A Stochastic Geometry Framework for Modeling of Wireless Communication

Description

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

Sujets

• Electromagnetic field
• maths

Informations

• Publié par: pefav
• Nombre de lectures: 13
• Langue: English
• Poids de l'ouvrage: 2 Mo

Extrait

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 networks ⇐ SG ⇑

signal detection models ⇑ radio wave propagation models

radio wave propagation models

signal power P ttdeemi

emitter

R

P i r P ec. receiver

detailed Maxwell's electromagnetic eld equations — too complex and not needed

Bartek Baszczyszyn

radio wave propagation models

signal power P emditte emitter

R

i P

P rec . receiver

detailed Maxwell's electromagnetic eld equations — too complex and not needed (D) Deterministic model:P rec. ≈ P imedett ¢ l(R) , (G) Stochastic (“far-eld”)model:P rec. = P i P i C ≈ LT P timedet ¢ F ¢ l(R) , wherel(R) ∼ R −β is deterministicuatittenaonfunction,Fis randomfadingvariable.

Bartek Baszczyszyn

radio wave propagation models

signal power P emitted

emitter

R

i P

r P ec. receiver

detailed Maxwell's electromagnetic eld equations — too complex and not needed (D) Deterministic model:P rec. ≈ P emitted ¢ l(R) ,

wherel(R) ∼ R −β is deterministicitnoneauttafunction,

Bartek Baszczyszyn

radio wave propagation models

signal power P mittede

emitter

R

P i

r P ec. receiver

detailed Maxwell's electromagnetic eld equations — too complex and not needed (D) Deterministic model:P rec. ≈ P emitted ¢ l(R) , (G) Stochastic (“far-eld”)model:P rec. = P i P i C ≈ LT P emdetti ¢ F ¢ l(R) , wherel(R) ∼ R −β is deterministicneauattontifunction,Fis randomfadingvariable. (M) Rayleigh fading :Fisxleaoiptenn(=Z I 2 +F Q 2 whereZ I ,Z Q i.i.d. N(0,1))

Bartek Baszczyszyn