A measure preserving mapping for structured Grassmannian constellations in SIMO channels

Cuevas Fernández, Diego; Álvarez Vizoso, Javier; Beltrán Álvarez, Carlos; Santamaría Caballero, Luis Ignacio; Tucek, Vít; Peters, Gunnar

doi:10.1109/GLOBECOM48099.2022.10000914

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Identificadores

URI: https://hdl.handle.net/10902/27565

DOI: 10.1109/GLOBECOM48099.2022.10000914

ISBN: 978-1-6654-3540-6

Fecha

2022

Derechos

© 2022 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.

Publicado en

IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, 2022, 2394-2399

Editorial

Institute of Electrical and Electronics Engineers Inc.

Enlace a la publicación

https://doi.org/10.1109/GLOBECOM48099.2022.10000914

Palabras clave

Noncoherent communications

Grassmannian constellations

SIMO channels

Measure-preserving mapping

Resumen/Abstract

In this paper, we propose a new structured Grassmannian constellation for noncoherent communications over single-input multiple-output (SIMO) Rayleigh block-fading channels. The constellation, which we call Grass-Lattice, is based on a measure preserving mapping from the unit hypercube to the Grassmannian of lines. The constellation structure allows for on-the-fly symbol generation, low-complexity decoding, and simple bit-to-symbol Gray coding. Simulation results show that Grass-Lattice has symbol error rate performance close to that of a numerically optimized unstructured constellation, and is more power efficient than other structured constellations proposed in the literature.