By Topic

Fractionally-spaced blind channel equalisation using hidden Markov models

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
$31 $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)
Krishnamurthy, V. ; Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia ; Dogancay, Kutluyil

The paper presents a maximum likelihood (ML) blind channel equalisation algorithm based on the expectation-maximisation (EM) algorithm. We assume that the channel input sequence is a finite-state Markov chain and the channel output sequence is obtained from the continuous-time channel output by oversampling it at a rate higher than the channel input symbol rate, which leads to a fractionally-spaced channel equalisation problem. The objective of blind channel equalisation is to estimate the channel input symbols without explicit knowledge of the channel characteristics and the requirement of training data. The availability of multichannel outputs for the same channel input improves the reliability of the estimates. A reduced-cost blind equalisation algorithm which draws on aggregation by stochastic complementation is also proposed. A simulation example is presented to demonstrate the performance of the proposed algorithms

Published in:

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on  (Volume:5 )

Date of Conference:

21-24 Apr 1997