Symbol Detection for Ambient Backscatter Communication With Multiple Ambient RF Sources in Space-Air-Ground Integrated Networks

Symbol detection is critical for ambient backscatter communication (AmBC) and its optimal detection threshold is sensitive to the distribution of the signal from the ambient radio frequency source. Existing work mainly focuses on symbol detection under the assumption of a single ambient RF source (S-ARF). However, in the space-air-ground integrated networks, multiple ambient RF sources (M-ARFs), including satellites, unmanned aerial vehicles and terrestrial base stations, often reuse the same RF resources, which makes the distribution of M-ARFs signals differ from that of an S-ARFs signal. In this paper, we investigate symbol detection for AmBC in the presence of M-ARFs. To this end, we model the M-ARFs signal as an aggregate signal with log-normally distributed power. On this basis, we formulate a maximum likelihood (ML) detector and obtain a closed-form approximate threshold using Hermite-Gauss Quadrature, which is effective under specific parameter conditions. Furthermore, to enhance generality and analyze the impact of aggregate signal parameters, we construct an energy detector (ED) and propose a novel log-energy detector (LED), for which we derive the expressions for bit error rate (BER) and near-optimal thresholds. Simulation results show that the aggregate signal can significantly degrade the BER performance when directly using the detection threshold assuming an S-ARF. In contrast, the ML and ED based on the proposed detection framework can mitigate the performance degradation, and LED can achieve superior BER performance.