Stochastic Geometry for Wireless Networks
Nonfiction, Science & Nature, Technology, Engineering, Computers, General Computing
| Author: | Professor Martin Haenggi | ISBN: | 9781139793858 |
| Publisher: | Cambridge University Press | Publication: | October 18, 2012 |
| Imprint: | Cambridge University Press | Language: | English |
| Author: | Professor Martin Haenggi |
| ISBN: | 9781139793858 |
| Publisher: | Cambridge University Press |
| Publication: | October 18, 2012 |
| Imprint: | Cambridge University Press |
| Language: | English |
Covering point process theory, random geometric graphs and coverage processes, this rigorous introduction to stochastic geometry will enable you to obtain powerful, general estimates and bounds of wireless network performance and make good design choices for future wireless architectures and protocols that efficiently manage interference effects. Practical engineering applications are integrated with mathematical theory, with an understanding of probability the only prerequisite. At the same time, stochastic geometry is connected to percolation theory and the theory of random geometric graphs and accompanied by a brief introduction to the R statistical computing language. Combining theory and hands-on analytical techniques with practical examples and exercises, this is a comprehensive guide to the spatial stochastic models essential for modelling and analysis of wireless network performance.
Covering point process theory, random geometric graphs and coverage processes, this rigorous introduction to stochastic geometry will enable you to obtain powerful, general estimates and bounds of wireless network performance and make good design choices for future wireless architectures and protocols that efficiently manage interference effects. Practical engineering applications are integrated with mathematical theory, with an understanding of probability the only prerequisite. At the same time, stochastic geometry is connected to percolation theory and the theory of random geometric graphs and accompanied by a brief introduction to the R statistical computing language. Combining theory and hands-on analytical techniques with practical examples and exercises, this is a comprehensive guide to the spatial stochastic models essential for modelling and analysis of wireless network performance.
