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008			230418s2020 sz | s |||| 0|eng d
020			_a9783031023798
024	7		_a10.1007/978-3-031-02379-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA273.5 _b2020 EB
100	1		_aDhillon, Harpreet S. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9688112
245	1	0	_aPoisson Line Cox Process : _bFoundations and Applications to Vehicular Networks _cby Harpreet S. Dhillon, Vishnu Vardhan Chetlur
250			_a1st edition 2020
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XVII, 131 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Learning Networks and Algorithms _x2690-4314
505	0		_aPreface -- Acknowledgments -- Introduction -- The Poisson Point Process -- The Poisson Line Process -- The Poisson Line Cox Process -- Vehicular Communication Networks -- Ad Hoc Network Model -- Cellular Network Model -- Load Analysis -- Localization Networks -- Path Distance Characteristics -- Potential Future Research -- Bibliography -- Authors' Biographies.
520			_aThis 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.
988			_aSynthesis Collection of Technology_2020
650		7	_2embne _9475879 _aVariables aleatorias
650		7	_2embne _9138936 _aEstadística matemática
700	1		_aChetlur, Vishnu Vardhan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9688113
776	0	8	_iPrinted edition: _z9783031002434
776	0	8	_iPrinted edition: _z9783031012518
776	0	8	_iPrinted edition: _z9783031035074
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02379-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b04/2023 _dz _eIG _zSI