Numerical calculation of information rates and capacity of quadrature Gaussian mixture channels

Duc Anh Le, Hung V. Vu, Nghi H. Tran, Mustafa C Gursoy, Tho Le-Ngoc

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents novel methods to accurately calculate the information rates and capacity of quadrature Gaussian mixture (GM) noise channels without the need of time-consuming Monte Carlo simulations or numerical integrations. The focus is on three important input signals: i) a Gaussian input; ii) a complex input with discrete amplitude and independent uniform phase, which is a capacity-Achieving input; and iii) finite-Alphabet signaling schemes, such as practical quadrature amplitude modulation (QAM). To this end, a novel piecewise-linear curve fitting (PWLCF) method is first proposed to estimate the entropy of a complex GM random variable to achieve any desired level of accuracy. The result can then be used to calculate the information rate when a Gaussian input is used. For a complex input with discrete amplitude and independent uniform phase, the output entropy is estimated in a similar manner but using polar coordinates and the Kernel function. When a finite-Alphabet input is used, we exploit the Laguerre-Gauss quadrature formula for an effective calculation of the output entropy. Combining with the noise entropy, we show that in all cases, the information rates can be computed accurately.

Original languageEnglish (US)
Title of host publication2016 IEEE 6th International Conference on Communications and Electronics, IEEE ICCE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages99-104
Number of pages6
ISBN (Electronic)9781509019311
DOIs
StatePublished - Sep 7 2016
Event6th IEEE International Conference on Communications and Electronics, IEEE ICCE 2016 - Ha Long, Viet Nam
Duration: Jul 27 2016Jul 29 2016

Other

Other6th IEEE International Conference on Communications and Electronics, IEEE ICCE 2016
CountryViet Nam
CityHa Long
Period7/27/167/29/16

Keywords

  • Complex Gaussian mixture
  • discrete input
  • Gaussian input
  • information rates
  • piecewise linear approximation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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