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A Stochastic Geometry Framework for Modeling of Wireless Communication

21 pages
A Stochastic Geometry Framework for Modeling of Wireless Communication Networks Bart?omiej B?aszczyszyn X Konferencja z probabilistyki Be¸dlewo, 19-23 maja 2008 INRIA-ENS / University of Wro?aw OUTLINE OF THE TALK I WIRELESS NETWORKS — a crash course in wireless communications II STOCHASTIC GEOMETRY (SG) — classic models in a new context III SINR COVERAGE MODEL IV SOME MORE (APPLIED) WORKS V CONCLUSIONS & PERSPECTIVES Bartek B?aszczyszyn WIRELESS NETWORKS what we build on Networking: coexistence and cooperation in time and space of many communications. Bartek B?aszczyszyn WIRELESS NETWORKS what we build on Networking: coexistence and cooperation in time and space of many communications. wireless networks ? SG ? signal detection models ? radio wave propagation models Bartek B?aszczyszyn

  • usful signal

  • concerning cellular networks

  • sg ?

  • equations —

  • wireless networks ?

  • power received

  • signal power

  • emitter receiver

  • electromagnetic field


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Networking:
A Stochastic Geometry Framework for Modeling of Wireless Communication Networks
Bartomiej Baszczyszyn
X Konferencja z probabilistyki B¸edlewo,19-23maja2008
INRIA-ENS / University of Wroaw
WIRELESS NETWORKS what we build on
coexistence and cooperation in time and space of many communications.
Bartek Baszczyszyn
OUTLINE OF THE TALK
IWIRELESS NETWORKS crash course in wireless communications— a IISTOCHASTIC GEOMETRY (SG)— classic models in a new context
IIISINR COVERAGE MODEL
IVSOME MORE (APPLIED) WORKS
VCONCLUSIONS & PERSPECTIVES
Bartek Baszczyszyn
Networking:
WIRELESS NETWORKS what we build on
coexistence and cooperation in time and space of many communications.
Bartek Baszczyszyn
wireless networksSG
signal detection models radio wave propagation models
radio wave propagation models
signal powerPttdeemi
emitter
R
Pi rPec. receiver
detailed Maxwell's electromagnetic eld equations — too complex and not needed
Bartek Baszczyszyn
radio wave propagation models
signal powerPemditte emitter
R
iP
Prec . receiver
detailed Maxwell's electromagnetic eld equations — too complex and not needed (D) Deterministic model:Prec.Pimedett¢l(R) , (G) Stochastic (“far-eld”)model:Prec.=PiPiCLTPtimedet¢F¢l(R) , wherel(R)Rβis deterministicuatittenaonfunction,Fis randomfadingvariable.
Bartek Baszczyszyn
radio wave propagation models
signal powerPemitted
emitter
R
iP
rPec. receiver
detailed Maxwell's electromagnetic eld equations — too complex and not needed (D) Deterministic model:Prec.Pemitted¢l(R) ,
wherel(R)Rβis deterministicitnoneauttafunction,
Bartek Baszczyszyn
radio wave propagation models
signal powerPmittede
emitter
R
Pi
rPec. receiver
detailed Maxwell's electromagnetic eld equations — too complex and not needed (D) Deterministic model:Prec.Pemitted¢l(R) , (G) Stochastic (“far-eld”)model:Prec.=PiPiCLTPemdetti¢F¢l(R) , wherel(R)Rβis deterministicneauattontifunction,Fis randomfadingvariable. (M) Rayleigh fading:Fisxleaoiptenn(=ZI2+FQ2whereZI,ZQi.i.d. N(0,1))
Bartek Baszczyszyn