Probabilities of False Alarm and Detection for the First-Order Cyclostationarity Test: Application to Modulation Classification

Ahmet Serbes, Huseyin Cukur, Khalid Qaraqe

Research output: Contribution to journalArticle

Abstract

Automatic modulation classification is one of the most challenging problems of cognitive radio and has significant commercial and military application. This letter focuses on blind modulation classification of first-order cyclostationary signals under a Gaussian channel. A detailed theoretical analysis of the first-order cyclostationarity test has been performed. We present the theoretical expressions of the probability of false alarm Pfa and the probability of detection Pd as a function of the selected threshold for the first-order cyclostationarity test based constant false alarm rate detector. The Pd is presented for only AM and M-FSK signals, which are the only signals that possess first-order cyclostationary features. Theoretical formulations presented in this letter are validated by extensive simulation results.

Original languageEnglish
Article number8866723
Pages (from-to)57-61
Number of pages5
JournalIEEE Communications Letters
Volume24
Issue number1
DOIs
Publication statusPublished - Jan 2020

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Keywords

  • automatic modulation classification
  • blind modulation identification
  • First-order cyclostationarity test

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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