AMC using cumulants with segmentation of input sequence for dispersive fading channels

Author

Markovic, Goran B. ; Dukic, Miroslav L.

Author_Institution

Sch. of Electr. Eng., Univ. of Belgrade, Belgrade, Serbia

fYear

2013

fDate

26-28 Nov. 2013

Firstpage

228

Lastpage

231

Abstract

In this paper, we present an analysis of AMC algorithms based on fourth-order cumulants with additional segmentation of input sequence introduced here in order to improve cumulant estimate quality. We here observe several possible solutions that are based on combining of cumulant estimates derived independently for the particular segments. The performances of the examined AMC solutions coupled with two channel estimation methods are evaluated through Monte-Carlo trials for different dispersive fading channels.

Keywords

Monte Carlo methods; channel estimation; cognitive radio; fading channels; AMC algorithms; Monte-Carlo trials; automatic modulation classification; channel estimation methods; cognitive radio networks; cumulant estimate quality; dispersive fading channels; fourth-order cumulants; input sequence; Artificial neural networks; Channel models; Gain; Phase shift keying; Signal to noise ratio; Wireless sensor networks; Automatic modulation classification (AMC); dispersive fading channels; higher-order cumulants;

fLanguage

English

Publisher

ieee

Conference_Titel

Telecommunications Forum (TELFOR), 2013 21st

Conference_Location

Belgrade

Print_ISBN

978-1-4799-1419-7

Type

conf

DOI

10.1109/TELFOR.2013.6716214

Filename

6716214