Characterizing the spectral properties and time variation of the in-vehicle wireless communication channel

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Loh, TH 
Rigelsford, J 

To deploy effective communication systems in vehicle cavities, it is critical to understand the time variation of the in-vehicle channel. Initially rapid channel variation is addressed, which is characterised in the frequency domain as a Doppler spread. It is then shown that for typical Doppler spreads, the in-vehicle channel is underspread, and therefore the information capacity approaches the capacity achieved with perfect receiver channel state information in the infinite bandwidth limit. Measurements are performed for a number of channel variation scenarios (absorptive motion, reflective motion, one antenna moving, both antennas moving), at a number of carrier frequencies and for a number of cavity loading scenarios. It is found that the Doppler spread increases with carrier frequency, however the type of channel variation and loading appear to have little effect. Channel variation over a longer time period is also measured, to characterise the slower channel variation. Channel variation is a function of the cavity occupant motion, which is difficult to model theoretically, therefore an empirical model for the slow channel variation is proposed, which leads to an improved estimate of the channel state.

Vehicle cavities, reverberation chambers, electromagnetic cavities, Doppler spread, time correlation, auto-regressive model, information capacity, underspread channels
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IEEE Transactions on Communications
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Institute of Electrical and Electronics Engineers (IEEE)
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This work is supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) and National Physical Laboratory (NPL) under an EPSRC-NPL Industrial CASE studentship programme on the subject of intra-Vehicular Wireless Sensor Networks. The work of T. H. Loh was supported by the 2009 - 2012 Physical Program and 2012 - 2015 Electromagnetic Metrology Program of the National Measurement Office, an Executive Agency of the U.K. Department for Business, Innovation and Skills, under Projects 113860 and EMT13020, respectively.