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Filtering by: Advisor Magana, Mario Remove constraint Advisor: Magana, Mario Subject MIMO systems Remove constraint Subject: MIMO systems

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  • Massive MIMO Channel Characterization

    Creator:
    Assiri, Mohammad
    Abstract:
    It has been estimated that data traffic from the different mobile devices that range from smartphones to machine-to-machine (M2M) devices will exceed 15.9 exabyte per month by the year 2018. With this immense data growth, the current wireless communication systems suffer from the scarcity of the radio spectrum and eventually...
    Resource Type:
    Masters Thesis
    Full Text:
    : Massive MIMO Channel Characterization Abstract approved: Mario E. Magaña It has been estimated that

  • Multi-User Massive MIMO Channel Estimation Based on Kalman Filters

    Creator:
    Yao, Zhaoda
    Abstract:
    In wireless communication, channel state information (CSI) is essential for data detection. Fast fading coefficients estimation is important in order to acquire accurate CSI. Kalman filters (KF) are widely used for real time parameter estimation and can be used to estimate the fast fading coefficients of a mobile communication channel....
    Resource Type:
    Masters Thesis
    Full Text:
    Mario E. Magaña In wireless communication, channel state information (CSI) is essential for data

  • Channel Estimation in TDD Massive MIMO Systems with Subsampled Data at BS

    Creator:
    Tian, Yichuan
    Abstract:
    Massive MIMO is a promising technique for future 5G communications due to its high spectrum and energy efficiency. To realize its potential performance gain, accurate channel state information at transmitter side (CSIT) is essential. Frequency division duplex (FDD) is widely employed by the most cellular systems today. However, it requires...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ Mario E. Magaña Massive MIMO is a promising technique for future 5G communications due to