On the Capacity of the Peak Power Constrained Vector Gaussian Channel: An Estimation Theoretic Perspective

Alex Dytso, Mert Al, H. Vincent Poor, Shlomo Shamai Shitz

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This paper studies the capacity of an n -dimensional vector Gaussian noise channel subject to the constraint that an input must lie in the ball of radius R centered at the origin. It is known that in this setting, the optimizing input distribution is supported on a finite number of concentric spheres. However, the number, the positions, and the probabilities of the spheres are generally unknown. This paper characterizes necessary and sufficient conditions on the constraint R, such that the input distribution supported on a single sphere is optimal. The maximum Rn, such that using only a single sphere is optimal, is shown to be a solution of an integral equation. Moreover, it is shown that Rn scales as √ n and the exact limit of Rn√n is found.

Original languageEnglish (US)
Article number8598797
Pages (from-to)3907-3921
Number of pages15
JournalIEEE Transactions on Information Theory
Volume65
Issue number6
DOIs
StatePublished - Jun 2019

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Keywords

  • Capacity
  • I-MMSE
  • amplitude constraint
  • harmonic functions
  • minimum mean square error (MMSE)
  • mutual information
  • peak-power

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