残留时间同步误差下环境反向散射通信的符号检测 (Symbol Detection in Ambient Backscatter Communications Under Residual Time Synchronization Errors)

Ambient backscatter communications (AmBC), where a backscatter transmitter (BT) modulates and reflects ambient signals to a backscatter receiver (BR), have been deemed a low-power communication technology for the Internet of Things. Previous work on symbol detection in AmBC assumed perfect time synchronization (TS), which is unrealistic in practice. The residual TS errors (RTSE) cause \emph{partial sample mismatch}, degrading symbol detection performance. To address this, we propose a new AmBC symbol detection framework that incorporates the BT's current and adjacent symbols, as well as channel coefficients. Using energy detector (ED) as a case study, we derive both exact and approximate bit error rate (BER) expressions. Our results show that the ED's BER performance degrades significantly under RTSE, with the symbol detection threshold optimized under the assumption of perfect TS. We then derive a closed-form expression for a near-optimal symbol detection threshold that minimizes BER under RTSE. To estimate the required parameters for the detection threshold, we propose a novel method exploiting the attributes of the BR's received signal samples. The analytical results are verified by simulation results.

翻译：环境反向散射通信（AmBC）中，反向散射发射器（BT）通过调制并反射环境信号至反向散射接收器（BR），已被视为物联网的低功耗通信技术。先前关于AmBC符号检测的研究均假设理想时间同步（TS），这在实际中难以实现。残留时间同步误差（RTSE）会导致部分采样失配，从而降低符号检测性能。为解决此问题，本文提出了一种新的AmBC符号检测框架，该框架综合考虑了BT当前及相邻符号以及信道系数。以能量检测器（ED）为例，我们推导了精确及近似的误码率（BER）表达式。结果表明，在RTSE影响下，基于理想TS假设优化的符号检测阈值会导致ED的BER性能显著恶化。为此，我们推导了在RTSE下最小化BER的近似最优符号检测阈值的闭式表达式。为估计检测阈值所需参数，我们提出了一种利用BR接收信号样本特性的新方法。仿真结果验证了理论分析的正确性。