ARIMA-based time variation model for beneath the chassis UWB channel

Intra-vehicular wireless sensor network (IVWSN) enables the integration of the wireless sensor network technology into the vehicle architecture through either eliminating the wires between the existing sensors and the corresponding electronic controller units (ECUs) or empowering new sensor technologies that are not currently implemented due to technical limitations. Ultra-wideband (UWB) has been determined to be the most appropriate technology for IVWSNs since it provides energy efficiency through the low duty-cycle operation and high reliability by exploiting the large bandwidth. In this paper, we propose a time variation model for UWB-based IVWSN-based on the extensive amount of data collected from the transmitter and receiver antennas at various locations and separation distances beneath the chassis of a vehicle moving at different speeds on different types of roads. We adopt the commonly used Saleh-Valenzuela (SV) model to represent the clustering phenomenon in the received power delay profiles (PDPs). The proposed novel time variation model then determines the time evolution of the PDPs by representing the changes in their cluster breakpoints, slopes, and break point amplitudes with the auto-regressive integrated moving average (ARIMA) model. ARIMA(5,1,0) has been demonstrated to fit the breakpoint, cluster slope, and breakpoint amplitude sequences collected at different vehicle speeds with different transmitter and receiver locations on asphalt and stone roads by using Box-Jenkins procedure. This model is validated with diagnostic checking. The absolute values of the model coefficients are observed to be mostly larger on asphalt road than their counterparts on the stone road while exhibiting no dependence on the vehicle speed nor the location of transmitter and receiver antennas.