Modeling Spatially-Correlated Cellular Networks by Using Inhomogeneous Poisson Point Processes

Shanshan Wang (1) , Marco Di Renzo (2, 1) , Xiaojun Xi (1)

1 L2S - Laboratoire des signaux et systèmes
2 CNRS - Centre National de la Recherche Scientifique

We introduce a new methodology for modeling and analyzing downlink cellular networks, where the Base Stations (BSs) constitute a motion-invariant Point Process (PP) that exhibits some degree of interactions among the points, e.g., spatial inhibition (repulsion) or spatial aggregation (clustering). The proposed approach is based on the theory of Inhomogeneous Poisson PPs (I-PPPs) and is referred to as Inhomogeneous Double Thinning (IDT) approach. The proposed approach consists of approximating a motion-invariant PP with an equivalent PP that is made of the superposition of two conditionally independent IPPPs. The inhomogeneities are mathematically modeled through two distance-dependent thinning functions and a tractable expression of the coverage probability is obtained.

Domains: Computer Science [cs]; Computer Science [cs]; Information Theory [cs.IT]

Shanshan Wang, Marco Di Renzo, Xiaojun Xi. Modeling Spatially-Correlated Cellular Networks by Using Inhomogeneous Poisson Point Processes. 22nd International ITG Workshop on Smart Antennas WSA 2018, Mar 2018, Bochum, Germany. ⟨10.5281/zenodo.3529633⟩. ⟨hal-02376548⟩