On gaussian MIMO BC-MAC duality with multiple transmit covariance constraints

Lan Zhang, Rui Zhang, Ying Chang Liang, Xintt Van, H. Vincent Poor

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

25 Scopus citations

Abstract

The conventional Gaussian multiple-input multipleoutput (MIMO) broadcast channel (BC)- multiple-access channel (MAC) duality has previously been applied to solve non-convex BC capacity computation problems. However, this conventional duality approach is applicable only to the case in which the base station (BS) of the BC is subject to a single sum-power constraint. An alternative approach is the minimax duality, established by Yu in the framework of Lagrange duality, which can be applied to solve the per-antenna power constraint case. This paper first extends the conventional BC-MAC duality to the general linear transmit covariance constraint (LTCC) case, and thereby establishes a general BC-MAC duality. This new duality is then applied to solve the BC capacity computation problem with multiple LTCCs. Moreover, the relationship between this new general BC-MAC duality and the minimax duality is also presented, and it is shown that the general BC-MAC duality has a simpler form. Numerical results are provided to illustrate the effectiveness of the proposed algorithm.

Original languageEnglish (US)
Title of host publication2009 IEEE International Symposium on Information Theory, ISIT 2009
Pages2502-2506
Number of pages5
DOIs
StatePublished - 2009
Event2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul, Korea, Republic of
Duration: Jun 28 2009Jul 3 2009

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8102

Other

Other2009 IEEE International Symposium on Information Theory, ISIT 2009
Country/TerritoryKorea, Republic of
CitySeoul
Period6/28/097/3/09

All Science Journal Classification (ASJC) codes

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

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