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Estimation of Performance Measures from Simulation

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Simulation of Communication Systems

Part of the book series: Applications of Communications Theory ((ACTH))

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Abstract

A Monte Carlo simulation run can be viewed as a statistical experiment which is the software counterpart of an experiment on a real system. The objective of the experiment is to allow us to make inferences about one or more performance parameters. The observations (measurements) consist of discretely spaced values of a finite-duration segment of a random process at some point in the system. Hence, these measurements are inherently random. Therefore, the inferences made can only be statistical. In this chapter we study the statistical aspect of measuring performance parameters within the simulation context. The parameters that we shall specifically be concerned with are the average level, average power, signal-to-noise ratio, probability distribution and density function, bit (symbol) error probability and power spectral density. We will also briefly review some popular visual indicators of signal quality, which are often generated in a simulation to provide a qualitative sense of the performance of a digital system, but which can also be used to provide somewhat loose quantitative bounds on performance.

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Author information

Authors and Affiliations

  1. GE Aerospace, Philadelphia, Pennsylvania, USA

    Michel C. Jeruchim

  2. AT&T Bell Laboratories, Holmdel, New Jersey, USA

    Philip Balaban

  3. University of Kansas, Lawrence, Kansas, USA

    K. Sam Shanmugan

  4. Comdisco Systems, Foster City, California, USA

    K. Sam Shanmugan

Authors
  1. Michel C. Jeruchim
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  2. Philip Balaban
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  3. K. Sam Shanmugan
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© 1992 Springer Science+Business Media New York

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Jeruchim, M.C., Balaban, P., Shanmugan, K.S. (1992). Estimation of Performance Measures from Simulation. In: Simulation of Communication Systems. Applications of Communications Theory. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3298-9_5

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  • DOI: https://doi.org/10.1007/978-1-4615-3298-9_5

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6451-1

  • Online ISBN: 978-1-4615-3298-9

  • eBook Packages: Springer Book Archive

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