Noise-Robust-Based Clock Parameter Estimation and Low-Overhead Time Synchronization in Time-Sensitive Industrial Internet of Things
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| Publicado en: | Entropy vol. 27, no. 9 (2025), p. 927-947 |
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| Otros Autores: | , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 024 | 7 | |a 10.3390/e27090927 |2 doi | |
| 035 | |a 3254508944 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231460 |2 nlm | ||
| 100 | 1 | |a Tang, Long |u Guangxi Key Laboratory of Braininspired Computing and Intelligent Chips, School of Electronic and Information Engineering, Guangxi Normal University, Guilin 541001, China; 17823537490@163.com (L.T.); lifangyan@mailbox.gxnu.edu.cn (F.L.) | |
| 245 | 1 | |a Noise-Robust-Based Clock Parameter Estimation and Low-Overhead Time Synchronization in Time-Sensitive Industrial Internet of Things | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Time synchronization is critical for task-oriented and time-sensitive Industrial Internet of Things (IIoT) systems. Nevertheless, achieving high-precision synchronization with low communication overhead remains a key challenge due to the constrained resources of IIoT devices. In this paper, we propose a single-timestamp time synchronization scheme that significantly reduces communication overhead by utilizing the mechanism of AP to periodically collect sensor device data. The reduced communication overhead alleviates network congestion, which is essential for achieving low end-to-end latency in synchronized IIoT networks. Furthermore, to mitigate the impact of random delay noise on clock parameter estimation, we propose a noise-robust-based Maximum Likelihood Estimation (NR-MLE) algorithm that jointly optimizes synchronization accuracy and resilience to random delays. Specifically, we decompose the collected timestamp matrix into two low-rank matrices and use gradient descent to minimize reconstruction error and regularization, approximating the true signal and removing noise. The denoised timestamp matrix is then used to jointly estimate clock skew and offset via MLE, with the corresponding Cramér–Rao Lower Bounds (CRLBs) being derived. The simulation results demonstrate that the NR-MLE algorithm achieves a higher clock parameter estimation accuracy than conventional MLE and exhibits strong robustness against increasing noise levels. | |
| 653 | |a Lower bounds | ||
| 653 | |a Accuracy | ||
| 653 | |a Regularization | ||
| 653 | |a Cramer-Rao bounds | ||
| 653 | |a Random variables | ||
| 653 | |a Parameter estimation | ||
| 653 | |a Communication | ||
| 653 | |a Industrial Internet of Things | ||
| 653 | |a Parameter sensitivity | ||
| 653 | |a Sensors | ||
| 653 | |a Network latency | ||
| 653 | |a Noise levels | ||
| 653 | |a Parameter robustness | ||
| 653 | |a Algorithms | ||
| 653 | |a Energy efficiency | ||
| 653 | |a Maximum likelihood estimation | ||
| 653 | |a Time synchronization | ||
| 653 | |a Energy consumption | ||
| 653 | |a Central limit theorem | ||
| 653 | |a Robustness | ||
| 700 | 1 | |a Li Fangyan |u Guangxi Key Laboratory of Braininspired Computing and Intelligent Chips, School of Electronic and Information Engineering, Guangxi Normal University, Guilin 541001, China; 17823537490@163.com (L.T.); lifangyan@mailbox.gxnu.edu.cn (F.L.) | |
| 700 | 1 | |a Yu Zichao |u Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230022, China; zichaoyu@mail.ustc.edu.cn | |
| 700 | 1 | |a Zeng Haiyong |u Guangxi Key Laboratory of Braininspired Computing and Intelligent Chips, School of Electronic and Information Engineering, Guangxi Normal University, Guilin 541001, China; 17823537490@163.com (L.T.); lifangyan@mailbox.gxnu.edu.cn (F.L.) | |
| 773 | 0 | |t Entropy |g vol. 27, no. 9 (2025), p. 927-947 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3254508944/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3254508944/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3254508944/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |