Symbol Detection in Ambient Backscatter Communications Under Residual Time Synchronization Errors

2025-12-17

AI Summary

Residual time synchronization error (RTSE) in ambient backscatter communication causes sampling mismatch, degrading symbol detection performance. Method: We propose a novel symbol detection framework jointly leveraging the current and neighboring symbols along with channel coefficients. For the first time under RTSE, we derive a closed-form expression for a near-optimal detection threshold. We further design a parameter estimation algorithm based on the statistical properties of received signal samples, eliminating reliance on perfect synchronization. Energy detector modeling, quantitative RTSE analysis, and sample-level mismatch compensation are integrated to mitigate sampling distortion. Results: The theoretically derived bit error rate (BER) expression aligns closely with simulation results. The optimized threshold enables detection performance approaching the ideal-synchronization limit. Our approach establishes an analytically tractable and practically implementable paradigm for robust symbol detection under non-ideal synchronization conditions.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

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.

Problem

• Addresses symbol detection degradation in ambient backscatter communications due to residual time synchronization errors
• Proposes a new detection framework incorporating current and adjacent symbols with channel coefficients
• Derives a near-optimal detection threshold to minimize bit error rate under synchronization errors

Innovation

• Incorporates current and adjacent symbols with channel coefficients
• Derives closed-form near-optimal threshold minimizing BER
• Proposes novel parameter estimation from received signal samples