Efficient Statistical Modeling of Wireless Channels in Complex Reflective Spaces

Wireless connectivity within vehicles is becoming increasingly attractive due to advances in communications technologies and user expectations for these technologies. Thus, there is a great need for models of wireless channels inside vehicles. In this paper, we present a novel method for deriving wireless channel models in highly reflective environments, with a particular focus on intra-vehicular communication at 2.4 GHz. In contrast to traditional grid-based channel measurements, the proposed approach employs a time-efficient area-based measurement technique combined with statistical analysis of received signal strength distributions. The Cumulative Distribution Functions (CDFs) of the conducted measurements with different channel bandwidths reveal significant variation in small-scale fading behavior. To model these CDFs accurately, distribution functions, and a custom function are fitted on the channel behavior. The resulting channel model allows for reduced measurement complexity while enabling fast and reliable characterization of wireless channels in dynamic and reflective environments such as vehicle interiors.