Performance analysis of clustered device-to-device networks using matern cluster process

This paper presents a new analytical framework for clustered device-to-device (D2D) networks in dense urban scenarios. We model the D2D network as a Matern cluster process (MCP) instead of Poisson point process and Tomas cluster process. MCP modeling can capture both clustered and bounded properties of D2D communications in urban areas. Considering a typical D2D receiver (DR), we assume it receives the content of interest from a D2D transmitter (DT) in the same cluster. Two different choice methods of its serving DT are analyzed: (1) the serving DT is chosen uniformly at random; (2) the serving DT is the closest active DT to the typical DR. Based on this model, distributions of the serving distance and interfering distances of both choice methods are derived through geometric construction and order statistics theory, respectively. With these distance distributions, the coverage and area spectral efficiency (ASE) of the network can be obtained using stochastic geometry. According to the analysis and simulations, we know that ASE of the uniform choice can be maximized by optimizing the average number of simultaneously active DTs per cluster. Meanwhile, ASEs of both choice methods can be maximized by choosing a proper coverage threshold. This paper provides a guideline to the analysis of clustered D2D communications and can be extended to heterogeneous networks.