Stochastic Geometry Analysis of Cellular Networks

Nonfiction, Science & Nature, Technology, Engineering, Computers, General Computing
Cover of the book Stochastic Geometry Analysis of Cellular Networks by Bartłomiej Błaszczyszyn, Martin Haenggi, Paul Keeler, Sayandev Mukherjee, Cambridge University Press
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Author: Bartłomiej Błaszczyszyn, Martin Haenggi, Paul Keeler, Sayandev Mukherjee ISBN: 9781108340502
Publisher: Cambridge University Press Publication: April 19, 2018
Imprint: Cambridge University Press Language: English
Author: Bartłomiej Błaszczyszyn, Martin Haenggi, Paul Keeler, Sayandev Mukherjee
ISBN: 9781108340502
Publisher: Cambridge University Press
Publication: April 19, 2018
Imprint: Cambridge University Press
Language: English

Achieve faster and more efficient network design and optimization with this comprehensive guide. Some of the most prominent researchers in the field explain the very latest analytic techniques and results from stochastic geometry for modelling the signal-to-interference-plus-noise ratio (SINR) distribution in heterogeneous cellular networks. This book will help readers to understand the effects of combining different system deployment parameters on key performance indicators such as coverage and capacity, enabling the efficient allocation of simulation resources. In addition to covering results for network models based on the Poisson point process, this book presents recent results for when non-Poisson base station configurations appear Poisson, due to random propagation effects such as fading and shadowing, as well as non-Poisson models for base station configurations, with a focus on determinantal point processes and tractable approximation methods. Theoretical results are illustrated with practical Long-Term Evolution (LTE) applications and compared with real-world deployment results.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Achieve faster and more efficient network design and optimization with this comprehensive guide. Some of the most prominent researchers in the field explain the very latest analytic techniques and results from stochastic geometry for modelling the signal-to-interference-plus-noise ratio (SINR) distribution in heterogeneous cellular networks. This book will help readers to understand the effects of combining different system deployment parameters on key performance indicators such as coverage and capacity, enabling the efficient allocation of simulation resources. In addition to covering results for network models based on the Poisson point process, this book presents recent results for when non-Poisson base station configurations appear Poisson, due to random propagation effects such as fading and shadowing, as well as non-Poisson models for base station configurations, with a focus on determinantal point processes and tractable approximation methods. Theoretical results are illustrated with practical Long-Term Evolution (LTE) applications and compared with real-world deployment results.

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