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Recursive estimation in time-varying communication systems


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Nicholson, Grant 1978 , 'Recursive estimation in time-varying communication systems', Unspecified thesis, University of Tasmania.

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This thesis considers applications of minimum mean-square error,
recursive estimators to equalization of time-varying digital
communication channels.
The equalization of the channel is framed as a linear state
estimation problem to which the discrete Kalman filter is applied.
The resultant equalizer, called the message estimator, yields an
unbiased, linear, minimum mean-square error estimate of the message
sequence. The message estimator models the channel as a vector, whose
elements are the sampled channel impulse response. An adaptive
Kalman filter is used in a decision feedback arrangement to estimate
on line the channel vector, and so adapt the message estimator to a
time-varying channel.
A tapped-delay-line equalizer is also investigated for minimum
mean-square error estimation of the message sequence. Recursive least
squares is modified to adaptively estimate the tap weights of the
equalizer on a time-varying channel. Recursive estimators are
considered for minimum variance of the tap weights. The recursive
least-squares equalizer, as well as a conventional steepest-descent
tapped-delay-line equalizer, are compared with the adaptive message
The message estimator and tapped-delay-line equalizer are two
different equalization approaches for a minimum mean-square error
estimate. The relation between mean-square error and error rate at
typical signal-to-noise ratios is discussed. Expressions are
developed to describe the amplitude probability distribution of the
message estimates for each scheme. The distributions are shown to
have similar properties of bias and residual intersymbol interference,
yet different error rates. The error rate of the message estimator
compares favourably with a transversal equalizer, but is significantly
higher than for a decision feedback equalizer of similar complexity.
An upper bound on the error rate for the message estimator is derived
which is simple to apply.
Computer simulation is used to test the proposed adaptive
equalizers on a time-varying channel. The convergence of the adaptive
message estimator is significantly quicker than for the recursive
least-squares equalizer, and an order of magnitude faster than for
the steepest-descent equalizer. The degradation in steady-state
performance from making the message estimator adaptive is small. The
adaptive message estimator should be particularly effective when the
channel is rapidly time-varying or the training period is restricted.

Item Type: Thesis - Unspecified
Authors/Creators:Nicholson, Grant
Keywords: Estimation theory, Least squares, Recursion theory
Copyright Holders: The Author
Copyright Information:

Copyright 1978 the author - The University is continuing to endeavour to trace the copyright
owner(s) and in the meantime this item has been reproduced here in good faith. We
would be pleased to hear from the copyright owner(s).

Additional Information:

Thesis (M.Eng.Sc.)--University of Tasmania, 1978. Bibliography: leaves 158-163

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