A BER-Based Partitioned Model for a 2.4GHz Vehicle-to-Vehicle Expressway Channel

Abstract

Statistical channel models based on BER performance are presented for a frequency-and time-selective vehicle-to-vehicle wireless communications link in an expressway environment in Atlanta, Georgia, where both vehicles traveled in the same direction. The models are developed from measurements taken using the direct sequence spread spectrum (DSSS) technique at 2.45 GHz. A collection of tapped delay line models, referred to as a "partitioned" model in the paper, is developed to attempt to capture the extremes of BER performance of the recorded channel. Overall and partition models are compared to the recorded channel in terms of the BER statistics obtained when the channels are inserted in a dedicated short range radio (DSRC) standard simulation system. The quality of the match between synthesized and recorded channel BER statistics is analyzed with respect to type of modulation (fixed or adaptive), the frame length, and the length of the interval over which the BER was calculated.

Propagation aspects of vehicle-to-vehicle communications - an overview

“…Ref. [18][19] describe the fading in each resolvable delay bin as Rician, and show from their experiments that the Rice factor in the first delay bin can be very high (up to 20 dB), while it is much lower for later delay bins. Similar behavior, though with somewhat different Rice factors, is found in [22] where fading of individual scatterers is studied.…”

“…The nonstationarities can be modeled by (i) a birth/death process to account for the appearance and disappearance of taps [6]; it must be noted that while this approach provides a nonstationary description, it does not account for the "drift" of scatterers into a different delay bin, and can also lead to a sudden appearance and disappearance of strong MPCs. (ii) defining different tap models for regions of a measurement route that have significantly different delay spreads, or whose PDPs lead to significantly different BERs [18]; however, such an approach does not provide a continuous (with time) characterizationof the channel; or (iii) using geometry-based channel models, which take nonstationarities into account automatically [22].…”

“…Ref. [18] showed that for each region of stationarity, a different tap-model should be used; if the simulation model is based on a single averaged PDP from which the realizations are drawn, the resulting BERs in a system simulation deviate considerably from the BERs resulting from the raw measured channel data. Ref.…”

Rapid Prototyping for Evaluating Vehicular Communications

“…In recent years several research papers have presented mobile and vehicular channel models that try to reflect the continuously changing conditions of the environment (60,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133).…”

“…Most of these models have been developed for SISO transceivers (60,116,117,118,120,121,123,124,127,128,130,132,133), while a few are specific for multiple-antenna systems (119,122,125,126,129,131). These vehicular models can be also classified depending on the way they were obtained, distinguishing physical models (116,117,118,124,125,126,129,130,131,132,133), empirical models (60,121,122,123,127,128) and models that mix empirical measurements and physical developments (119,120).…”