Cognitive vehicular networks by Anna Maria Vegni, Dharma P. Agrawal

By Anna Maria Vegni, Dharma P. Agrawal

A entire textual content on either present and rising parts of cognitive vehicular networks, this ebook makes a speciality of a brand new type of cellular advert hoc networks. It makes use of a pedagogical method using cognitive elements utilized to vehicular environments and includes contributions from famous and excessive profile researchers of their respective specialties. The ebook offers major technical and sensible insights on assorted views, ranging from a easy historical past on cognitive radio, interrelated applied sciences, program to vehicular networks, technical demanding situations, and destiny developments.

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Cognitive vehicular networks

A accomplished textual content on either present and rising parts of cognitive vehicular networks, this booklet specializes in a brand new classification of cellular advert hoc networks. It makes use of a pedagogical process using cognitive features utilized to vehicular environments and contains contributions from recognized and excessive profile researchers of their respective specialties.

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13–21, 2000. [8] Partners for Advanced Transportation Technology. edu. [9] J. Liu and S. Singh. ATCP: TCP for mobile ad hoc networks, IEEE Journal on Selected Areas in Communications, 2001, 19(7): 1300–1315. [10] B. Jarupan and E. Ekici. A survey of cross-layer design for VANETs Ad Hoc Networks, July 2011, 9(5): 966–983. Towards Cognitive Vehicular Networks 29 [11] R. Schmilz, A. Leiggener, A. Festag, L. Eggert and W. Effelsberg. Analysis of path characteristics and transport protocol design in vehicular ad hoc networks, in Proc.

Spectrum Mobility: vehicles clear the channel when a licensed user is detected. The focus of this chapter is on a particular vehicle spectrum management subproblem which deals solely with selecting the appropriate available frequency set in a distributed fashion for cognitive vehicular network applications. The spectrum allocation problem in CRNs is more challenging than in other existing wireless communication networks for several reasons. First, the required detection of errors in spectrum sensing algorithms deteriorates the performance of the adapting spectrum allocation algorithm [18, 31].

IEEE Transactions on Vehicular Technology, 2009, 58(4): 1804–1815. [25] H. Li, C. Li and H. Dai. Quickest spectrum sensing in cognitive radio. Proc. 42nd Annual Conference on Information Science and Systems (CISS'08), 2008, pp. 203–208. [26] D. Willkomm, S. Machiraju, J. Bolot and A. Wolisz. Primary users in cellular networks: A large-scale measurement study. Proc. IEEE DySPAN, 2008, pp. 1–11. F. Akyildiz, Won-Yeol Lee, C. Mehmet Vuran and Shantidev Mohanty. NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey.

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