Cyclostationarity-based modulation classification of linear digital modulations in flat fading channels

Octavia A. Dobre, Ali Abdi, Yeheskel Bar-Ness, Wei Su

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

Modulation classification is an intermediate step between signal detection and demodulation, and plays a key role in various civilian and military applications. In this correspondence, higher-order cyclic cumulants (CCs) are explored to discriminate linear digital modulations in flat fading channels. Single- and multi-antenna CC-based classifiers are investigated. These benefit from the robustness of the CC-based features to unknown phase and timing offset. Furthermore, the latter provides significant performance improvement due to spatial diversity used to combat the fading effect. Classifier performances are investigated under a variety of channel conditions. In addition, analytical closed-form expressions for the cyclic cumulant polyspectra of linearly digitally modulated signals affected by fading, carrier frequency and timing offsets, and additive Gaussian noise are derived, along with a condition for the oversampling factor to avoid aliasing in the cycle and spectral frequency domains.

Original languageEnglish (US)
Pages (from-to)699-717
Number of pages19
JournalWireless Personal Communications
Volume54
Issue number4
DOIs
StatePublished - Sep 2010

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Antenna arrays
  • Automatic modulation classification
  • Cycle aliasing
  • Higher-order cyclic statistics
  • Probability of correct classification
  • Selection combining

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