Frame Synchronization and Sampling Frequency Offset Estimation for Ambient Internet of Things

Backscatter communication and the ambient Internet of Things (AIoT) represent pivotal technologies for the future of IoT, offering the promise of ultra-low-power operation. However, the performance of AIoT systems is severely degraded by frequency offsets, especially sampling frequency offset (SFO). This paper addresses this critical issue by proposing effective techniques for SFO mitigation. Specifically, we first establish a system model that incorporates the deleterious effects of SFO. Then, we introduce a robust, energy-based frame synchronization scheme to accurately identify frame boundaries, thereby enhancing the precision of subsequent SFO estimation. Furthermore, we propose a frequency-domain SFO estimation algorithm coupled with a time-domain SFO compensation method. Simulation results validate the efficacy of the proposed frame synchronization, SFO estimation, and compensation schemes.