Modulation classification for M-ary CPM signals: Based on PAM decomposition and phase detection methods

Chih Ping Tsu, Dah Chung Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We study new modulation classification methods for M-ary CPM signals based on the average likelihood ratio test (ALRT) approach. It is well-known that the M-ary CPM signal can be decomposed into the superposition of multiple PAM waveforms. In this paper, we apply the decomposed PAM waveforms for CPM classification through ALRT. However, to detect the CPM signals costs a high complexity because the PAM decomposition method requires multiple filters to match the PAM waveforms. Hence, we propose a new phase detection method which has lower complexity. In addition, we analyze the phase noise in the phase detection method to insure the prerequisite of applying the ALRT approach for modulation classification. Simulation results show that the new M-ary CPM classification method has satisfying probability of correct classification when SNR is beyond 0 dB.

Original languageEnglish
Title of host publication2011 20th International Conference on Computer Communications and Networks, ICCCN 2011 - Proceedings
DOIs
StatePublished - 2011
Event2011 20th International Conference on Computer Communications and Networks, ICCCN 2011 - Maui, HI, United States
Duration: 31 Jul 20114 Aug 2011

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
ISSN (Print)1095-2055

Conference

Conference2011 20th International Conference on Computer Communications and Networks, ICCCN 2011
Country/TerritoryUnited States
CityMaui, HI
Period31/07/114/08/11

Keywords

  • Average likelihood ratio test
  • continuous phase modulation (CPM)
  • modulation classification
  • PAM
  • phase detection

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