Distance distributions for Matern cluster processes with application to network performance analysis

Conference item

In this work, we analyze the distance statistics corresponding to points in a Matérn cluster (offspring points) and points that do not belong to that cluster (non-offspring points). We first derive the probability density function (PDF) of the distance between an offspring point and a non-offspring point of a Matérn cluster. We then formulate the probability generating functional based on this PDF. Since many wireless networks (e.g., device-to-device (D2D) networks and cognitive radio systems) exhibit device clustering, this formalism enables us to efficiently formulate and evaluate expressions that describe the interference statistics and connection probability in clustered networks. We validate our theoretical analysis with numerical simulations, and illustrate that traditional methods of evaluating similar performance metrics (based on point process statistics instead of distance statistics) are unsuitable for use in such complex scenarios.

Authors: Tang, J; Chen, G; Coon, J; Simmons, D

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Institute of Electrical and Electronics Engineers
• Host title: IEEE International Conference on Communications 2017
• Journal: IEEE International Conference on Communications 2017
• Publication date: 2017-05-01
• Acceptance date: 2017-01-27
• DOI: 10.1109/ICC.2017.7997055
• EISSN: 1938-1883
• Keywords: distance probability density function; Matérn cluster process; Interference