Abstract
Vibrational radar backscatter communication (VRBC) utilizes millimeter-wave radar vibrometry to receive message signals from vibrating surfaces. So long as multiple transponding surfaces are separable by the system radar in angle and/or range, VRBC can simultaneously detect, isolate, and decode messages from these multiple sources. For anything-to-vehicle communications, VRBC is therefore a scalable, low-latency approach which leverages existing automotive radars to increase situational awareness without requiring any additional use of the RF spectrum. In this paper, we describe the modeling and processing of VRBC signals. We show that knowledge of surface resonances and coding constraints can be used to improve system performance by incorporating them into a Markov model. We provide insight into the rate capabilities of VRBC by providing a theoretical upper bound that incorporates the presence of intersymbol interference (ISI). Simulation results compare our upper bound to achievable communication rates using single symbol vs sequence detection maximum likelihood methods for a given symbol length, set of symbol excitations, and VRBC radar pulse repetition interval (PRI).
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