Analysis of Blockage Effects on Urban Cellular Networks

TLDR

Urban cellular networks suffer performance degradation from large‑scale blockages, yet existing analyses often ignore or oversimplify these effects. The study proposes a random‑shape‑theory‑based framework and path‑loss model to analyze how blockages affect connectivity, coverage, and rate in urban cellular networks. Blockages are modeled as randomly sized and oriented rectangles whose centers form a Poisson point process, and a path‑loss model incorporating these blockages is used to evaluate connectivity, coverage, and rate. The analysis shows that blockages per link follow a Poisson distribution, the probability of an unobstructed link decays exponentially with length, base‑station density must increase superlinearly with blockage density to preserve connectivity, and buildings can actually improve SIR coverage and rate by blocking more interference than desired signals.

Abstract

Large-scale blockages such as buildings affect the performance of urban cellular networks, especially at higher frequencies. Unfortunately, such blockage effects are either neglected or characterized by oversimplified models in the analysis of cellular networks. Leveraging concepts from random shape theory, this paper proposes a mathematical framework to model random blockages and analyze their impact on cellular network performance. Random buildings are modeled as a process of rectangles with random sizes and orientations whose centers form a Poisson point process on the plane. The distribution of the number of blockages in a link is proven to be a Poisson random variable with parameter dependent on the length of the link. Our analysis shows that the probability that a link is not intersected by any blockages decays exponentially with the link length. A path loss model that incorporates the blockage effects is also proposed, which matches experimental trends observed in prior work. The model is applied to analyze the performance of cellular networks in urban areas with the presence of buildings, in terms of connectivity, coverage probability, and average rate. Our results show that the base station density should scale superlinearly with the blockage density to maintain the network connectivity. Our analyses also show that while buildings may block the desired signal, they may still have a positive impact on the SIR coverage probability and achievable rate since they can block significantly more interference.