Reliability Improvement of Digital Communication using Redundancy in Uncertainty Region Reception

Abstract

An efficient method is considered for utilizing the redundancy of the transmittible language to improve the reliability of a digital communication system disturbed by additive non-white gaussian noise. Namely, the reliability of digital systems using orthogonal and binary digit codes is improved by introducing an uncertainty region at the receiver. This method is an extension and generalization of null-zone reception previously applied to the improvement of binary transmission in the presence of white gaussian or peak-limited noise. It is shown that, by permitting a small percentage of nulls to be printed, considerable improvement in reliability is achieved. In addition, it is shown that communication links using orthogonal digit coding afford greater reliability than corresponding links using binary digit coding. Performance results are given for several different codes for the case in which the demodulated gaussian noise power density spectrum increases with increasing frequency Such a noise power density spectrum acts as a weighting function which confines the generated signals to the available band of frequencies. A geometric interpretation of the results is given in terms of n-dimensional Euclidean space.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1963
Accession Number
AD0414370

Entities

People

  • Ludwik Kurz

Organizations

  • New York University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Bandwidth
  • Bits
  • Closed Loop Systems
  • Computer Programming
  • Correlation Techniques
  • Detection
  • Differential Equations
  • Electrical Engineering
  • Engineering
  • Engineers
  • Equations
  • Frequency
  • Gaussian Noise
  • Integral Equations
  • Mathematical Filters
  • Probability
  • Random Variables

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Radio communications and signal processing.
  • Statistical inference.

Technology Areas

  • Space