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Reduced-Complexity Transceiver Signal Processing Algorithms for Massive MIMO and mmWave Cellular Systems

  • Author / Creator
    Maliheh Soleimani
  • Future broadband cellular networks will have to accommodate explosively growing demand for high bit rate data services. The adoption of multiple-input multiple-output (MIMO) designs with large antenna arrays (also known as massive MIMO) and the use of millimeter wave (mmWave) frequency bands are considered as two key techniques to satisfy these demands. The motivations of moving to mmWave frequencies and employing large antenna arrays are respectively the much wider bandwidths that become available and the higher spectral efficiencies that are enabled. While potentially providing great advantages, both of these technologies are still in an exploratory research stage, focused on developing efficient algorithms to address the challenges that their implementation faces. Issues such as channel estimation, radio frequency (RF) hardware constraints, computational complexity, cost and power consumption have yet to be fully addressed. The key objectives of this research are the design and performance evaluation of the following. First, a low complexity and simplified path selection algorithm, based on bipartite graphs for massive MIMO channel under sparsity condition in massive MIMO systems, is proposed and analyzed. Second, a joint design of user clustering and pre-processing algorithms that are suitable for spatially sparse massive MU-MIMO downlink channels is proposed where a two-layer beamforming scheme is performed to both minimize inter-beam and inter-user interference, and maximize spatial multiplexing gain. Third, a projection-based hybrid precoding algorithm for hybrid transceiver in mmWave MIMO systems is proposed for both fully-connected and partially-connected structures. Finally, a robust precoder for massive MIMO systems employing single-RF-chain load-modulated transmitters that represents a promising alternative to hybrid digital-analog precoders to achieve reduced-complexity hardware implementation is studied.

  • Subjects / Keywords
  • Graduation date
    Spring 2021
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/r3-aj63-5m05
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.