Abstract.
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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Date received: July 23, 1998. Date revised: August 26, 1999.
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Hansson, A., Wahlberg, B. Continuous-Time Blind Channel Deconvolution Using Laguerre Shifts. Math. Control Signals Systems 13, 333–346 (2000). https://doi.org/10.1007/PL00009873
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DOI: https://doi.org/10.1007/PL00009873