NDLI: Recursive least squares algorithm for blind deconvolution of channels with cyclostationary inputs

Content Provider	IEEE Xplore Digital Library
Author	Ilow, J. Hatzinakos, D.
Copyright Year	1993
Description	Author affiliation: Dept. of Electr. Eng., Toronto Univ., Ont., Canada (Ilow, J.; Hatzinakos, D.)
Abstract	The authors propose a new discrete time blind deconvolution technique for linear channels driven by cyclostationary inputs. This problem arises in digital communications, seismic signal processing, and many other applications. In particular, homomorphic approaches are applied to the cyclic autocorrelation of the fractionally-spaced sampled output of the channel. First, the method identifies the differential cepstrum parameters of the complex channel by means of a recursive least squares (RLS) algorithm. The RLS algorithm is based on the special characteristics of a cyclic autocorrelation matrix and an appropriate matrix inversion lemma. Once the differential cepstrum parameters are recovered, then the impulse response of the channel/equalizer is obtained by simple recursive formulas. Only partial information is required, i.e., the cyclic period and the distribution of the input data. It is shown that the method can directly identify the characteristics of either the channel or its inverse, provided that an unknown channel satisfies a special condition. The method is evaluated by means of computer simulations and is found to perform efficiently.
Starting Page	123
Ending Page	127
File Size	448759
Page Count	5
File Format	PDF
ISBN	0780309537
DOI	10.1109/MILCOM.1993.408534
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-10-11
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Least squares methods Deconvolution Signal processing algorithms Autocorrelation Cepstrum Resonance light scattering Digital communication Digital signal processing Equalizers Computer simulation
Content Type	Text
Resource Type	Article

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