Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters

Author

Liang, Qilian ; Mendel, Jerry M.

Author_Institution

Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA

Volume

8

Issue

5

fYear

2000

fDate

10/1/2000 12:00:00 AM

Firstpage

551

Lastpage

563

Abstract

Presents a kind of adaptive filter: type-2 fuzzy adaptive filter (FAF); one that is realized using an unnormalized type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system (FLS). We apply this filter to equalization of a nonlinear time-varying channel and demonstrate that it can implement the Bayesian equalizer for such a channel, has a simple structure, and provides fast inference. A clustering method is used to adaptively design the parameters of the FAF. Two structures are used for the equalizer: transversal equalizer (TE) and decision feedback equalizer (DFE). A decision tree structure is used to implement the decision feedback equalizer, in which each leaf of the tree is a type-2 FAF. This DFE vastly reduces computational complexity as compared to a TE. Simulation results show that equalizers based on type-2 FAFs perform much better than nearest neighbor classifiers (NNC) or equalizers based on type-1 FAFs

Keywords

adaptive filters; computational complexity; decision feedback equalisers; decision trees; fuzzy logic; fuzzy set theory; inference mechanisms; time-varying channels; Bayesian equalizer; clustering method; decision feedback equalizer; fast inference; nonlinear time-varying channels; transversal equalizer; type-2 fuzzy adaptive filters; unnormalized type-2 Takagi-Sugeno-Kang fuzzy logic system; Adaptive filters; Bayesian methods; Clustering methods; Decision feedback equalizers; Fuzzy logic; Fuzzy systems; Takagi-Sugeno-Kang model; Tellurium; Time-varying channels; Transversal filters;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/91.873578

Filename

873578