Classification of Digital Modulation Types in Multipath Environments

Abstract

As the digital communications industry continues to grow and evolve, the applications of this discipline continue to grow as well. This growth, in turn, has spawned an increasing need to seek automated methods of classifying digital modulation types. This research is a revision of previous work, using the latest mathematical software including MATLAB version 7 and Simulink(trade name). The program considers the classification of nine different modulation types Specifically, the classification scheme can differentiate between 2,- 4, and 8 PSK, 256-QAM from other types of M-QAM signals, and also M-FSK signals from PSK and QAM signals in various types of propagation channels, including multipath fading and a variety of signal-to-noise levels. This method successfully identifies these modulation types without the benefit of a priori information Higher-order statistical parameters are selected as class features and are tested in a classifier for their ability to identify the above modulation types. This study considers the effects due to realistic multipath propagation channels and additive white Gaussian noise. Using these features, and considering all fading conditions, it was determined that the classifier was correct for a randomly sent signal under randomly high or low SNR levels (low: 0dB to 8dB: high: 50dB to 100dB) over 83.9% of the time.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2008
Accession Number
ADA494488

Entities

People

  • Andrew F. Young

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Space

DTIC Thesaurus Topics

  • Amplitude Modulation
  • Communication Channels
  • Communication Systems
  • Computational Science
  • Computer Communications
  • Computer Simulations
  • Computers
  • Data Science
  • Digital Communications
  • Electrical Engineering
  • Frequency Shift
  • Gaussian Noise
  • Information Science
  • Line Of Sight
  • Machine Learning
  • Mathematical Models
  • Modulation

Fields of Study

  • Engineering

Readers

  • Economics
  • Radio communications and signal processing.
  • Regression Analysis.