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AWGN-goodness is enough: capacity-achieving lattice codes based on dithered probabilistic shaping

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Title: AWGN-goodness is enough: capacity-achieving lattice codes based on dithered probabilistic shaping
Authors: Campello, A
Dadush, D
Ling, C
Item Type: Journal Article
Abstract: In this paper we show that any sequence of infinite lattice constellations which is good for the unconstrained Gaussian channel can be shaped into a capacity-achieving sequence of codes for the power-constrained Gaussian channel under lattice decoding and non-uniform signalling. Unlike previous results in the literature, our scheme holds with no extra condition on the lattices (e.g. quantization-goodness or vanishing flatness factor), thus establishing a direct implication between AWGNgoodness, in the sense of Poltyrev, and capacity-achieving codes. Our analysis uses properties of the discrete Gaussian distribution in order to obtain precise bounds on the probability of error and achievable rates. In particular, we obtain a simple characterization of the finite-blocklength behavior of the scheme, showing that it approaches the optimal dispersion coefficient for high signalto- noise ratio. We further show that for low signal-to-noise ratio the discrete Gaussian over centered lattice constellations cannot achieve capacity, and thus a shift (or “dither”) is essentially necessary.
Issue Date: 1-Mar-2019
Date of Acceptance: 26-Aug-2018
URI: http://hdl.handle.net/10044/1/64716
DOI: https://dx.doi.org/10.1109/TIT.2018.2875004
ISSN: 0018-9448
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 1961
End Page: 1971
Journal / Book Title: IEEE Transactions on Information Theory
Volume: 65
Issue: 3
Copyright Statement: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Engineering
Information theory
channel coding
lattices
shaping
MODULATION
INEQUALITIES
CHANNEL
0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
1005 Communications Technologies
Networking & Telecommunications
Publication Status: Published
Open Access location: https://arxiv.org/pdf/1707.06688.pdf
Online Publication Date: 2018-10-09
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering