Symbol Timing Synchronization and Signal Detection for Ambient Backscatter Communication
Yuxin Li, Guangyue Lu, Yinghui Ye, Zehui Xiong, Liqin Shi
TL;DR
The paper tackles symbol timing offset (STO) in ambient backscatter communication (AmBC) without coordination from the ambient RF source. It introduces a BD pilot design featuring alternating bit-pairs to induce sampling-errors, enabling a maximum likelihood estimation (MLE) of STO based on pilot variations, and integrates STO compensation into an energy-detection (ED) symbol detector. The proposed method achieves accurate STO estimation and markedly mitigates BER degradation caused by STO, with residual gaps limited by pilot length and estimation accuracy. This approach enables robust AmBC in non-cooperative environments, reducing reliance on controlled ambient transmitters and hardware complexity.
Abstract
Ambient backscatter communication (AmBC) enables ambient Internet of Things (AIoT) devices to achieve ultra-low-power, low-cost, and massive connectivity. Most existing AmBC studies assume ideal synchronization between the backscatter device (BD) and the backscatter receiver (BR). However, in practice, symbol timing offset (STO) occurs due to both the propagation delay and the BR activation latency, which leads to unreliable symbol recovery at the BR. Moreover, the uncontrollable nature of the ambient radio frequency source renders conventional correlation-based synchronization methods infeasible in AmBC. To address this challenge, we investigate STO estimation and symbol detection in AmBC without requiring coordination from the ambient radio frequency source. Firstly, we design a specialized pilot sequence at the BD to induce sampling errors in the pilot signal. Furthermore, we propose a pilot-based STO estimator using the framework of maximum likelihood estimation (MLE), which can exploit the statistical variations in the received pilot signal. Finally, we integrate STO compensation into an energy detector and evaluate the bit error rate (BER) performance. Simulation results show that the proposed estimator achieves accurate STO estimation and effectively mitigates the BER performance degradation caused by STO.
