-
FORSKNINGSLABB
-
Bredbandskommunikation
-
Elektronik
-
Kommunikation
-
Nätverk och säkerhet
-
Signalbehandling
-
Teoretisk elektroteknik
-
-
FORSKNING PÅ EIT
-
Centrumbildningar
-
Utrustning
-
Vetenskaplig excellens
-
Mest citerade artiklar
-
Mest nerladdade artiklar
-
Vetenskapliga böcker
-
Senaste publikationer
-
Publikationer
-
TagCloud-animering
-
Forskningprojekt
-
Alumni/Hedersdoktorer
-
Emeritus
|
- Referens:
-
- Title:
- Measurement based Shadow Fading Model for Vehicle-to-Vehicle Network Simulations
IEEE Transactions on Vehicular Technology: Special Section on Vehicular Network and Communication System, From Laboratory into Reality
- Type:
- article
- Keywords:
- Channel measurements, V2V, vehicular, VANET simulator, shadow fading model, large-scale fading
- Abstract:
- The Vehicle-to-Vehicle (V2V) propagation channel has significant implications on the design and performance of novel communication protocols for Vehicular Ad Hoc Networks (VANET). Extensive research efforts have been made to develop and implement V2V channel models for advanced VANET system simulators. The impact of shadowing caused by other vehicles has, however, largely been neglected in most of the models, as well as in the system simulations. In this paper we present a simple shadow fading model targeting system simulations based on real world measurements performed in urban and highway scenarios. Video information from the measurements is used to separate the line-of-sight (LOS) condition from the obstructed line-of-sight (OLOS) by vehicles and non line-of-sight (NLOS) by buildings. It is observed that the vehicles obstructing LOS induce an additional attenuation of about $10$\,dB in the received signal power. We use a Markov chain based state transition diagram to model transitions from LOS to obstructed LOS and present an example of state transition intensities for a real traffic mobility model. We also provide a simple recipe, how to incorporate our shadow fading model in VANET network simulators.
- Year:
- 2012
- MODS XML
Tillbaka
|
|