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An Introduction to Cellular Network Analysis Using Stochastic Geometry [electronic resource] / by Jeffrey G. Andrews, Abhishek K. Gupta, Ahmad Alammouri, Harpreet S. Dhillon.

By: Andrews, Jeffrey G [author.].
Contributor(s): Gupta, Abhishek K [author.] | Alammouri, Ahmad [author.] | Dhillon, Harpreet S [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Learning, Networks, and Algorithms: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: XVII, 87 p. 18 illus., 16 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031297434.Subject(s): Computer science -- Mathematics | Mathematical statistics | Telecommunication | Computer Networks | Electrical engineering | Stochastic processes | Wireless communication systems | Mobile communication systems | Probability and Statistics in Computer Science | Communications Engineering, Networks | Computer Networks | Electrical and Electronic Engineering | Stochastic Networks | Wireless and Mobile CommunicationAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 004.0151 Online resources: Click here to access online
Contents:
Acknowledgments -- Introduction -- Key Background on Stochastic Geometry -- Downlink Analysis -- Uplink Analysis -- Heterogeneous Cellular Network Analysis -- Dense Cellular Networks -- Extensions -- Bibliography.
In: Springer Nature eBookSummary: 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.
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Acknowledgments -- Introduction -- Key Background on Stochastic Geometry -- Downlink Analysis -- Uplink Analysis -- Heterogeneous Cellular Network Analysis -- Dense Cellular Networks -- Extensions -- Bibliography.

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.

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