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Continuous-time blind channel deconvolution using Laguerre shiftsPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
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PrimeFaces.cw("AccordionPanel","widget_formSmash_responsibleOrgs",{id:"formSmash:responsibleOrgs",widgetVar:"widget_formSmash_responsibleOrgs",multiple:true}); 2000 (English)In: Mathematics of Control, Signals, and Systems, ISSN 09324194 (ISSN), Vol. 13, no 4, 333-346 p.Article in journal (Refereed) Published
##### Abstract [en]

##### Place, publisher, year, edition, pages

2000. Vol. 13, no 4, 333-346 p.
##### Keyword [en]

Communication channels (information theory), Equalizers, Error analysis, FIR filters, Intersymbol interference, Mathematical models, Perturbation techniques, Spurious signal noise, Continuous-time blind channel deconvolution, Laguerre shifts, Signal filtering and prediction
##### National Category

Control Engineering
##### Identifiers

URN: urn:nbn:se:kth:diva-55408OAI: oai:DiVA.org:kth-55408DiVA: diva2:471626
#####

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##### Note

References: Bokor, J., Heuberger, P., Ninness, B., Oliveira E Silva, T., Van Den Hof, P., Wahlberg, B., Modelling and identification with orthogonal basis functions (1999) Workshop Notes, 14th IFAC World Congress, Workshop Nro. 6, , Beijing, July; Brockett, R.W., (1970) Finite Dimensional Linear Systems, , Wiley, New York; Cedervall, M., (1997) Subspace and Maximum Likelihood Estimation for Systems and Signal Modelling, , Doctoral Dissertation ISBN 91-506-1208-5, Systems and Control Group, School of Engineering, Uppsala University, Uppsala; Endres, T.J., Halford, S.D., Johnson C.R., Jr., Giannakis, G.B., Simulated comparisons of blind equalization algorithms for cold start-up applications (1998) International Journal of Adaptive Control and Signal Processing, 12 (3), pp. 283-301; Giannakis, G.B., Halford, S.D., Blind fractionally spaced equalization of noisy FIR channels: Direct and indirect solutions (1997) IEEE Transactions on Signal Processing, 45 (9), pp. 2277-2292; Lee, Y.W., (1960) Statistical Theory of Communication, , Wiley, New York; Luo, H., Li, Y., The application of blind channel identification technique to prestack seismic deconvolution (1998) Proceedings of the IEEE, 86 (10), pp. 2082-2089; Liu, H., Xu, G., Tong, L., Kailath, T., Recent developments in blind channel equalization: From cyclostationarity to subspaces (1996) Signal Processing, 50, pp. 83-99; Moulines, E., Duhamel, P., Cardoso, J.-F., Mayrargue, S., Subspace methods for the blind identification of multichannel FIR filters (1995) IEEE Transactions on Signal Processing, 43 (2), pp. 516-525; Proakis, J.G., Masoud, S., (1994) Communication Systems Engineering, , Prentice-Hall, Englewood Cliffs, NJ; Shen, J., Ding, Z., Direct blind MMSE channel equalization based on second-order statistics (2000) IEEE Transactions on Signal Processing, 48 (4), pp. 1015-1022; Tong, L., Perreau, S., Multichannel blind identification: From subspace to maximum likelihood methods (1998) Proceedings of the IEEE, 86 (10), pp. 1951-1968; Wahlberg, B., System identification using Kautz models (1994) IEEE Transactions on Automatic Control, 39 (6), pp. 1276-1281; Wiener, N., (1949) Extrapolation, Interpolation, and Smoothing of Stationary Time Series with Engineering Applications, , Wiley, New York NR 20140805Available from: 2012-01-02 Created: 2012-01-02 Last updated: 2013-09-05Bibliographically approved

The objective of this paper is to study the problem of continuous-time blind deconvolution of a pulse amplitude modulated signal propagated over an unknown channel and perturbed by additive noise. The main idea is to use so-called Laguerre filters to estimate a continuous-time model of the channel. Laguerre-filter-based models can be viewed as an extension of finite-impulse-response (FIR) models to the continuous-time case, and lead to compact and parsimonious linear-in-the-parameters models. Given an estimate of the channel, different symbol estimation techniques are possible. Here, the shift property of Laguerre filters is used to derive a minimum mean square error estimator to recover the transmitted symbols. This is done in a way that closely resembles recent FIR-based schemes for the corresponding discrete-time case. The advantage of this concept is that physical a priori information can be incorporated in the model structure, like the transmitter pulse shape.

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