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Adapting OFDM for vehicular communication requires extensive knowledge of anticipated multipath and Doppler environments. We present a GPS-enabled channel sounding system built and used to conduct a channel measurement campaign. Tests conducted at the 700 MHz band in and around downtown Ann Arbor, Michigan, explored various vehicle-to-vehicle and vehicle-to-roadside channel scenarios. The measured channel metrics are used to quantify the effects on guard interval, packet duration, and subcarrier spacing for a functional OFDM system at 700 MHz. This paper is one of the first to present vehicular-based channel-modeling results from measured data in the 700 MHz band.

Ramps events are a significant source of uncertainty in wind power generation. Developing statistical models from historical data for wind power ramps is important for designing intelligent distribution and market mechanisms for a future electric grid. This requires robust detection schemes for identifying wind ramps in data. In this paper, use an optimal detection technique for identifying wind ramps for large time series. The technique relies on defining a family of scoring functions associated with any rule for defining ramps on an interval of the time series. A dynamic programming recursion is then used to find all such ramp events. Identified wind ramps are used to perform an extensive statistical analysis on the process, characterizing ramping duration and rates as well as other key features needed for developing future models.