Poisson line Cox process : foundations and applications to vehicular networks / Harpreet S. Dhillon and Vishnu Vardhan Chetlur.Material type: TextSeries: Synthesis digital library of engineering and computer science | Synthesis lectures on learning, networks, and algorithms ; #24.Publisher: [San Rafael, California] : Morgan & Claypool, Description: 1 PDF (xvii, 131 pages) : illustrations (some color)Content type: text Media type: electronic Carrier type: online resourceISBN: 9781681738437Subject(s): Stochastic geometry | Machine-to-machine communications | Vehicular ad hoc networks (Computer networks) | stochastic geometry | Poisson line Cox process (PLCP) | Poisson line process (PLP) | coverage probability | vehicular networks | vehicular ad hoc network (VANET) | cellular vehicle-to-everything (C-V2X)Additional physical formats: Print version:: No titleDDC classification: 519.2 LOC classification: QA273.5 | .D557 2020ebOnline resources: Abstract with links to full text | Abstract with links to resource Also available in print.
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Mode of access: World Wide Web.
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Part of: Synthesis digital library of engineering and computer science.
Includes bibliographical references (pages 121-129).
1. Introduction -- 1.1. Motivation -- 1.2. Historical perspective -- 1.3. Scope and organization
2. The Poisson point process -- 2.1. Introduction -- 2.2. Properties of PPP -- 2.3. The Poisson Voronoi tessellation -- 2.4. Summary
3. The Poisson line process -- 3.1. Planar line processes -- 3.2. Plp and its properties -- 3.3. Summary
4. The Poisson line Cox process -- 4.1. Construction of PLCP -- 4.2. Properties of PLCP -- 4.3. Laplace functional -- 4.4. Asymptotic characteristics -- 4.5. Summary
5. Vehicular communication networks -- 5.1. Objectives -- 5.2. Notation and modeling assumptions -- 5.3. Coverage probability -- 5.4. Summary
6. Ad hoc network model -- 6.1. Poisson bipolar model -- 6.2. Poisson line Cox bipolar (PLCB) model -- 6.3. Performance trends -- 6.4. Summary
7. Cellular network model -- 7.1. 2D PPP model -- 7.2. PLCP model -- 7.3. Performance trends -- 7.4. SINR characterization under shadowing -- 7.5. Summary
8. Load analysis -- 8.1. Load on the roadside units -- 8.2. Load on the macro base stations -- 8.3. Summary
9. Localization networks -- 9.1. System model -- 9.2. Blind spot probability -- 9.3. Summary
10. Path distance characteristics -- 10.1. Manhattan Poisson line process -- 10.2. Manhattan Poisson line Cox process -- 10.3. The shortest path distance -- 10.4. Results and discussion -- 10.5. Summary
11. Potential future research -- 11.1. Enhancements of the model -- 11.2. Performance metrics -- 11.3. Spatio-temporal analysis.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
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This book provides a comprehensive treatment of the Poisson line Cox process (PLCP) and its applications to vehicular networks. The PLCP is constructed by placing points on each line of a Poisson line process (PLP) as per an independent Poisson point process (PPP). For vehicular applications, one can imagine the layout of the road network as a PLP and the vehicles on the roads as the points of the PLCP. First, a brief historical account of the evolution of the theory of PLP is provided to familiarize readers with the seminal contributions in this area. In order to provide a self-contained treatment of this topic, the construction and key fundamental properties of both PLP and PLCP are discussed in detail. The rest of the book is devoted to the applications of these models to a variety of wireless networks, including vehicular communication networks and localization networks. Specifically, modeling the locations of vehicular nodes and roadside units (RSUs) using PLCP, the signal-to-interference-plus-noise ratio (SINR)-based coverage analysis is presented for both ad hoc and cellular network models. For a similar setting, the load on the cellular macro base stations (MBSs) and RSUs in a vehicular network is also characterized analytically. For the localization networks, PLP is used to model blockages, which is shown to facilitate the characterization of asymptotic blind spot probability in a localization application. Finally, the path distance characteristics for a special case of PLCP are analyzed, which can be leveraged to answer critical questions in the areas of transportation networks and urban planning. The book is concluded with concrete suggestions on future directions of research. Based largely on the original research of the authors, this is the first book that specifically focuses on the self-contained mathematical treatment of the PLCP. The ideal audience of this book is graduate students as well as researchers in academia and industry who are familiar with probability theory, have some exposure to point processes, and are interested in the field of stochastic geometry and vehicular networks. Given the diverse backgrounds of the potential readers, the focus has been on providing an accessible and pedagogical treatment of this topic by consciously avoiding the measure theoretic details without compromising mathematical rigor.
Also available in print.
Title from PDF title page (viewed on July 7, 2020).