1,720,968 research outputs found
A Bayesian approach to blind equalization using fractional sampling
No full textThe optimum design of blind fractionally spaced equalizers is addressed in the framework of a Bayesian approach. The resulting iterative, Bussgang-like equalizer design incorporates constraints on the overall channel-equalizer response in order to meet Nyquist characteristic (raised cosine). The experienced convergence robustness also results in increased accuracy
Bussgang-zero crossing equalization: An integrated HOS-SOS approach
No full textIn this paper, an integrated higher order statistics (HOS) and second order statistics (SOS) based equalization technique is presented as an extension of the Bussgang equalization algorithm. This extension allows the simultaneous taking into account of the statistical knowledge about the data source, as done in the conventional HOS approaches and, in particular, by Buss-gang-like equalization algorithms such as super exponential, constant modulus, etc., and the spectral redundancy usually present in pulse-amplitude modulation (PAM) and quadrature-amplitude modulation (QAM) modulated signals, exploited by SOS-based approaches. The technique presented here employs a new form of SOS equalization that naturally inserts into the Bussgang scheme. It is based on a zero crossing (ZC) property of the received signal when it is passed through a suitable filter. The novel equalization scheme is presented in a Bayesian estimation framework, after illustration of the general Bussgang paradigm and of the principles of the ZC approach. From simulated experiments, it results that the extended Bussgang-ZC equalizer not only outperforms conventional Bussgang equalizers but is also robust to situations where HOS and SOS approaches individually fail
Gain-control-free blind carrier frequency offset acquisition for QAM constellations
No full textThis paper introduces a novel blind frequency offset estimator for quadrature amplitude modulated (QAM) signals. Specifically, after a preliminary frequency compensation, the estimator is based on the pi/2-folded phase histogram of the received data. Then, the frequency offset estimate is taken as the frequency compensation value that minimizes the mean square error between the phase histogram measured on the received samples and the reference phase probability density function analytically calculated in the case of zero frequency offset. The pi/2-folded phase histogram of the received data is here called Constellation Phase Signature, since it definitively characterizes the phase distribution of signal samples belonging to a particular QAM constellation, and it has already been employed to develop a gain-control-free phase estimator that well performs both for square and cross constellations. Also the here described frequency offset estimator has the remarkable property to be gain-control-free and, thus, it can be fruitfully employed in frequency acquisition stages. The asymptotic performance of the estimator has been analytically evaluated and assessed by numerical simulations. Theoretical analysis and numerical results show that the novel frequency offset estimator outperforms state-of-the art estimators in a wide range of signal-to-noise ratio (SNR) values
Semiblind bussgang equalization for sparse channels
No full textIn this correspondence, we describe a semiblind Bussgang equalization scheme that incorporates the training sequence in a quite direct and flexible fashion. Among others, we discuss how the training sequence can be used to control the Bussgang nonlinearity thus enforcing the convergence of the iterative equalizer design. Moreover, we focus on the case of channels whose impulse response is long but sparse, counteracted by equalizers designed on a suitable sparse support. Numerical performance analysis conducted on compact and sparse time-varying channels shows that sparse Bussgang semiblind equalizer using a short training sequence outperforms blind, trained, and decision directed equalizers in a variety of fading conditions
Blind phase recovery for QAM communication systems
No full textIn this paper, a novel phase estimator that can be employed for both square and cross Quadrature Amplitude Modulation (QAM) based digital transmission is presented. It does not need gain control and requires only the knowledge of the type of the transmitted symbol constellation, i.e., square or cross. It is based on the evaluation of the fourth power of the received data and the measurement of the orientation of the concentration ellipses of the bivariate Gaussian distribution having the same second-order moments. The analytical evaluation of the estimation error as well as of the asymptotic variance is provided. Experimental results outline,the good performance of the estimator described here, which is superior to that of well-known phase estimation methods. Finally, it is outlined how the eccentricity of the concentration ellipses can be used to devise a test for detecting the constellation. type
Blind equalization for correlated input symbols: A Bussgang approach
No full textThis paper addresses the problem of blind equalization in the case of correlated input symbols, and it shows how the knowledge of the symbol sequence probability distribution can be directly incorporated in a Bussgang blind equalization scheme. Numerical results pertaining to both linear and nonlinear modulation schemes show that a significant improvement in equalization performance is obtained by exploiting the symbol sequence probability distribution using the approach herein described
High SNR performance analysis of a blind frequency offset estimator for cross QAM communication
No full textIn this paper we present theoretical performance analysis for a blind frequency offset estimator for cross Quadrature Amplitude Modulated constellations. The estimator is based on applying a tentative frequency offset compensation by means of a nonlinear transformation of the received signal samples and on estimating an accumulation function in different angular windows. For perfect frequency offset compensation, the measurements are suitably clustered and their accumulation, named "Constellation Phase Signature" (CPS), is a peaked function of the window orientation. Hence, the frequency offset estimator is selected by maximization of the peakness of the accumulation function The performance analysis is shown to match the numerical simulations for medium to high values of SNR. ©2008 IEEE
Blind image deblurring driven by nonlinear processing in the edge domain
No full textThis work addresses the problem of blind image deblurring, that is, of recovering an original image observed through one or more unknown linear channels and corrupted by additive noise. We resort to an iterative algorithm, belonging to the class of Bussgang algorithms, based on alternating a linear and a nonlinear image estimation stage. In detail, we investigate the design of a novel nonlinear processing acting on the Radon transform of the image edges. This choice is motivated by the fact that the Radon transform of the image edges well describes the structural image features and the effect of blur, thus simplifying the nonlinearity design. The effect of the nonlinear processing is to thin the blurred image edges and to drive the overall blind restoration algorithm to a sharp, focused image. The performance of the algorithm is assessed by experimental results pertaining to restoration of blurred natural images
MARKOV MODEL OF H.264 VIDEO SOURCES PERFORMING BIT-RATE SWITCHING
No full textFast and bit-saving video bit-rate switching is an important issue in video streaming systems on a time varying channel as the one offered by a wireless mesh network, or the one sensed during a vertical handover. The recent H.264 video coding standard supports the seamless switching among bitstreams coded at different bit-rates by means of suitably coded frames, named Switching Pictures. This work addresses the modelling of the traffic generated by a H.264 source performing bit-rate switching using SP frames. The H.264 source is modelled by a Markov chain where each state models the generation of an entire Group Of Pictures (GOP), and is characterized by the kind of SP frame encoded in the GOP. Interframe correlation, typical of video sources, is suitably taken into account by the interstate dependence. The accuracy of the model is assessed by comparison of the cell loss rate of a fixed size buffer filled with a synthetic source according to the model herein proposed, with a state of the art AR model and with a real H.264 video codec. © 2008 IEEE
Reduced complexity rotation-invariant texture classification using a blind deconvolution approach
No full textIn this paper, we present a texture classification procedure that makes use of a blind deconvolution approach. Specifically, the texture is modeled as the output of a linear system driven by a binary excitation. We show that features computed from one-dimensional slices extracted from the two-dimensional autocorrelation function (ACF) of the binary excitation allows representing the texture for rotation-invariant classification purposes. The two-dimensional classification problem is thus reconduced to a more simple one-dimensional one, which leads to a significant reduction of the classification procedure computational complexity
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