Probability of Error Analysis Using a Gauss-Chebyshev Quadrature Rule

Abstract

One of the most important steps in designing a communication system involves analyzing the error performance of the system to determine if it meets requirements. There are many techniques to accomplish such analysis and the most desirable one is that which can be used quickly and efficiently. This thesis examines one method of error performance analysis that utilizes the two sided Laplace transform of the probability density function (PDF) of a decision statistic. Additionally, a Gauss-Chebyshev quadrature rule is utilized to attain the error probability. This method is used to find the error performance of several communication systems of varying complexity in order to verify the use of the method and investigate its implementation. The models considered are antipodal baseband signaling in additive white Gaussian noise (AWGN), BPSK in AWGN and an imperfect carrier reference in the receiver, and BPSK and NFSK in AWGN with Rayleigh fading. The results are implemented using a computer and are compared to known results. All results are shown to match theoretical results. Additionally, up to a 99% computational time savings was realized using this method to analyze error performance of the BPSK case with an imperfect carrier reference in the receiver.

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Document Details

Document Type
Technical Report
Publication Date
Jun 30, 1999
Accession Number
ADA366385

Entities

People

  • Michael J. Radermacher

Organizations

  • University of Colorado, at Colorado Springs

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Communication Channels
  • Communication Systems
  • Computational Science
  • Computer Simulations
  • Digital Communications
  • Error Analysis
  • Errors
  • Frequency
  • Frequency Shift
  • Gaussian Distributions
  • Gaussian Noise
  • Numerical Integration
  • Probability
  • Probability Density Functions
  • Random Variables
  • Simulations

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Radio communications and signal processing.
  • Statistical inference.