Channel Estimation Algorithms for Future Mobile Communication Systems

  • Research field:Communication technology and signal processing
  • Type:Masterarbeit
  • Time:from now
  • Supervisor:

    M.Sc. Adriana Briseno

  • Millimeter wave (mmWave) communications have recently attracted large research interest, since the available bandwidth can potentially lead to the rates of multiple Gbps per user. Due to the severe pathloss incurred aby mmWave frequencies, large antenna gains are required both at the base station (BS) and the user equipment (UE) side. Thanks to the small wavelength associated with mmWave frequencies, large antenna arrays can be packed in small areas, such that the required large antenna gain can be obtained using beamforming. In particular, the hybrid analog/digital beamforming architecture has been considered, where the corresponding signal processing techniques must be designed to enable channel estimation and a good tradeoff between the spectral efficiency and energy consumption/hardware cost. However, the performance of directional beamforming largely relies on the accuracy of available channel state information (CSI). That means that the transmitter and receiver need to know the spatial direction in which they have to direct their beams. Therefore, new channel estimation algorithms have to be developed, which support hybrid analog/digital beamforming architectures. The two important figures of merit are the required estimation time and estimation accuracy of those algorithms.  

    In frame of this thesis channel estimation algorithms for hybrid analog/digital beamforming architectures are investigated. This work includes the following tasks:

    • Literature research on recently published channel estimation algorithms
    • Implementation of different algorithms in MATLAB
    • Comparison of different algorithms in numerical simulations
    • If possible, implementation and testing using the MIMO demonstrator developed at IHE

    Required knowledge:

    1. Basics on radio frequency systems and wireless communications

    2. Proficiency usage of Matlab

    3. Complex mathematical understanding