On February 12, 2020, Martin Kurras successfully defended his Ph.D. thesis Massive MIMO in Cellular Networks. The Ph.D. examination committee was formed by Prof. Dr.-Ing. Hoc Khiem Trieu (Institute of Microsystems Technology) and the two reviewers Prof. Dr.-Ing. Gerhard Bauch and Prof. Dr.-Ing. Tobias Weber (University of Rostock).
Abstract
This thesis studies the application of centralized large antenna arrays at base stations in cellular networks, widely called “massive multiple-input multiple-output (MIMO)”.
Figure 1: Massive MIMO at the base station in a cellular network
The first part focuses on the improvement of spectral efficiency in the downlink for spatial multiplexing, see the left-hand-side in Figure 1. This thesis shows that massive MIMO can also provide spectral efficiency gains in frequency-division-duplex systems using a combination of hybrid-precoding and explicit channel state information at the base station, see Figure 2. This finding also holds true under realistic pilot/feedback overhead assumptions and in an interference limited multi-cell environment.
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Figure 2: Massive MIMO in FDD with hybrid. | Figure 3: Adaptive search space quantization for search-based DoA estimation. |
The second part deals with direction-of-arrival (DoA) based localization in the uplink, see the right hand side in Figure 1. Thereby, this thesis provides a low-complexity search-based DoA estimation algorithm for 3D-positioning utilizing the large number of base stations with negligible performance loss compared to a brute-force-search, see Figure 3. Furthermore, a novel two-step user-grouping algorithm for the purpose of joint multiple user DoA estimation is investigated in order to reduce the amount of resources required for uplink positioning pilots.