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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.05030 |
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| _version_ | 1866913138424676352 |
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| author | Gerosa, Daniele Hou, Rui Björk, Vimar Gustavsson, Ulf Eriksson, Thomas |
| author_facet | Gerosa, Daniele Hou, Rui Björk, Vimar Gustavsson, Ulf Eriksson, Thomas |
| contents | This paper addresses the mathematical modeling and compensation of stochastic discrete-time clock jitter in analog-to-digital converters (ADCs). We model the stochastic clock jitter as a first-order autoregressive (AR(1)) process, and we propose two novel, computationally efficient, pilot-assisted dejittering algorithms for baseband signals: one based on solving a sequence of weighted least-squares problems, and another that exploits the correlated jitter structure via a Kalman filter-based routine. We also propose a conditional maximum-likelihood estimator for the autoregressive parameters, enabling near-optimal Kalman-filter performance even when such parameters vary over time. We further provide a mathematical analysis of the induced linearization errors, and we complement the theory with synthetic simulations to evaluate the proposed techniques across different scenarios. The proposed techniques are shown to yield a 1-15 dB improvement in signal-to-noise-and-distortion ratio (SINADR) and 0.02-1.6 dB in symbol error vector magnitude (EVM), depending on impairment severity and pilot density. The Kalman smoother generally provides superior performance by leveraging additional temporal information. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_05030 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Autoregressive Stochastic Clock Jitter Compensation in Analog-to-Digital Converters Gerosa, Daniele Hou, Rui Björk, Vimar Gustavsson, Ulf Eriksson, Thomas Signal Processing Optimization and Control This paper addresses the mathematical modeling and compensation of stochastic discrete-time clock jitter in analog-to-digital converters (ADCs). We model the stochastic clock jitter as a first-order autoregressive (AR(1)) process, and we propose two novel, computationally efficient, pilot-assisted dejittering algorithms for baseband signals: one based on solving a sequence of weighted least-squares problems, and another that exploits the correlated jitter structure via a Kalman filter-based routine. We also propose a conditional maximum-likelihood estimator for the autoregressive parameters, enabling near-optimal Kalman-filter performance even when such parameters vary over time. We further provide a mathematical analysis of the induced linearization errors, and we complement the theory with synthetic simulations to evaluate the proposed techniques across different scenarios. The proposed techniques are shown to yield a 1-15 dB improvement in signal-to-noise-and-distortion ratio (SINADR) and 0.02-1.6 dB in symbol error vector magnitude (EVM), depending on impairment severity and pilot density. The Kalman smoother generally provides superior performance by leveraging additional temporal information. |
| title | Autoregressive Stochastic Clock Jitter Compensation in Analog-to-Digital Converters |
| topic | Signal Processing Optimization and Control |
| url | https://arxiv.org/abs/2505.05030 |