Automatic modulation classification for cognitive radios using cumulants based on fractional lower order statistics

M. Narendar, A. P. Vinod*, A. S.Madhu Kumar, Anoop Kumar Krishna

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

15 Citations (Scopus)

Abstract

Automatic modulation classification (AMC) finds various applications in cognitive radios. This paper presents a method for the automatic classification using cumulants derived using fractional lower order statistics. The performance of the classifier is presented in the form of probability of correct classification under noisy and fading conditions. Unlike many of the conventional methods, the proposed method does not require a priori knowledge of signal parameters. The proposed method is also more robust to different noises. Simulation results show that the proposed method can achieve better classification accuracy when compared to conventional cumulant based AMC method, in various impulsive noise conditions.

Original languageEnglish
Title of host publication2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011 - Istanbul, Turkey
Duration: 13 Aug 201120 Aug 2011

Publication series

Name2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011

Conference

Conference2011 30th URSI General Assembly and Scientific Symposium, URSIGASS 2011
Country/TerritoryTurkey
CityIstanbul
Period13/08/1120/08/11

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