The iterative identification method for Hammerstein nonlinear channel

This paper is concerned with the iteration identification algorithm for Hammerstein model with complex-valued input for the fact that the existing algorithms are not valid for complex input. Based on the stochastic gradient algorithm, the extended stochastic gradient algorithm is proposed by definin...

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Veröffentlicht in:10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014) S. 67 - 72
Hauptverfasser: Su, Rui, Wang, Bin, Liu, Shigang
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Stevenage, UK IET 2014
The Institution of Engineering & Technology
Schlagworte:
Communication channel equalisation and identification
Interpolation and function approximation (numerical analysis)
Other topics in statistics
Radio links and equipment
iterative methods
extended hierarchical multiinnovation stochastic gradient algorithm
identification
iterative identification method
cost function
wireless channels
stochastic processes
complex-valued input
gradient methods
Hammerstein nonlinear channel
multiinnovation identification theory
computational complexity
ISBN:1849198454, 9781849198455
Online-Zugang:Volltext
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Zusammenfassung:This paper is concerned with the iteration identification algorithm for Hammerstein model with complex-valued input for the fact that the existing algorithms are not valid for complex input. Based on the stochastic gradient algorithm, the extended stochastic gradient algorithm is proposed by defining new cost function for complex input. The extended hierarchical multi-innovation stochastic gradient algorithm is proposed by introducing multi-innovation identification theory and hierarchical principle to the extended stochastic gradient algorithm. Experimental simulations show that the extended hierarchical multi-innovation stochastic gradient algorithm has better performance than the extended stochastic gradient algorithm at the expense of computational complexity.
Bibliographie:ObjectType-Article-1
ObjectType-Feature-2
SourceType-Conference Papers & Proceedings-1
content type line 22
ISBN:1849198454
9781849198455
DOI:10.1049/ic.2014.0075