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dc.contributor.advisorSawan, M. Edwinen_US
dc.contributor.authorKhasawneh, Mohammad Naser Fawwazen_US
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Scienceen_US
dc.description.abstractChannel estimation problem is a crucial state of the art research topic that has been addressed in the literature for the past decade. The importance of such research area emerged from the fact that telecommunication scholars are searching for a wireless telecommunication system that provides a minimum error performance yet can utilize the used spectrum efficiently. Channel estimation is a common practice in most of the wireless communication systems to give the receiver an indication about the channel conditions and hence will affect his decision in detecting the transmitted information This thesis will Compare Four methods for Channel estimation problems based in semi-blind approach for MU-MIMO systems; the Rank Revealing QR factorization RRQR, Least square method LS, CAPON method and the Eigenvector method. Performance comparison is based on the Minimum mean square error (MMSE). The introduced method in this thesis is the Eigenvector method, and it's presented in comparison to the first three methods. Compared to the RRQR the Eigenvector is based on a searching function similar to the MUSIC function with the addition of the Eigen values of the null space in the search function.en_US
dc.format.extentxi, 44 p.en_US
dc.format.extent708344 bytes
dc.publisherWichita State Universityen_US
dc.titleComparison study for multi-user MIMO channel estimation techniquesen_US

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  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • EECS Theses and Dissertations
    Collection of Master's theses and Ph.D. dissertations completed at the Dept. of Electrical Engineering and Computer Science
  • Master's Theses
    This collection includes Master's theses completed at the Wichita State University Graduate School (Fall 2005 --)

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