An Introduction to Cellular Network Analysis Using Stochastic Geometry
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Beschreibung
This book provides an accessible yet rigorous first reference for readers interested in learning how to model and analyze cellular network performance using stochastic geometry. In addition to the canonical downlink and uplink settings, analyses of heterogeneous cellular networks and dense cellular networks are also included. For each of these settings, the focus is on the calculation of coverage probability, which gives the complementary cumulative distribution function (ccdf) of signal-to-interference-and-noise ratio (SINR) and is the complement of the outage probability. Using this, other key performance metrics, such as the area spectral efficiency, are also derived. These metrics are especially useful in understanding the effect of densification on network performance. In order to make this a truly self-contained reference, all the required background material from stochastic geometry is introduced in a coherent and digestible manner.
This Book:
- Provides an approachable introduction to the analysis of cellular networks and illuminates key system dependencies
- Features an approach based on stochastic geometry as applied to cellular networks including both downlink and uplink
- Focuses on the statistical distribution of signal-to-interference-and-noise ratio (SINR) and related metrics
This book provides an accessible yet rigorous first reference for readers interested in learning how to model and analyze cellular network performance using stochastic geometry. In addition to the canonical downlink and uplink settings, analyses of heterogeneous cellular networks and dense cellular networks are also included. For each of these settings, the focus is on the calculation of coverage probability, which gives the complementary cumulative distribution function (ccdf) of signal-to-interference-and-noise ratio (SINR) and is the complement of the outage probability. Using this, other key performance metrics, such as the area spectral efficiency, are also derived. These metrics are especially useful in understanding the effect of densification on network performance. In order to make this a truly self-contained reference, all the required background material from stochastic geometry is introduced in a coherent and digestible manner.
This Book:
- Provides an approachable introduction to the analysis of cellular networks and illuminates key system dependencies
- Features an approach based on stochastic geometry as applied to cellular networks including both downlink and uplink
- Focuses on the statistical distribution of signal-to-interference-and-noise ratio (SINR) and related metrics
Provides an approachable introduction to the analysis of cellular networks and illuminates key system dependencies Features an approach based on stochastic geometry as applied to cellular networks including both downlink and uplink Focuses on the statistical distribution of signal-to-interference-and-noise ratio (SINR) and related metrics
Autor*in
Jeffrey G. Andrews
Themen in »An Introduction to Cellular Network Analysis Using Stochastic Geometry«
Stochastic Geometry Poisson Point Process Wireless Communications Cellular Networks Heterogeneous Cellular Networks Dense Networks