On optimal training and beamforming in uncorrelated MIMO systems with feedback

Francisco Rubio*, Dongning Guo, Michael L Honig, Xavier Mestre

*Corresponding author for this work

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

3 Scopus citations

Abstract

This paper studies the design and analysis of optimal training-based beamforming in uncorrelated multiple-input multiple-output (MIMO) channels with known Gaussian statistics. First, given the response of the MIMO channel to a finite sequence of training vectors, the beamforming vector which maximizes the average received signal-to-noise ratio (SNR) over all channel realizations is found. Secondly, the question of what consists of optimal training for a given amount of training is addressed. Upper and lower bounds for the maximum achievable SNR using beamforming are established. Furthermore, optimal training sequences are conjectured to satisfy the Welch bound. The conjecture is supported by the evidence that such sequences achieve close to the upper bound with moderate to large amount of trainings.

Original languageEnglish (US)
Title of host publicationCISS 2008, The 42nd Annual Conference on Information Sciences and Systems
Pages902-907
Number of pages6
DOIs
StatePublished - Sep 22 2008
EventCISS 2008, 42nd Annual Conference on Information Sciences and Systems - Princeton, NJ, United States
Duration: Mar 19 2008Mar 21 2008

Other

OtherCISS 2008, 42nd Annual Conference on Information Sciences and Systems
CountryUnited States
CityPrinceton, NJ
Period3/19/083/21/08

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'On optimal training and beamforming in uncorrelated MIMO systems with feedback'. Together they form a unique fingerprint.

Cite this