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One-Bit Normalized Scatter Matrix Estimation For Complex Elliptically Symmetric Distributions

Liu, Chun-Lin and Vaidyanathan, P. P. (2020) One-Bit Normalized Scatter Matrix Estimation For Complex Elliptically Symmetric Distributions. In: 2020 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE , Piscataway, NJ, pp. 9130-9134. ISBN 9781509066315. https://resolver.caltech.edu/CaltechAUTHORS:20210304-101834311

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Abstract

One-bit quantization has attracted attention in massive MIMO, radar, and array processing, due to its simplicity, low cost, and capability of parameter estimation. Specifically, the shape of the covariance of the unquantized data can be estimated from the arcsine law and onebit data, if the unquantized data is Gaussian. However, in practice, the Gaussian assumption is not satisfied due to outliers. It is known from the literature that outliers can be modeled by complex elliptically symmetric (CES) distributions with heavy tails. This paper shows that the arcsine law remains applicable to CES distributions. Therefore, the normalized scatter matrix of the unquantized data can be readily estimated from one-bit samples derived from CES distributions. The proposed estimator is not only computationally fast but also robust to CES distributions with heavy tails. These attributes will be demonstrated through numerical examples, in terms of computational time and the estimation error. An application in DOA estimation with MUSIC spectrum is also presented.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/icassp40776.2020.9053956DOIArticle
ORCID:
AuthorORCID
Liu, Chun-Lin0000-0003-3135-9684
Vaidyanathan, P. P.0000-0003-3003-7042
Additional Information:© 2020 IEEE. The work of Chun-Lin Liu was supported by the Ministry of Science and Technology, Taiwan (Grant Number 108-2218-E-002-043-MY2), the Ministry of Education, Taiwan (Grant Number NTU-108V0902), and National Taiwan University. The work of P. P. Vaidyanathan was supported by the ONR grant N00014-18-1-2390, the NSF grant CCF-1712633, and the California Institute of Technology.
Funders:
Funding AgencyGrant Number
Ministry of Science and Technology (Taipei)108-2218-E-002-043-MY2
Ministry of Education (Taipei)NTU-108V0902
National Taiwan UniversityUNSPECIFIED
Office of Naval Research (ONR)N00014-18-1-2390
NSFCCF-1712633
CaltechUNSPECIFIED
Subject Keywords:One-bit quantization, complex elliptically symmetric distributions, arcsine law, robust statistics, scatter matrices
Record Number:CaltechAUTHORS:20210304-101834311
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210304-101834311
Official Citation:C. Liu and P. P. Vaidyanathan, "One-Bit Normalized Scatter Matrix Estimation For Complex Elliptically Symmetric Distributions," ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2020, pp. 9130-9134, doi: 10.1109/ICASSP40776.2020.9053956
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108312
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:04 Mar 2021 21:23
Last Modified:04 Mar 2021 21:23

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