University of Lyon 2

Displaying 1-2 of 2 results

  • White Papers // Mar 2012

    Maximum Mutual Information Design for Amplify-and-Forward Multi-Hop MIMO Relaying Systems Under Channel Uncertainties

    In this paper, the authors investigate maximum mutual information design for multi-hop Amplify-and-Forward (AF) Multiple-Input Multiple-Output (MIMO) relaying systems with imperfect channel state information, i.e., Gaussian distributed channel estimation errors. The robust design is formulated as a matrix-variate optimization problem. Exploiting the elegant properties of majorization theory and matrix-variate functions,...

    Provided By University of Lyon 2

  • White Papers // Jul 2010

    Toward Active XML Data Warehousing

    Warehousing data is not a trivial task, particularly when dealing with huge amounts of distributed and heterogeneous data. Moreover, traditional decision support systems do not feature intelligent capabilities for integrating such complex data. Therefore, the authors propose an approach for intelligent decision support based on active XML warehousing. They exploit...

    Provided By University of Lyon 2

  • White Papers // Jul 2010

    Toward Active XML Data Warehousing

    Warehousing data is not a trivial task, particularly when dealing with huge amounts of distributed and heterogeneous data. Moreover, traditional decision support systems do not feature intelligent capabilities for integrating such complex data. Therefore, the authors propose an approach for intelligent decision support based on active XML warehousing. They exploit...

    Provided By University of Lyon 2

  • White Papers // Mar 2012

    Maximum Mutual Information Design for Amplify-and-Forward Multi-Hop MIMO Relaying Systems Under Channel Uncertainties

    In this paper, the authors investigate maximum mutual information design for multi-hop Amplify-and-Forward (AF) Multiple-Input Multiple-Output (MIMO) relaying systems with imperfect channel state information, i.e., Gaussian distributed channel estimation errors. The robust design is formulated as a matrix-variate optimization problem. Exploiting the elegant properties of majorization theory and matrix-variate functions,...

    Provided By University of Lyon 2