Higher Order Spectra and Their use in Digital Communication Signal Estimation.

Abstract

This thesis compared the detection ability of the spectrogram, the 1-1/2D instantaneous power spectrum (l-1/2Dips), the bispectrum, and outer product (dyadic) representation for digitally modulated signals corrupted by additive white Gaussian noise. Four detection schemes were tried on noise free BPSK, QPSK, FSK, and 00K signals using different transform lengths. After determining the optimum transform length, each test signal is corrupted by additive white Gaussian noise. Different SNR levels were used to determine the lowest SNR level at which the message or the modulation type could be extracted. The optimal transform length was found to be the symbol duration when processing BPSK, 00K, and FSK via the spectrogram, the 1-1/2Dips, or the bispectrum method. The best transform size for QPSK was half of the symbol length. For the outer product (dyadic) spectral representation, the best transform size was four times larger than the symbol length. For all processing techniques, with the exception of the other product representation, the minimum detectable SNR is about 15 dB for BPSK, FSK, and 00K signals and about 20 dB for QPSK signals. For the outer product spectral method, these values tend to be about 10 dB lower. (KAR) p. 2

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1995
Accession Number
ADA297717

Entities

People

  • Cihat Yayci

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Carrier Waves
  • Correlation Techniques
  • Data Science
  • Data Transmission
  • Data Transmission Systems
  • Detection
  • Digital Communications
  • Electrical Engineering
  • Frequency Shift
  • Gaussian Noise
  • Information Processing
  • Modulation
  • Power Spectra
  • Random Variables
  • Spectra
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Radio communications and signal processing.
  • Spectroscopy.
  • Statistical inference.