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Analysis of Blockage Effects on Urban Cellular Networks

Published 17 Sep 2013 in cs.IT and math.IT | (1309.4141v1)

Abstract: Large-scale blockages like 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 Poisson random variable with parameter dependent on the length of the link. A path loss model that incorporates the blockage effects is 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. Analytic results show while buildings may block the desired signal, they may still have a positive impact on network performance since they can block significantly more interference.

Citations (628)

Summary

  • The paper introduces a mathematical framework using random shape theory and PPP to quantify the impact of building blockages on signal propagation.
  • It demonstrates that blockage-induced shadowing can selectively reduce interference, potentially enhancing coverage in dense urban areas.
  • The analysis incorporates SINR limits and variable blockage sizes to offer actionable insights for optimizing base station deployment.

Analysis of Blockage Effects on Urban Cellular Networks

The paper presents a comprehensive mathematical framework to model and analyze the impact of large-scale blockages, such as buildings, on urban cellular network performance. Employing concepts from random shape theory, the authors address the often overlooked or oversimplified effects of blockages at higher frequencies, which are particularly relevant for emerging millimeter-wave (mmWave) networks.

The authors model buildings as a process of random rectangles, characterized by their centers forming a Poisson point process (PPP) on the plane. This innovative approach captures the randomness of building sizes, orientations, and heights. A noteworthy result is that the number of blockages on a link is a Poisson random variable, with its parameter depending on the link length. Crucially, the proposed path loss model reflects experimental trends, notably adding an exponential decay component to the path loss formulation caused by blockages.

In cellular networks, particularly those in urban areas, the distribution of base stations is becoming less regular. This change in infrastructure demands advanced mathematical tools like stochastic geometry to analyze network coverage and connectivity. The PPP assumption made in this study for both base stations and building centers enables tractable results, applicable to understanding the nuanced effects of blockages in real-world deployments.

The analysis reveals that while blockages may hinder direct line-of-sight (LoS) communication, their shadowing effects can reduce interference more markedly than the desired signal, potentially enhancing coverage probability and average rate in dense networks. An important contribution of the paper is the counterintuitive insight that blockages can sometimes improve network performance by selectively attenuating interference.

Key findings include:

  • Connectivity Analysis: The paper quantifies visible regions for base stations and mobile users, deriving the distribution of the distance to the nearest visible base station. The average number of visible base stations is finite, ensuring that cellular users experience reliable connectivity.
  • Coverage Probability: The impact of base station density on coverage shifts when blockages are considered, distinguishing this work from models that ignore such effects. The analysis shows that increased base station deployment does not monotonically enhance coverage, as network performance can degrade if deployment density increases without considering blockage effects.
  • Average Achievable Rate: Blockages are shown to alter the rate achievable in networks, dependent on both the density and size of blockages. The framework accommodates device capabilities such as RF-imposed SINR limits, which are often overlooked in idealized models.

The potential implications are significant for the design and optimization of future cellular networks, especially in urban environments where irregular structures impact signal propagation unpredictably. The framework allows for precise evaluation and planning of base station deployment and placement strategies that acknowledge the heterogeneity introduced by blockages.

Future avenues for research emerging from this paper include addressing signal reflections and refining the model for even more adaptive architectural deployment patterns. Additionally, extending the framework to multi-tier network configurations and investigating correlated shadowing effects among different links could provide deeper insights into network behavior in complex urban terrains.

In conclusion, the paper succeeds in delivering a nuanced approach to modeling blockage effects in urban cellular environments, presenting essential insights that challenge conventional wisdom on network performance and design strategies.

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