We introduce predictive communication algorithms for channel estimation and equalization in vehicular environments. The proposed concept makes use of vehicular sensors combined with unique properties of surrounding environment to predict future changes in the communication scenario. This combination enables a new range of improvements in the direct-link vehicular communications. Among others, it allows predicting the Doppler frequency shift for some strong channel components in highly dynamic scenarios and estimating the likelihood for the communicating vehicles to remain in the line-of-sight conditions. A predictive Doppler-shift compensation is presented as an illustrative example of one of potential benefits for future vehicular communications. The algorithm is applied to compensate the strong line-of-sight component as well as the line-of-sight with one strong reflection which is received at the same sampling interval. The obtained simulation results show that the proposed sensor-based Doppler-shift prediction and compensation approach outperforms a benchmark least-squares channel estimation with linear interpolation algorithm in various road scenarios (urban, rural, and highway) and relative driving directions (same and oncoming) of communicating vehicles.
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Alieiev et al. (2018) studied this question.
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