Low-Complexity Voronoi Shaping for the Gaussian Channel
Journal article, 2021

Voronoi constellations (VCs) are finite sets of vectors of a coding lattice enclosed by the translated Voronoi region of a shaping lattice, which is a sublattice of the coding lattice. In conventional VCs, the shaping lattice is a scaled-up version of the coding lattice. In this paper, we design low-complexity VCs with a cubic coding lattice of up to 32 dimensions, in which pseudo-Gray labeling is applied to minimize the bit error rate. The designed VCs have considerable shaping gains of up to 1.03 dB and finer choices of spectral efficiencies in practice compared with conventional VCs. A mutual information estimation method and a log-likelihood approximation method based on importance sampling for very large constellations are proposed and applied to the designed VCs. With error-control coding, the proposed VCs can have higher information rates than the conventional scaled VCs because of their inherently good pseudo-Gray labeling feature, with a lower decoding complexity.

Spectral efficiency

Generators

Geometric shaping

Encoding

Constellation diagram

information rates

Gain

multidimensional modulation formats

Lattices

Decoding

Voronoi constellation

lattices

Author

Shen Li

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks, Communication Systems

Ali Mirani

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

Magnus Karlsson

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

Erik Agrell

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks, Communication Systems

IEEE Transactions on Communications

00906778 (ISSN)

Vol. 70 2 865-873

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Subject Categories

Telecommunications

Control Engineering

Signal Processing

DOI

10.1109/TCOMM.2021.3130286

More information

Latest update

2/18/2022