Simplified Kalman Estimation of Fading Mobile Radio
High Performance at LMS Computational Loads.
NUTEK Workshop on Digital Communications,
Uppsala, Sweden, May 25-26, 1992.
Parameters of time-varying systems are often estimated
by adaptive algorithms with sliding time-windows,
which discount old data.
We may then face a dilemma: the use of a short data window
(or, equivalently, a large adaptation gain) results in noisy estimates.
With a long data window (small gain), time varying parameters
are tracked with a considerable delay.
To improve the accuracy, the present paper suggests
a low-complexity algorithm which takes
a priori information about the
properties of the time-variations into account,
in the form of stochastic models.
A low complexity algorithm for channel estimation in
Rayleigh fading environments is presented.
The channel estimators are presumed to operate in
conjunction with a Viterbi detector.
The algorithms are based on simplified internal
modelling of time-variant channel coefficients and
approximation of a Kalman estimator.
A novel averaging approach is used to replace the on-line
update of the Riccati equation.
Compared to RLS tracking, both a significantly lower bit
error rate and a much lower computational complexity
- Related publications:
in IEEE ICASSP'93, on the above theme.
by L Lindbom, with more details on the algorithm.
of time-varying channel coefficients in D-AMPS systems.
by L Lindbom 1995, presenting an improved general design methodology.