iately and serve both the users using NOMA principle. 5.4 Point Process The conventional design adopted for the traditional cellular network is grid based. The grid-based model places the BSs (specifically the macroBS) on a grid. Although the Grid-based models are popular and are used extensively, however, they are highly idealized and are not easily tractable. Due to the intractability, complex system-level simulations are used to calculate the outage probability and rate of the network. Furthermore, interference modeling is a challenging task even while considering single-tier cellular networks. The characterization of interference in a single-tier network, assuming the conventional hexagonal grid-based model, requires massive Monte Carlo simulations [9] due to intractability or inaccurate results due to unrealistic assumptions [41]. Thus, a more realistic model with tractable analysis is required, especially for modeling the multi-tier BSs of the HetNets. Practically, due to varied capacity demands in the area of service, the BSs P. Swami and V. Bhatia are far from following a grid-based model. If snapshots of BSs at various locations are checked, the position of the BSs with respect to each other will be random. This makes the grid-based model very idealistic, and its assumptions violate realistic characteristics of a network. Such topological randomness is true for single-tier and multi-tier networks. The design of HetNet requires interference avoidance. There- fore, rigorous yet simple interference models are necessary. Stochastic geometry provides the necessary tools to model the multi-tier networks. Besides capturing the topological randomness of the BSs, stochastic geometry tools are competent in providing tractable analysis [42-44]. In stochastic geometry, the randomness of the BSs is captured using various point processes, appropriate for the given practical scenario. This makes the point process an essential object in stochastic geometry. A point process is defined as a random collection of points in 