• DocumentCode
    862724
  • Title

    Intrinsic Subspace Convergence in TDD MIMO Communication

  • Author

    Dahl, Tobias ; Pereira, Silvana Silva ; Christophersen, Nils ; Gesbert, David

  • Author_Institution
    Dept. of Informatics, Univ. of Oslo, Blindern
  • Volume
    55
  • Issue
    6
  • fYear
    2007
  • fDate
    6/1/2007 12:00:00 AM
  • Firstpage
    2676
  • Lastpage
    2687
  • Abstract
    In numerical linear algebra, students encounter early the iterative power method, which finds eigenvectors of a matrix from an arbitrary starting point through repeated normalization and multiplications by the matrix itself. In practice, more sophisticated methods are used nowadays, threatening to make the power method a historical and pedagogic footnote. However, in the context of communication over a time-division duplex (TDD) multiple-input multiple-output (MIMO) channel, the power method takes a special position. It can be viewed as an intrinsic part of the uplink and downlink communication switching, enabling estimation of the eigenmodes of the channel without extra overhead. Generalizing the method to vector subspaces, communication in the subspaces with the best receive and transmit signal-to-noise ratio (SNR) is made possible. In exploring this intrinsic subspace convergence (ISC), we show that several published and new schemes can be cast into a common framework where all members benefit from the ISC
  • Keywords
    MIMO communication; convergence; eigenvalues and eigenfunctions; iterative methods; matrix algebra; telecommunication switching; wireless channels; TDD MIMO communication; communication switching; eigenmode estimation; intrinsic subspace convergence; iterative power method; matrix eigenvectors; numerical linear algebra; signal-to-noise ratio; time-division duplex multiple-input multiple-output channel; vector subspaces; Communication switching; Context; Convergence; Downlink; Eigenvalues and eigenfunctions; Iterative methods; Linear algebra; MIMO; Signal to noise ratio; Singular value decomposition; Channel identification; eigenmodes; multiple-input multiple-output (MIMO) systems; singular modes; singular value decomposition (SVD);
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2007.896901
  • Filename
    4203059