The current analysis of wireless networks whose transceivers are confined to streets is largely 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 binomial line process, is more accurate. We characterize the statistical properties of the BLP and the corresponding binomial line Cox process 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 transmission 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.

翻译：当前，针对收发器局限于街道的无线网络分析主要基于泊松模型，例如泊松线过程和泊松线Cox过程。我们论证了在重要场景中，采用具有有限且确定数量街道的模型（称为二项式线过程）更为精确。我们对BLP及相应的二项式线Cox过程的统计特性进行了刻画，并将其应用于分析接入点沿城市街道部署的网络性能。此类部署场景将成为5G及未来无线网络的典型特征。为深入洞察网络性能，我们推导了信干噪比的元分布，并据此研究了传输平均本地时延和成功传输密度。这些指标分别表征了网络的时延与覆盖性能，是下一代无线系统的关键性能指标。