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Receiver Processing and Limited-Feedback User Scheduling for Multiuser MIMO and MIMO-OFDM Downlink

  • Author / Creator
    Eslami, Mohsen
  • Use of multiple antennas at both ends of a communication link, known as multiple-input multiple-output (MIMO), increases the reliability and/or capacity of that link. Orthogonal frequency division multiplexing (OFDM) is an effective technique for high data rate transmission over frequency selective channels. At this time MIMO-OFDM has been proposed for many emerging standards and seems to be a promising solution for future high data rate wireless communications. In the first part of this thesis, a novel sub-optimum detection method for spatially multiplexed multicarrier code division multiplexing (SM-MC-CDM) transmission is proposed. It is shown that compared to the spatially multiplexed OFDM (SM-OFDM), the frequency domain spreading in SM-MC-CDM systems results in an additional diversity gain. To take advantage of diversity and multiplexing while mitigating the interference, a low complexity efficient detector employing unified successive interference cancellation (U-SIC) is designed. Analytical results for the performance and capacity of zero-forcing (ZF) U-SIC are provided. Further performance improvement is achieved by adopting an iterative subcarrier reconstruction-detection algorithm in conjunction with the U-SIC. The results demonstrate significant performance improvement over other existing methods of comparable complexity. Performance of turbo-coded SM-MC-CDM transmission is also investigated. In the next part of the thesis, multiuser MIMO downlink is considered. Efficient transmission schemes based on zero-forcing (ZF) linear receiver processing, eigenmode transmission and partial channel state information are proposed. The proposed schemes utilize a handshaking procedure between the BS and the users to select (schedule) a subset of users and determine the precoding matrix at the base station (BS). The advantage of the proposed limited feedback schemes lies in their relatively low complexity scheduling algorithms and high sum rate throughput, even for a small pool of users. For large user pools and when the number of antennas at each user terminal is at least equal to the number of antennas at the BS, we show that the proposed scheme is asymptotically optimal in the sense that it achieves the same sum rate as the optimum scheme as the number of users approaches infinity. Next, net throughput is used as a benchmark to compare several MIMO-OFDM downlink transmission schemes with complete CSIT and also with limited feedback. Considering limited feedback per chunk user scheduling for MIMO-OFDM downlink, it is shown that there exists a chunk size which maximizes the average net throughput. It is shown that the net throughput maximizing chunk size depends on the number of users in the system and the communication channel's characteristics. Finally, future directions for possible research are given.

  • Subjects / Keywords
  • Graduation date
    2009-11
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3RR1PZ1Z
  • 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.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Electrical and Computer Engineering
  • Supervisor / co-supervisor and their department(s)
    • Krzymien, Witold (Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Tellambura, Chintha (Electrical and Computer Engineering)
    • Nikolaidis, Ioanis (Computing Science)
    • Jing, Yindi (Electrical and Computer Engineering)
    • Heath, Robert (Electrical and Computer Engineering, University of Texas - Austin)