Excellent Performance of DFE Based on IT2SNFS in Time-Varying Channels

Author

Chang, Yao-Jen ; Ho, Chia-Lu

Author_Institution

Dept. of Commun. Eng., Nat. Central Univ., Chung-Li, Taiwan

fYear

2010

fDate

26-28 Feb. 2010

Firstpage

110

Lastpage

113

Abstract

In this paper, we incorporate an interval type-2 self-organizing neural fuzzy system (IT2SNFS) into decision feedback equalizer (DFE) for time-varying channels. By exploiting the structure and parameter learning algorithms of the IT2SNFS, the proposed DFE is able to obtain the improved performance without the estimation of the channel order. Moreover, the IT2SNFS can set conditions on the increase demand of the fuzzy rules and hence the DFE results in little hardware complexity. We show in simulations that the IT2SNFS-based DFE performs much better than the traditional DFE methods in time-varying channels.

Keywords

equalisers; fuzzy set theory; learning (artificial intelligence); self-organising feature maps; telecommunication computing; time-varying channels; decision feedback equalizer; fuzzy rules; interval type-2 self-organizing neural fuzzy system; parameter learning algorithms; time-varying channels; Bit error rate; Communication system software; Decision feedback equalizers; Finite impulse response filter; Fuzzy sets; Fuzzy systems; Hardware; Nonlinear distortion; Time-varying channels; Vectors; DFE; Time-varying channels; Type-2 fuzzy sets;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Software and Networks, 2010. ICCSN '10. Second International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-5726-7

Electronic_ISBN

978-1-4244-5727-4

Type

conf

DOI

10.1109/ICCSN.2010.51

Filename

5437620