Stochastic Geometry Analysis of Cellular Networks
Nonfiction, Science & Nature, Technology, Engineering, Computers, General Computing
| 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.
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.
