Binomial Line Cox Processes: Statistical Characterization and Applications in Wireless Network Analysis

The current analysis of wireless networks with transceivers confined to streets is primarily based on Poissonian models, such as Poisson line processes and Poisson line Cox processes. We demonstrate important scenarios where a model with a finite and deterministic number of streets, termed the binomial line process (BLP), is more accurate. We characterize the statistical properties of the BLP and the corresponding binomial line Cox process (BLCP) and apply them to analyze the performance of a network whose access points are deployed along the streets of a city. Such a deployment scenario will be typical for 5G and future wireless networks. In order to obtain a fine-grained insight into the network performance, we derive the meta distribution of the signal-to-interference and noise ratio. Accordingly, we investigate the mean local delay in transmissions and the density of successful transmission. These metrics, respectively, characterize the latency and coverage performance of the network and are key performance indicators of next-generation wireless systems.