Digital Communications Systems: Test and Evaluation Studies. Volume II. Extrapolation Techniques for the Evaluation of Digital Communications Equipment.

Abstract

PRESENTAn accepted method for determining the expected performance of digital communications equipment is to obtain data experimentally from which to plot a curve of long term bit error rate versus received signal-to-noise ratio. Present procedures for obtaining complete data are very time consuming. A technique has been devised to extrapolate the desired information accurately from more readily obtainable data. The validity of the technique is established both analytically and experimentally. In order to validate the extrapolation method for obtaining the desired curves of long term bit error rate, it is necessary to prove the basic hypothesis that small variations of the internal anomalies (in digital receivers) that contribute to errors in the detection process cause lateral shifts of the curves, but the curves retain their characteristic shape depending upon the modulation scheme. This hypothesis is proved first by calculating the anomaly effects on the curves based upon theoretical analysis. Experimental verification is then obtained by examining the effects upon the curves by anomalies induced into representative items of digital communications equipment. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 31, 1979
Accession Number
ADA097123

Entities

People

  • G. R. Davis
  • L. C. Schooley

Organizations

  • University of Arizona

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Communication Systems
  • Decoding
  • Demodulation
  • Digital Communications
  • Digital Data
  • Frequency
  • Frequency Shift
  • Intersymbol Interference
  • Mathematical Filters
  • Measurement
  • Modulation
  • Radio Equipment
  • Random Variables
  • Resonant Frequency
  • Stochastic Processes
  • Test And Evaluation
  • Waveforms

Readers

  • Computational Modeling and Simulation
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Theoretical Analysis.