Title :
Fast-convergence filtered regressor algorithms for blind equalisation
Author :
Douglas, S.C. ; Cichocki, Andrzej ; Amari, S.
Author_Institution :
Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA
fDate :
11/7/1996 12:00:00 AM
Abstract :
The authors present a simple extension of the standard Bussgang blind equalisation algorithms that significantly improves their convergence properties. The technique uses the inverse channel estimate to filter the regressor signal. The modified algorithms provide quasi-Newton convergence in the vicinity of a local minimum of the chosen cost function with only a modest increase in the overall computational complexity of the system. An example of the technique as applied to the constant-modulus algorithm indicates its superior convergence behaviour
Keywords :
computational complexity; convergence of numerical methods; deconvolution; equalisers; filtering theory; signal processing; blind equalisation; computational complexity; constant-modulus algorithm; convergence properties; cost function; fast-convergence algorithms; filtered regressor algorithms; inverse channel estimate; local minimum; quasi-Newton convergence;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19961414