Distributed recovery of a Gaussian source in interference with successive lattice processing

Christian Chapman; Matthew Kinsinger; Ameya Agaskar; Daniel W. Bliss

doi:10.3390/e21090845

Distributed recovery of a Gaussian source in interference with successive lattice processing

Christian Chapman, Matthew Kinsinger, Ameya Agaskar, Daniel W. Bliss

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

A scheme for recovery of a signal by distributed listeners in the presence of Gaussian interference is constructed by exhausting an "iterative power reduction" property. An upper bound for the scheme's achieved mean-squared-error distortion is derived. The strategy exposes a parameter search problem, which, when solved, causes the scheme to outperform others of its kind. Performance of a blocklength-one scheme is simulated and is seen to improve over plain source coding without compression in the presence of many interferers, and experiences less outages over ensembles of channels.

Original language	English (US)
Article number	845
Journal	Entropy
Volume	21
Issue number	9
DOIs	https://doi.org/10.3390/e21090845
State	Published - 2019

Keywords

Distributed source coding
Lattice codes
Network information theory

ASJC Scopus subject areas

Physics and Astronomy(all)

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10.3390/e21090845

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AU - Agaskar, Ameya

AU - Bliss, Daniel W.

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N2 - A scheme for recovery of a signal by distributed listeners in the presence of Gaussian interference is constructed by exhausting an "iterative power reduction" property. An upper bound for the scheme's achieved mean-squared-error distortion is derived. The strategy exposes a parameter search problem, which, when solved, causes the scheme to outperform others of its kind. Performance of a blocklength-one scheme is simulated and is seen to improve over plain source coding without compression in the presence of many interferers, and experiences less outages over ensembles of channels.

AB - A scheme for recovery of a signal by distributed listeners in the presence of Gaussian interference is constructed by exhausting an "iterative power reduction" property. An upper bound for the scheme's achieved mean-squared-error distortion is derived. The strategy exposes a parameter search problem, which, when solved, causes the scheme to outperform others of its kind. Performance of a blocklength-one scheme is simulated and is seen to improve over plain source coding without compression in the presence of many interferers, and experiences less outages over ensembles of channels.

KW - Distributed source coding

KW - Lattice codes

KW - Network information theory

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JO - Entropy

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ER -

Distributed recovery of a Gaussian source in interference with successive lattice processing

Abstract

Keywords

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