Abstract
Current approaches to the analysis of heterogeneous cellular networks (HetNets) with random spatial models assume users to be distributed according to a homogeneous Poisson Point Process (PPP) independently of the base station (BS) locations. In reality, however, current deployments are capacity-driven, which correlates the BS and user locations. In this paper, we develop tools for the downlink analysis of HetNets with general nonuniform user distributions by enriching the K-tier PPP HetNet model. Instead of being PPP distributed, the user locations are modeled by a Poisson cluster process with the cluster centers being the BSs. In particular, we provide the first formal analysis of the downlink coverage probability in terms of a general density function describing the locations of users around the BSs. All the results are specialized to a particular case of a Thomas cluster process, where the locations of the users around BSs are Gaussian distributed. Our results concretely demonstrate that the coverage probability decreases with the increasing variance of the user location distribution, ultimately collapsing to the result for the PPP user distribution when the variance goes to infinity.
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