| Paper ID | SPTM-18.3 |
| Paper Title |
MODIFIED ARCSINE LAW FOR ONE-BIT SAMPLED STATIONARY SIGNALS WITH TIME-VARYING THRESHOLDS |
| Authors |
Arian Eamaz, University of Illinois at Chicago, United States; Farhang Yeganegi, Amirkabir University of Technology, Iran; Mojtaba Soltanalian, University of Illinois at Chicago, United States |
| Session | SPTM-18: Sampling Theory, Analysis and Methods |
| Location | Gather.Town |
| Session Time: | Thursday, 10 June, 15:30 - 16:15 |
| Presentation Time: | Thursday, 10 June, 15:30 - 16:15 |
| Presentation |
Poster
|
| Topic |
Signal Processing Theory and Methods: [SMDSP] Sampling, Multirate Signal Processing and Digital Signal Processing |
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| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
One-bit quantization has attracted considerable attention in signal processing for communications and sensing. The arcsine law is a useful relation often used to estimate the normalized covariance matrix of zero-mean stationary input signals when they are sampled by one-bit analog-to-digital converters (ADCs)—practically comparing the signals with a given threshold level. This relation, however, only considers a zero threshold which can cause a remarkable information loss. For the first time in the literature, this paper introduces an approach to extending the arcsine law to the case where one-bit ADCs apply time-varying thresholds. In particular, the proposed method is shown to accurately recover the variance and autocorrelation of the stationary signals of interest. |
