Sum-rate of MIMO broadcast channels with one bit feedback

Jordi Diaz, Osvaldo Simeone, Yeheskel Bar-Ness

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

27 Scopus citations

Abstract

The sum-capacity of a multi-antenna broadcast Gaussian channel is known to be achieved by Dirty Paper Coding techniques, or, asymptotically in the number of users n, by beamforming methods, that require full channel state information at the base station. Based on the opportunistic beamforming principle, it has been recently shown that the optimal scaling law of the sum-rate with respect to n, for fixed signal to noise ratio and number of transmitting antennas M, (i.e., M log log n) can be achieved by employing a feedback of only one real and one integer number per user. Moreover, it was proved that a linear scaling with respect of M can be guaranteed only if M scales no faster than logrt. In this paper, the optimal scaling law of the sum-rate with respect to n is proved to be achievable with only one bit of feedback per user. The proof builds on opportunistic beamforming and binary quantization of the signal to noise plus interference ratio. Moreover, the linear scaling of the sum-rate with M is demonstrated to hold for M growing no faster than logrt even with such a reduced feedback. Finally, the results above are extended to the MIMO case, where each user is equipped with multiple antennas.

Original languageEnglish (US)
Title of host publicationProceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006
Pages1944-1948
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
Country/TerritoryUnited States
CitySeattle, WA
Period7/9/067/14/06

All Science Journal Classification (ASJC) codes

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

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