By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ilow, J. ; Dept. of Electr. Eng., Toronto Univ., Ont., Canada ; Hatzinakos, D.

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

Published in:

Military Communications Conference, 1993. MILCOM '93. Conference record. Communications on the Move., IEEE  (Volume:1 )

Date of Conference:

11-14 Oct 1993