03519nam 22006612 450 991045295830332120151005020622.01-316-08953-31-139-79385-31-139-77948-61-139-78346-71-139-78247-91-139-77644-41-139-04381-11-283-71462-01-139-77796-3(CKB)2550000000708205(EBL)1042477(OCoLC)819508220(SSID)ssj0000756994(PQKBManifestationID)11467459(PQKBTitleCode)TC0000756994(PQKBWorkID)10753498(PQKB)11686412(UkCbUP)CR9781139043816(MiAaPQ)EBC1042477(WaSeSS)IndRDA00052773(PPN)174665571(Au-PeEL)EBL1042477(CaPaEBR)ebr10618592(CaONFJC)MIL402712(EXLCZ)99255000000070820520110302d2013|||| uy| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierStochastic geometry for wireless networks /Martin Haenggi, University of Notre Dame, Indiana[electronic resource]Cambridge :Cambridge University Press,2013.1 online resource (xv, 284 pages) digital, PDF file(s)Title from publisher's bibliographic system (viewed on 05 Oct 2015).1-107-01469-7 Includes bibliographical references and index.Machine generated contents note: Part I. Point Process Theory: 1. Introduction; 2. Description of point processes; 3. Point process models; 4. Sums and products over point processes; 5. Interference and outage in wireless networks; 6. Moment measures of point processes; 7. Marked point processes; 8. Conditioning and Palm theory; Part II. Percolation, Connectivity and Coverage: 9. Introduction; 10. Bond and site percolation; 11. Random geometric graphs and continuum percolation; 12. Connectivity; 13. Coverage; Appendix: introduction to R.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.Wireless communication systemsMathematicsStochastic modelsWireless communication systemsMathematics.Stochastic models.621.39/80151922Haenggi Martin763312UkCbUPUkCbUPBOOK9910452958303321Stochastic geometry for wireless networks1548497UNINA