Stochastic Geometry Based Analysis of Candidate Technologies for 5G Cellular Systems

Future fifth generation (5G) cellular standards incorporate new emerging technologies such as cognitive radio, device to device (D2D), interweave, energy harvesting, massive MIMO, and millimeter wave networks. However, the achievable gains of these technologies are limited by the spatial randomness of nodes and network interference. Spatial locations of nodes are increasingly random. Characterizing the impacts of this randomness on system parameters is a main motivation of this thesis. Moreover, when two networks coexist in the same geographical area, interference occurs between the networks in addition to interference within each network. The interplay between different technologies is also of high interest as they will be deployed in tandem. Therefore, the main communication problem addressed in this thesis is the characterization of interference among spatially random nodes for co-existing networks under emerging technologies. The main contributions of this thesis are categorized as follows: 1) Development of power control and receiver association schemes for an annular underlay CR network and investigation of their performance, 2) Development of co-operative beacon detection schemes for interweave CR networks and investigation of their performance, 3) Investigation of the feasibility of wireless energy harvesting for an underlay CR network using stochastic geometry and markov chain based models, 4) Quantifying the effect of performance degradation for an underlaid receiver when base stations use massive MIMO, and 5) Development of an analytical framework to analize performance degradation to an underlaid D2D network employing millimeter wave frequencies. It is shown that stochastic geometry models provide vital insights into key network design considerations while incorporating most system and channel parameters. The research outcomes