Coding Capacity of Discrete-Time Gaussian and Nongaussian Channels

Abstract

Coding capacity is obtained for the discrete time Gaussian channel, and upper bounds on capacity are obtained for a class of nonGaussian channels. The results apply to channels with or without memory, stationary or nonstationary. An assumption is required in order to obtain these results; this assumption is appropriate for channels without memory using an average energy constraint and for a large class of channels with memory. Keywords: Channel capacity; Shannon theory; Information theory.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1987
Accession Number
ADA190318

Entities

People

  • Charles R. Baker

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Classification
  • Coding
  • Continuous Spectra
  • Convex Sets
  • Covariance
  • Eigenvalues
  • Eigenvectors
  • Gaussian Channels
  • Hilbert Space
  • Inequalities
  • North Carolina
  • Probability
  • Random Variables
  • Spectra
  • Stochastic Processes
  • Theorems

Fields of Study

  • Engineering

Readers

  • Riverine Ecology
  • Statistical inference.