ANALYSIS AND DESIGN OF MACHINE-TYPE COMMUNICATION NETWORKS USING STOCHASTIC GEOMETRY

Abstract

Machine-type Communication (MTC) is an emerging technology that seeks spectrally efficient ways to provide ubiquitous connectivity among a massive number of automated devices. As MTC prevail in a wide range of applications realizing the Internet-of-Things, efficiently supporting MTC's unique requirements will be a key challenge. This thesis derives system-level insights for MTC, offers critical parameter optimizations to expedite their development and standardization progress. Firstly, the thesis proposes relaying schemes exclusively designed for MTC, and presents resource partitioning schemes for maximum network capacity. Full-duplex relays were considered in the following chapter, assuming a similar single-hop relay architecture. It was shown for certain parameter settings that using a correct proportion of in-band and out-band full-duplex relays can provide a higher network capacity than using either one alone. Finally, the last technical part studies the cognitive radio techniques for MTC, and proposes an optimal design of exclusion/guard zone radii for interference mitigation.