DocumentCode :
1551614
Title :
Efficient adaptive complex filtering algorithm with application to channel equalisation
Author :
Perry, R. ; Bull, D.R. ; Nix, A.
Author_Institution :
Centre for Commun. Res., Bristol Univ., UK
Volume :
146
Issue :
2
fYear :
1999
fDate :
8/1/1999 12:00:00 AM
Firstpage :
57
Lastpage :
64
Abstract :
The paper describes a means of efficiently implementing an adaptive complex transversal filter. Three real-coefficient filter sections are used to realise the transversal filter section of a complex equaliser, thus using one less filter than a conventional realisation. An adaptive algorithm is developed, in a manner similar to the least mean square algorithm, which allows the three filters to be trained independently and in parallel using real valued arithmetic. In this way, the throughput can be maintained, whilst reducing the number of multipliers in both the filter and coefficient update sections by 25%. Using independence theory, it is demonstrated that the three filters converge to a solution consistent with the optimal Wiener-Hopf solution. The convergence speed is characterised in terms of the complex input data stream. The transient behaviour of the algorithm is examined using a simulation of a channel equaliser and is supported by analysis
Keywords :
adaptive equalisers; adaptive filters; adaptive signal processing; convergence of numerical methods; digital arithmetic; adaptive algorithm; adaptive complex transversal filter; channel equalisation; coefficient update; complex input data stream; convergence speed; efficient adaptive complex filtering algorithm; gradient based training algorithm; independence theory; least mean square algorithm; multipliers; optimal Wiener-Hopf solution; real valued arithmetic; real-coefficient filter sections; simulation; throughput; transient behaviour;
fLanguage :
English
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
Publisher :
iet
ISSN :
1350-245X
Type :
jour
DOI :
10.1049/ip-vis:19990160
Filename :
788761
Link To Document :
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