Coverage Probability Analysis for Device-to-Device Communication Underlaying Cellular Networks

Abstract

As one of the most promising techniques in wireless communication systems, device-to-device (D2D) has drawn much attention due to its superior performance. Meanwhile, the interference between cellular users and D2D users is still a challenging problem and needs to be mitigated effectively. A large number of simulation experiments for D2D communications have been studied to reduce the impact of the interference in the existing literature. However, theoretical research is still lacking. Thus, in this paper, we use stochastic geometry to evaluate the uplink performance of users by considering the impact of the previous moment on the next moment, which captures the effect of temporal and the spatial correlation of the interference in D2D communication underlaying cellular networks. Using a Poisson point process to model locations of D2D users, we derive an analytic expression for conditional probability and unconditional probability of link success, and prove that the probability of link success is temporally correlated. Moreover, we provide a theoretical framework for interference mitigation in D2D underlaying cellular networks.

Remarks on a stochastic geometric model for interference-limited cellular communications

“…where D z is a RV representing the distance between the BS at z and he typical UE. The SIR at the typical UE is thus given by (3).…”

“…Stochastic geometry (SG) has been used heavily as a modeling tool in the field of wireless communications, e.g., ad hoc networks, cellular networks and IoT device deployment. For example, SG has been used in [1] to model heterogeneous cellular networks, in [2] to model narrow band internet of things (IoT), in [3] to model D2D communications underlaying cellular systems, and in [4] to model millimeter wave dense cellular networks. The SG model is based on treating the nodes as a realization (snapshot) of a spatial point process in the Euclidean plane, then averaging over all node locations to obtain useful performance metrics.…”