The interplay between estimation theory and information theory

Sergio Verdu

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

For signals observed in Gaussian noise, there are several interesting intersections between information theory and linear and nonlinear minimum mean-square error (MMSE) estimation. We unveil a new relationship between the input-output mutual information and the MMSE achievable by the optimal estimator of the input. This relationship holds for arbitrarily distributed scalar and vector signals, as well as for discrete-time and continuous-time noncausal MMSE estimation (smoothing). We will also focus on two applications of these information theoretic results: the mercury/waterfilling formula for power allocation with arbitrary input constellations; and a universal continuous-time nonlinear filtering formula that couples the signal-to-noise ratios achievable by smoothing and filtering.

Original languageEnglish (US)
DOIs
StatePublished - Dec 1 2005
Event2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2005 - New York, NY, United States
Duration: Jun 5 2005Jun 8 2005

Other

Other2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2005
CountryUnited States
CityNew York, NY
Period6/5/056/8/05

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Engineering(all)

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