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Issue No. 04 - April (2016 vol. 15)
ISSN: 1536-1233
pp: 868-882
Xiaohui Wang , , Electrical and Computer Engineering, Pittsburgh, PA
Eric Anderson , , Electrical and Computer Engineering, Pittsburgh, PA
Peter Steenkiste , , Electrical and Computer Engineering, Pittsburgh, PA
Fan Bai , , ECI Lab, General Motors Global R&D, Warren, Michigan
Networking research benefits from controlled, repeatable experimentation using simulation and emulation systems. Making simulations realistic is a challenge for wireless systems and is especially difficult for vehicular networks. This paper presents a general framework for modeling and reproducing environment-specific channel properties. We show that one can estimate localized environment information, and adding such information to state-of-the art channel models significantly increases accuracy. We describe the proposed framework and validate it for fading and line-of-sight effects in vehicle-to-vehicle channels. While suitable models can provide a close approximation of channel conditions, accuracy is limited by the quality of the input information about the environment being modeled. We present a systematic approach to estimating location-specific scattering properties using aerial photography. Using signal-level channel emulation, we show that the improved fading models produce more accurate results at the packet/link level. The error rates of the improved model are 45 and 22 percent lower than using previous state of the art, for Doppler spectrum similarity and packet delivery ratio, respectively. The proposed models—and their implementation—have been designed to minimize run-time complexity while preserving accuracy. The implementation is efficient gh to allow concurrent real-time simulation of many of channels.
Fading, Doppler effect, Channel models, Computational modeling, Accuracy, Roads, Computer architecture

X. Wang, E. Anderson, P. Steenkiste and F. Bai, "Improving the Accuracy of Environment-Specific Channel Modeling," in IEEE Transactions on Mobile Computing, vol. 15, no. 4, pp. 868-882, 2016.
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