Load-aware modelling in cellular networks with repulsively deployed base stations

Spatial models for the locations of base stations (BSs) in cellular networks have long been desirable since they play a pivotal role in evaluating the mutual interference and,hence, overall performance of the network. The Poisson point process (PPP) is the most analytically tractable and widely used model for the location of BSs, but it fails to capture the underlying separation between BSs of cellular networks. This thesis uses most recently proposed model, the Ginibre point process (GPP), for the location of BSs to capture the underlying separation between them. The GPP is a special type of determinantal point process (DPP) that provides the best fit for the random phenomena where repulsion exists and at the same time maintains the analytical tractability of the analysis.Apart from spatial models for the location of BSs, another most important aspect is the BS load which has not been addressed in most of the previous analyses. The main emphasis of this thesis is to incorporate the BS load using the idea of conditional thinning of the interference field. For a single-tier cellular network where the BSs are spatially distributed via GPP and transmitting with a certain probability, we derive the coverage probability for the typical user under the assumption of a Rayleigh fading channel. To evaluate the coverage, we have also determined the Laplace transform of interference,under the diagonal approximation, in a GPP-based model that can be used for various other settings as well. In addition, to show that the β-GPP model is accurate for cellular networks, we provide the fitting results of β-GPP to that of actual BS deployment data set in terms of the coverage probability. We also model the multi-tier cellular network using the β-GPP and provide the Monte Carlo simulation results for the coverage probability under various network settings.