Multitier heterogeneous network using stochastic geometry and factorial moment approaches

The rapid growth of small cells is driving cellular network toward randomness and heterogeneity. Usually, cellular networks are modeled by placing each tier (eg, macro, pico, and relay nodes) deterministically on a grid. In such a heterogeneous cellular network, the rational approach to characterize the base stations (BSs), user, and relay locations is by using random spatial models. When calculating the metric performances such as coverage probability, these networks are idealized without consideration of interference. Therefore, interference modeling remains the key issue for the deployment of small cells. This paper developed a single and multitier cellular network model that captures the downlink heterogeneous cellular network with variable parameters such as the target signal‐to‐interference ratio (SIR), transmitted power, and deployment density. In particular, we model ‐tier transmission and compare it with a single‐tier and traditional grid model to obtain tractable coverage probability using stochastic geometry and factorial moment. The obtained results demonstrate the effectiveness and analytical tractability to study the heterogeneous performance.