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Sphere decoding inspired approximation method to compute the entropy of large Gaussian mixture distributions
KTH, School of Electrical Engineering (EES), Signal Processing.
KTH, School of Electrical Engineering (EES).ORCID iD: 0000-0001-7421-0113
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-0036-9049
Huawei Technologies Sweden AB.
2014 (English)In: IEEE Workshop on Statistical Signal Processing Proceedings, 2014, 264-267 p.Conference paper, Published paper (Refereed)
Abstract [en]

The computation of mutual informations of large scale systems with finite input alphabet and Gaussian noise has often prohibitive complexities. In this paper, we propose a novel approach exploiting the sphere decoding concept to bound and approximate such mutual information term with reduced complexity and good accuracy. Using Monte-Carlo simulations, the method is numerically demonstrated for the computation of the mutual information of a frequency- and time-selective channel with QAM modulation.

Place, publisher, year, edition, pages
2014. 264-267 p.
Keyword [en]
Approximation method, Finite input alphabet, Gaussian mixture distribution, Mutual information, Sphere decoding, Approximation theory, Decoding, Gaussian noise (electronic), Intelligent systems, Signal processing, Approximation methods, Mutual informations, Stereo vision
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-167952DOI: 10.1109/SSP.2014.6884626ISI: 000361019700067Scopus ID: 2-s2.0-84907396576ISBN: 9781479949755 (print)OAI: oai:DiVA.org:kth-167952DiVA: diva2:817177
Conference
2014 IEEE Workshop on Statistical Signal Processing, SSP 2014, 29 June 2014 through 2 July 2014, Gold Coast, QLD
Note

QC 20150604

Available from: 2015-06-04 Created: 2015-05-22 Last updated: 2016-12-05Bibliographically approved

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Do, Tan TaiOechtering, Tobias J.

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf