Thresholds for Identification of Passive Wireless SAW Sensors with Barker Coding

摘要

This paper addresses a computational analysis of optimal thresholds for identification of remote passive wireless surface acoustic wave (SAW) sensors with Barker coding. The SAW sensor signal is considered to be narrowband in the presence of Gaussian noise induced by the receiver that makes the signal envelope Rician. The error probability for the coded SAW sensor is determined via the probability of the sum of errors caused by each of the reflectors on the sensor substrate. The error probability is minimized for the "0" signal envelopes having zero signal-to-noise ratios (SNRs) with the Rayleigh distributions and "1" signal envelopes with some given SNRs and the Rice distributions. It is shown that, for the derived probabilistic nonlinear integral equation, the optimal threshold cannot be found in simple functions and the computational analysis is required. The threshold has been found numerically and discussed for the known Barker codes.