dc.description.abstract |
In data communication systems, the performance of the
receiver is generally degraded due to the presence of the
inter symbol interference (ISI) arising from the time-spread
of the transmitted pulse. A linear transversal filter with
tapped delay line (TDL) structure is normally used to combat
the effect of ISI, but the linear equalizer is not able to
cope with the severe distortion in the channel and hence, in
such situations a decision feed back equalizer (D^E) is used.
The tap coefficients of the equalizer are normally evaluated
by minimizing the output mean square error (MSE), which requires
the prior knowledge of the channel tap coefficients. Thus in
practice the equalizer's tap coefficients are adaptively
adjusted to their optimum values, using the steepest descent
algorithm. The rate of convergence of MSE, in such a situation
is slow and depends upon the channel characteristics. To speed
up the rate of convergence, several fast algorithms have been
developed during recent years and in this thesis we consider
the applications of the lattice structure for the adaptive
channel equalization.
We first consider the comparison of the error rate
performance of Kalman feed back and decision feed back equali
zers for the multilevel base band data transmission system and
it is found that the performance of the decision feed back
equalizer (DFE) is better than the performance of the Kalman
feed back equalizer in general. The DFE normally suffers from
the effect of the error propagation, which Is due to the wrong
decisions being used in the feed back filter. The evaluation
of the error bounds for the DFE is considered next using two
different approaches. The first method uses the Gauss quadra
ture rule (GQR) which requires the knowledge of the moments
of the interference and in the second method, the unknown
density function of the interference is approximated to a
known density function for the evaluation of the probability
of error.
The adaptive algorithms for the equalization of the
channel using DFE are considered next and the rate of «R
convergence of tap gain error for the estimated gradient
algorithm is analyzed and an optimum value of the step size
is evaluated. The Godard and the fast Kalman algorithms are
applied to the channel equalization and the rate of convergence
of MSE is obtained by simulation and the results are compared.
We then consider the application of the lattice structure
to the channel equalization of the carrier modulated data
transmission system. The complex least square lattice and the
complex gradient lattice algorithms are derived using the
complex gradient operator and the algorithms are simulated to
study the error rate performance and the rate of convergence of
mean square error for a variety of fixed channels for the
quadrature phase shift keyed (QPSK) system. The performance of
the lattice equalizers is compared with the performance of the
complex tapped delay line equalizer and the simulation results
are presented.
We next consider the application of the lattice structure
to the channel equalization using decision feed back equali
zation for the carrier modulated data transmission system.
The equalizer structure consists of both scalar and vector
lattice stages. The complex least square lattice and the
complex gradient lattice algorithms suitable for the above
situation are derived and simulated to obtain the probability
of error at different values of signal to noise ratio . The
rate of convergence of MSE for the deterministic channels for
the QPSK data is also obtained.
We finally consider the application of the lattice
structure as a DFE for the eoualization of fading dispersive
channel. A tapped delay line model of the channel is used,
where the tap gain coefficients are complex valued mutually
independent Gaussian random variables. The error rate perfor
mance of the complex least square lattice decision feed back
equalizer is obtained for the random fixed channels having
different power Impulse responses and for the random fading
channel with different fade rates. The performance results
evaluated by simulation are presented. |
en_US |