functions. We present simulation examples showing that linear and nonlinear blind SV equalizers offer better performance than cumulant-based techniques, mainly in applications when only a small number of data samples is available, such as in packet-based transmission over fast fading channels.

Constantinos B. Papadias - One of the best experts on this subject based on the ideXlab platform.

  • Nonsingular Constant Modulus Equalizer for PDM-QPSK Coherent Optical Receivers
    IEEE Photonics Technology Letters, 2010
    Co-Authors: Athanasios Vgenis, Constantinos B. Papadias, Constantinos S. Petrou, Ioannis Roudas, Lambros Raptis
    Abstract:

    Adaptive electronic equalizers using the Constant Modulus algorithm (CMA) algorithm often converge to a singular coefficient matrix that produces the same signal at multiple outputs. We address this issue in the context of optical communications systems with polarization-division multiplexing and coherent receivers. We study, by computer simulation, the performance of multiuser CMA equalizer, an enhanced CMA equalizer initially proposed for use in wireless multiuser and later multiple-input/multiple-output communications systems. We show that the proposed adaptive electronic equalizer does not exhibit singularities and, therefore, is superior to the commonly used CMA equalizer.

  • a Constant Modulus algorithm for multiuser signal separation in presence of delay spread using antenna arrays
    IEEE Signal Processing Letters, 1997
    Co-Authors: Constantinos B. Papadias, A Paulraj
    Abstract:

    The consider the problem of recovering p synchronous communication signals that are transmitted through a multiple-input/multiple-output (MIMO) linear channel and are, therefore, received in the presence of both interuser (IUI) and intersymbol interference (ISI). A multichannel linear equalization approach is taken, and we propose to adjust the equalizer coefficients with a blind adaptive algorithm (without the use of training data). This multiuser Constant Modulus algorithm (MU-CMA) is derived from the minimization of a cost function that penalizes deviations of the equalized signals from the Constant Modulus property as well as cross-correlations between them. The proposed scheme appears to be an appealing technique for multiuser blind equalization that combines good convergence properties with low computational complexity.

  • a space time Constant Modulus algorithm for sdma systems
    Vehicular Technology Conference, 1996
    Co-Authors: Constantinos B. Papadias, A Paulraj
    Abstract:

    We consider the problem of blind recovery of p synchronous i.i.d. communication signals that are transmitted through a linear spatio-temporal channel and captured by an m-element array. Such a situation may arise for example in a space-division-multiple-access (SDMA) mobile communication system. We propose an approach of the Constant-Modulus (CM) type in order to construct optimization criteria that may allow joint blind recovery of the transmitted signals with low computational complexity. Several aspects of the proposed algorithms related to their convergence and implementation are discussed and computer simulations are provided as experimental evidence to the algorithms' performance.

  • new adaptive blind equalization algorithms for Constant Modulus constellations
    International Conference on Acoustics Speech and Signal Processing, 1994
    Co-Authors: Constantinos B. Papadias
    Abstract:

    We present a new class of adaptive filtering algorithms for blind equalization of Constant Modulus signals. The algorithms are first derived in a classical system identification context by minimizing at each iteration a deterministic criterion and then their counterpart for blind equalization is derived by modifying this criterion taking into account the Constant-Modulus property of the transmitted signal. The algorithms impose more constraints than the classical Constant Modulus algorithm (CMA) and as a result achieve faster convergence. An asymptotic analysis has provided useful parameter bounds that guarantee the algorithms' stability. A priori knowledge of these bounds helps the algorithms escape from undesirable local minima of their cost function thus giving them a potential advantage over the classical CMA. An efficient computational organization for the derived algorithms is also proposed and their behaviour has been tested by means of computer simulations. >

L I Jinming - One of the best experts on this subject based on the ideXlab platform.

  • simulation of Constant Modulus blind equalization algorithm initialized by support vector machines
    Computer Simulation, 2008
    Co-Authors: L I Jinming
    Abstract:

    For increasing the convergence rate of Constant Modulus blind equalization algorithm and avoiding local minima,a Constant Modulus algorithm initialed by support vector machines is presented in this paper.The new algo- rithm utilizes a short initial data segment,transforms blind equalization problem into support vector regression problem and sets the initial weights of the blind equalizer by means of support vector machines.Then,the algorithm is switched to Constant Modulus algorithm,which has a lower computational burden.The results of computer simulation based on a shallow water channel demonstrate that the initial phase utilizing support vector machines converges fast, while the algorithm is stable after switching to the Constant Modulus algorithm.The proposed algorithm is suitable for real time data recovery in fast fading underwater acoustic channel.