Dissertation on Massive MIMO in Cellular Networks
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).
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.
Figure 2: Massive MIMO in FDD with hybrid. Figure 3: Adaptive search space quanti-zation 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.