On the Estimation of Nonrandom Signal Coefficients From Jittered Samples

This paper examines the problem of estimating the parameters of a bandlimited signal from samples corrupted by random jitter (timing noise) and additive, independent identically distributed (i.i.d.) Gaussian noise, where the signal lies in the span of a finite basis. For the presented classical esti...

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Main Authors: Goyal, Vivek K., Weller, Daniel Stuart
Other Authors: Massachusetts Institute of Technology. Research Laboratory of Electronics
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
Online Access:http://hdl.handle.net/1721.1/73123
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author Goyal, Vivek K.
Weller, Daniel Stuart
author2 Massachusetts Institute of Technology. Research Laboratory of Electronics
author_facet Massachusetts Institute of Technology. Research Laboratory of Electronics
Goyal, Vivek K.
Weller, Daniel Stuart
author_sort Goyal, Vivek K.
collection MIT
description This paper examines the problem of estimating the parameters of a bandlimited signal from samples corrupted by random jitter (timing noise) and additive, independent identically distributed (i.i.d.) Gaussian noise, where the signal lies in the span of a finite basis. For the presented classical estimation problem, the Cramér-Rao lower bound (CRB) is computed, and an Expectation-Maximization (EM) algorithm approximating the maximum likelihood (ML) estimator is developed. Simulations are performed to study the convergence properties of the EM algorithm and compare the performance both against the CRB and a basic linear estimator. These simulations demonstrate that by postprocessing the jittered samples with the proposed EM algorithm, greater jitter can be tolerated, potentially reducing on-chip ADC power consumption substantially.
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spelling mit-1721.1/731232022-09-29T16:33:14Z On the Estimation of Nonrandom Signal Coefficients From Jittered Samples Goyal, Vivek K. Weller, Daniel Stuart Massachusetts Institute of Technology. Research Laboratory of Electronics Goyal, Vivek K. Weller, Daniel Stuart This paper examines the problem of estimating the parameters of a bandlimited signal from samples corrupted by random jitter (timing noise) and additive, independent identically distributed (i.i.d.) Gaussian noise, where the signal lies in the span of a finite basis. For the presented classical estimation problem, the Cramér-Rao lower bound (CRB) is computed, and an Expectation-Maximization (EM) algorithm approximating the maximum likelihood (ML) estimator is developed. Simulations are performed to study the convergence properties of the EM algorithm and compare the performance both against the CRB and a basic linear estimator. These simulations demonstrate that by postprocessing the jittered samples with the proposed EM algorithm, greater jitter can be tolerated, potentially reducing on-chip ADC power consumption substantially. National Defense Science and Engineering Graduate Fellowship National Science Foundation (U.S.) (CAREER Grant 0643836) Texas Instruments Leadership University Consortium Program Analog Devices, inc. 2012-09-24T17:54:32Z 2012-09-24T17:54:32Z 2010-11 2010-10 Article http://purl.org/eprint/type/JournalArticle 1053-587X 1941-0476 http://hdl.handle.net/1721.1/73123 Weller, Daniel S., and Vivek K Goyal. “On the Estimation of Nonrandom Signal Coefficients From Jittered Samples.” IEEE Transactions on Signal Processing 59.2 (2011): 587–597. en_US http://dx.doi.org/ 10.1109/tsp.2010.2090347 IEEE Transactions on Signal Processing Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) arXiv
spellingShingle Goyal, Vivek K.
Weller, Daniel Stuart
On the Estimation of Nonrandom Signal Coefficients From Jittered Samples
title On the Estimation of Nonrandom Signal Coefficients From Jittered Samples
title_full On the Estimation of Nonrandom Signal Coefficients From Jittered Samples
title_fullStr On the Estimation of Nonrandom Signal Coefficients From Jittered Samples
title_full_unstemmed On the Estimation of Nonrandom Signal Coefficients From Jittered Samples
title_short On the Estimation of Nonrandom Signal Coefficients From Jittered Samples
title_sort on the estimation of nonrandom signal coefficients from jittered samples
url http://hdl.handle.net/1721.1/73123
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