Blind search for optimal Wiener equalizers using an artificial immune network model

This work proposes a framework to determine the optimal Wiener equalizer by using an artificial immune network model together with the constant modulus (CM) cost function. This study was primarily motivated by recent theoretical results concerning the CM criterion and its relation to the Wiener approach. The proposed immune-based technique was tested under different channel models and filter orders, and benchmarked against a procedure using a genetic algorithm with niching. The results demonstrated that the proposed strategy has a clear superiority when compared with the more traditional technique. The proposed algorithm presents interesting features from the perspective of multimodal search, being capable of determining the optimal Wiener equalizer in most runs for all tested channels.2003874074

Multi-user PDF estimation based criteria for adaptive blind separation of discrete sources

This paper deals with criteria for adaptive blind separation of discrete sources. The criteria are based on the estimation of the probability density function (pdf) of the recovered signal using a parametric model and the divergence of Kullback-Leibler to measure the similarities between the involved signals. Two strategies that guarantee the recovering of all sources are employed: the first one introduces a penalty when the sources are correlated and the second one constrains the filtering to an orthogonal global system response. Simulations are carried out to evaluate the performance of the criteria compared with existing blind methods in typical multi-user environments such as spatial and space-time processing. (c) 2005 Elsevier B.V. All rights reserved.8551059107

Using adaptive arrays for collision resolution in slotted ALOHA packet radio systems

This paper discusses a general framework for evaluating the throughput performance of adaptive antenna arrays when the Slotted ALOHA protocol is employed as the random access mechanism for wireless packet transmission. A novel blind adaptive algorithm is presented and its performance is assessed by comparison with the minimum mean squared error (MMSE). Tno propagation scenarios are considered: line of sight and Rayleigh fading, The results are obtained through a mis of analysis and simulation and it is shown that the proposed algorithm allows the antenna array to attain a high fraction of the optimal MMSE gains without resorting to training sequences.2434435

Performance evaluation of combined spatial processing and multiple access interference equalization for DS-CDMA systems

Adaptive detection in code division multiple access (CDMA) systems aims the reduction of interference in order to allow capacity increase. Spatial processing and multiple access interference (MAI) equalization are two important techniques that have been used separately in adaptive detection for CDMA. The first contribution of this paper is the proposal and performance assessment of a detector that operates simultaneously as a spatial processor and MAI equalizer. Its minimum mean square error performance in a multiple cell CDMA system is addressed and compared with the two existing techniques. A blind adaptive implementation of a similar concept is a second proposition of the paper. Its performance is assessed in terms of wrong capture probability and compared with two other existing techniques, based on constant modulus (CM) or decision-directed (DD) algorithms. Simulation results show that the first combined scheme performs better than the separated existing techniques, while the proposed blind approach also overcomes limitations of CM and DD-based solutions.13661161

Chaotic phenomena in adaptive blind equalisers

The authors investigate the occurrence of chaotic phenomena in blind equalisers adapted by the constant modulus algorithm (CMA). It is shown that periodic and chaotic behaviour may take place during the update of the coefficients of the equaliser, for certain values of the adaptation step size, in both deterministic and stochastic versions of the algorithm. To study the stochastic CMA, an original theoretical framework is proposed, founded on a Markov chain-based modelling of the algorithm. The results reveal important features of the most useful technique for non-supervised equalisation. As far as is known, such convergence issues have not been properly explored in previous work.150636036

An improved method for signal processing and compression in power quality evaluation

This paper introduces a new waveform coding technique, based on wavelet transform, for power quality monitoring purposes. The proposed enhanced data compression method (EDCM) presents a complete adaptive signal processing approach to estimate the fundamental sinusoidal component and separate it from the transient ones in the monitored signal. When these nonstationary components are submitted to the compression technique, the sparse representation property of the wavelet transform provides an improvement in the compression ratio. Also, the degradation inserted by the lossy compression process is minimized. Simulation results confirm the effectiveness of the proposed method when compared to the standard solution, characterized by the compression of the whole monitored signal.19246447

An interconnected type-1 fuzzy algorithm for impulsive noise cancellation in multicarrier-based power line communication systems

This paper introduces an interconnected type-1 fuzzy algorithm which is trained by a modified version of the Scaled Conjugated Gradient method for impulsive noise cancellation in discrete multitone/orthogonal frequency-division multiplexing (DMT/OFDM)-based systems for broadband power line communications. The advanced algorithm makes use of the fuzzy systems capacity of dealing with uncertainties to reduce the presence of high-power impulsive noises while the DMT/OFDM technique copes with the severe intersymbol interference observed in power line channels. As a result, for a given error probability, a high number of bits can be allotted to each subchannel due to the signal-to-noise ratio enhancements achieved by the proposed fuzzy algorithm. The simulation results show that the novel fuzzy algorithm not only achieve a high data rate, but it also outperforms the standard impulsive noises techniques and other computational intelligence-based techniques, especially in the presence of additive and high-power impulsive noises.2471364137

Split Wiener filtering with application in adaptive systems

This paper proposes a new structure for split transversal filtering and introduces the optimum split Wiener filter. The approach consists of combining the idea of split filtering with a linearly constrained optimization scheme. Furthermore, a continued split procedure, which leads to a multisplit filter structure, is considered. It is shown that the multisplit transform is not an input whitening transformation. Instead, it increases the diagonalization factor of the input signal correlation matrix without affecting its eigenvalue spread. A power normalized, time-varying step-size least mean square (LMS) algorithm, which exploits the nature of the transformed input correlation matrix, is proposed for updating the adaptive filter coefficients. The multisplit approach is extended to linear-phase adaptive filtering and linear prediction. The optimum symmetric and antisymmetric linear-phase Wiener filters are presented. Simulation results enable. us to evaluate the performance of the multisplit LMS algorithm.52363664

Blind turbo receivers with fast least-squares channel estimation and soft-feedback equalisation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Low-complexity blind turbo receivers composed of a soft-feedback equaliser (SFE) and fast least-squares (FLS) channel estimators are proposed. To reduce the complexity of the SFE computation, a function approximation is proposed instead of numerical algorithms in a specific step of the equaliser's computation. Concerning FLS channel estimators, a specific filter parameters initialisation procedure is proposed in each turbo iteration to avoid possible numerical instabilities. Estimation of noise variance is also considered. The proposed scheme can perform as the turbo equaliser with perfect channel knowledge from a certain signal-to-noise ratio.462114641465Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

A fast least-squares algorithm for linearly constrained adaptive filtering

An extension of the field of fast least-squares techniques is presented. It is shown that the adaptation gain, which is updated with a number of operations proportional to the number of transversal filter coefficients, can be used to update the coefficients of a linearly constrained adaptive filter. An algorithm that is robust to round-off errors is derived. It is general and flexible. It can handle multiple constraints and multichannel signals. Its performance is illustrated by simulations and compared with the classical LMS-based Frost algorithm.4451168117