Lower bounds on parameter modulation-estimation under bandwidth constraints

Nir Weinberger, Neri Merhav

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The problem of modulating the value of a parameter onto a band-limited signal to be transmitted over a continuous-time, additive white Gaussian noise (AWGN) channel, and estimating this parameter at the receiver, is considered. The performance is measured by the mean power-α error (MPαE), which is defined as the worst-case αth order moment of the absolute estimation error. The optimal exponential decay rate of the MPαE as a function of the transmission time, is investigated. Two upper (converse) bounds on the MPαE exponent are derived, on the basis of known bounds for the AWGN channel of inputs with unlimited bandwidth. The bounds are computed for typical values of the error moment and the signal-to-noise ratio (SNR), and the SNR asymptotics of the different bounds are analyzed. The new bounds are compared to known converse and achievability bounds, which were derived from channel coding considerations.

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Information Theory, ISIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2093-2097
Number of pages5
ISBN (Electronic)9781509040964
DOIs
StatePublished - 9 Aug 2017
Externally publishedYes
Event2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany
Duration: 25 Jun 201730 Jun 2017

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Conference

Conference2017 IEEE International Symposium on Information Theory, ISIT 2017
Country/TerritoryGermany
CityAachen
Period25/06/1730/06/17

Keywords

  • Additive white Gaussian noise
  • Bandwidth constraints
  • Modulation
  • Parameter estimation

Fingerprint

Dive into the research topics of 'Lower bounds on parameter modulation-estimation under bandwidth constraints'. Together they form a unique fingerprint.

Cite this