Abstract
The demand for capacity within existing mobile networks continues to increase as more subscribers and more devices communicate and as data-rich applications become more popular. The evolving 5G telecommunications standards aim to respond to such demand. A promising approach to increasing capacity and reliability within the context of 5G is Massive Multiple-Input Multiple-Output (MIMO) where many transmit antennas are used relative to the number of users, thus providing a greater opportunity to use the spatial characteristics of the channel for spatial diversity and multiplexing.This thesis presents an analysis of the propagation environments of Massive MIMO. Factors specific to Massive MIMO are investigated, including slow-fading across arrays and spherical wavefronts, as well as standard measures for wireless communications systems. A study of dynamic Massive MIMO channels is also presented, showing how channels vary in time within busy environments. A time-series model based on the channel condition number is proposed for a statistics-based simulation of the channel. The propagation studies described in this thesis inform the investigation of different practical applications of Massive MIMO technology. One such application is related to the synchronisation process within 5G systems, where synchronisation blocks consisting of the physical broadcast channel and synchronisation signals are sent by the base station to allow users to obtain synchronisation information when connecting to a network. Each block can be sent with a different beam configuration, the collection of which forms a grid of beams over the coverage area. The optimal grid of beams varies by coverage area, so this thesis presents a study to obtain such configurations through a combination of practical network data, propagation models and statistical distributions of users, creating a data set of user distributions with optimal beams.
These data then form the basis for the development of a method to simplify the selection of beam configurations. The final chapter describes a study of the effects of beamforming on Massive MIMO performance, comparing beamforming systems with systems that are dependent only on the multipath propagation characteristics of the environment within which the system operates. The study is based on 3D ray-tracing propagation models of Bristol, built from open-source map data. The Marzetta approach to Massive MIMO downlink transmission using different forms of linear processing, which makes no reference to specific beam configurations, is modelled and the performance analysed in relation to the Error Vector Magnitude, which provides an indication of modulation schemes that can be supported and therefore the expected throughput. The results are compared to similar systems with beams directed towards the mobile users, as well as other systems employing a beamforming strategy.
| Date of Award | 5 Dec 2023 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Mark A Beach (Supervisor) & Geoff Hilton (Supervisor) |