On achievable sum rate for vector Gaussian interference channels

Xiaohu Shang, Biao Chen, Michael J. Gans

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

3 Scopus citations

Abstract

We develop a procedure to compute a lower bound of the sum capacity for the vector Gaussian interference channel (IFC). The obtained lower bound is shown to be tight for the very strong interference case and the procedure can be used to construct an inner bound for the vector Gaussian IFC. Alternatively, orthogonal transmission via frequency division multiplexing is considered and we establish the concavity of the sum rate as a function of the bandwidth allocation factor for the vector channel case. Numerical examples indicate that the achievable sum rate via the superposition code compares favorably with orthogonal transmission. This improvement holds for all interference power levels, a sharp contrast to that of the scalar counterpart.

Original languageEnglish (US)
Title of host publicationProceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006
Pages2215-2219
Number of pages5
DOIs
StatePublished - Dec 1 2006
Event2006 IEEE International Symposium on Information Theory, ISIT 2006 - Seattle, WA, United States
Duration: Jul 9 2006Jul 14 2006

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8101

Other

Other2006 IEEE International Symposium on Information Theory, ISIT 2006
CountryUnited States
CitySeattle, WA
Period7/9/067/14/06

Keywords

  • Achievable rate region
  • Sum capacity
  • Vector gaussian interference channels

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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  • Cite this

    Shang, X., Chen, B., & Gans, M. J. (2006). On achievable sum rate for vector Gaussian interference channels. In Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006 (pp. 2215-2219). [4036363] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2006.261944