Advances in portable technologies and emergence of new applications stimulate interest in urban vehicular communications for commercial, military, and homeland defense applications. Simulation is an essential tool to study the behavior and evaluate the performance of protocols and applications in large-scale urban vehicular ad hoc networks (VANET). In this paper, we propose CORNER, a low computational cost yet accurate urban propagation model for mobile networks. CORNER estimates the presence of buildings and obstacles along the signal path using information extrapolated from urban digital maps. A reverse geocoding algorithm is used to classify the propagation situation of any two nodes that need to communicate starting from their geographical coordinates. We classify the relative position of the sender and the receiver as in line of sight (LOS) or nonline of sight (NLOS). Based on this classification, we apply different formulas to compute the path loss (PL) metric. CORNER has been validated through extensive on-the-road experiments, the results show high accuracy in predicting the network connectivity. In addition, on-the-road experiments suggest the need to refine the fading model to differentiate between LOS, and NLOS situations. Finally, we show the impact of CORNER on simulation results for widely used applications. © 2006 IEEE.

CORNER: A radio propagation model for VANETs in Urban scenarios

Giordano, Eugenio;Pau, Giovanni
;
2011

Abstract

Advances in portable technologies and emergence of new applications stimulate interest in urban vehicular communications for commercial, military, and homeland defense applications. Simulation is an essential tool to study the behavior and evaluate the performance of protocols and applications in large-scale urban vehicular ad hoc networks (VANET). In this paper, we propose CORNER, a low computational cost yet accurate urban propagation model for mobile networks. CORNER estimates the presence of buildings and obstacles along the signal path using information extrapolated from urban digital maps. A reverse geocoding algorithm is used to classify the propagation situation of any two nodes that need to communicate starting from their geographical coordinates. We classify the relative position of the sender and the receiver as in line of sight (LOS) or nonline of sight (NLOS). Based on this classification, we apply different formulas to compute the path loss (PL) metric. CORNER has been validated through extensive on-the-road experiments, the results show high accuracy in predicting the network connectivity. In addition, on-the-road experiments suggest the need to refine the fading model to differentiate between LOS, and NLOS situations. Finally, we show the impact of CORNER on simulation results for widely used applications. © 2006 IEEE.
Giordano, Eugenio; Frank, Raphael; Pau, Giovanni; Gerla, Mario
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/616735
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