A Three-State Received Signal Strength Model for Integrated Sensing and Backscatter Communication

Backscatter communication (BC) can enable nar-rowband radio frequency (RF) sensing with lower power con-sumption and lower system complexity compared with conventional sensing systems with active transmitter-receiver (TX -RX) pairs. To integrate sensing in the BC scenario, this paper investi-gates the impact of human position on the received signal strength (RSS). We first derive a new RSS model for the BC scenario based on three states: non-fading, reflection, and shadowing, depending on the location of the person with respect to line-of-sight (LoS) link. We validate the model by indoor measurements and compare it with the three-state model of the active TX-RX scenario. The measurements show that the proposed model accurately predicts human-induced RSS changes. Furthermore, we observe that human-induced RSS variances in the BC scheme are higher than those in the TX-RX scenario, benefiting variance-based sensing methods. Therefore, the proposed model can be implemented in low-power BC-enabled device-free sensing applications, such as human presence detection and device-free localization.