Efficient Sampling Rate Offset Compensation - an Overlap-Save Based Approach. Schmalenstroeer, J. & Haeb-Umbach, R. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 499-503, Sep., 2018.
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Paper doi abstract bibtex
Paper doi abstract bibtex Distributed sensor data acquisition usually encompasses data sampling by the individual devices, where each of them has its own oscillator driving the local sampling process, resulting in slightly different sampling rates at the individual sensor nodes. Nevertheless, for certain downstream signal processing tasks it is important to compensate even for small sampling rate offsets. Aligning the sampling rates of oscillators which differ only by a few parts-per-million, is, however, challenging and quite different from traditional multirate signal processing tasks. In this paper we propose to transfer a precise but computationally demanding time domain approach, inspired by the Nyquist-Shannon sampling theorem, to an efficient frequency domain implementation. To this end a buffer control is employed which compensates for sampling offsets which are multiples of the sampling period, while a digital filter, realized by the well-known Overlap-Save method, handles the fractional part of the sampling phase offset. With experiments on artificially misaligned data we investigate the parametrization, the efficiency, and the induced distortions of the proposed resampling method. It is shown that a favorable compromise between residual distortion and computational complexity is achieved, compared to other sampling rate offset compensation techniques.
@InProceedings{8553379,
author = {J. Schmalenstroeer and R. Haeb-Umbach},
booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
title = {Efficient Sampling Rate Offset Compensation - an Overlap-Save Based Approach},
year = {2018},
pages = {499-503},
abstract = {Distributed sensor data acquisition usually encompasses data sampling by the individual devices, where each of them has its own oscillator driving the local sampling process, resulting in slightly different sampling rates at the individual sensor nodes. Nevertheless, for certain downstream signal processing tasks it is important to compensate even for small sampling rate offsets. Aligning the sampling rates of oscillators which differ only by a few parts-per-million, is, however, challenging and quite different from traditional multirate signal processing tasks. In this paper we propose to transfer a precise but computationally demanding time domain approach, inspired by the Nyquist-Shannon sampling theorem, to an efficient frequency domain implementation. To this end a buffer control is employed which compensates for sampling offsets which are multiples of the sampling period, while a digital filter, realized by the well-known Overlap-Save method, handles the fractional part of the sampling phase offset. With experiments on artificially misaligned data we investigate the parametrization, the efficiency, and the induced distortions of the proposed resampling method. It is shown that a favorable compromise between residual distortion and computational complexity is achieved, compared to other sampling rate offset compensation techniques.},
keywords = {computational complexity;data acquisition;digital filters;distributed sensors;frequency-domain analysis;signal sampling;time-domain analysis;computational complexity;digital filter;buffer control;overlap-save based approach;sampling rate offset compensation;frequency domain implementation;Nyquist-Shannon sampling theorem;time domain approach;multirate signal processing;artificially misaligned data;sampling rate offsets;downstream signal processing tasks;individual sensor nodes;local sampling process;data sampling;distributed sensor data acquisition;Frequency-domain analysis;Interpolation;Oscillators;Task analysis;Europe;Distortion;Overlap-Save method;sampling rate offset;resampling},
doi = {10.23919/EUSIPCO.2018.8553379},
issn = {2076-1465},
month = {Sep.},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570429285.pdf},
}Downloads: 0
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Nevertheless, for certain downstream signal processing tasks it is important to compensate even for small sampling rate offsets. Aligning the sampling rates of oscillators which differ only by a few parts-per-million, is, however, challenging and quite different from traditional multirate signal processing tasks. In this paper we propose to transfer a precise but computationally demanding time domain approach, inspired by the Nyquist-Shannon sampling theorem, to an efficient frequency domain implementation. To this end a buffer control is employed which compensates for sampling offsets which are multiples of the sampling period, while a digital filter, realized by the well-known Overlap-Save method, handles the fractional part of the sampling phase offset. With experiments on artificially misaligned data we investigate the parametrization, the efficiency, and the induced distortions of the proposed resampling method. 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