The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
La détection compressée (CS) est connue pour fournir de meilleures performances d'estimation de canal que la méthode des moindres carrés (LS) pour l'estimation de canal. Toutefois, les retards liés aux trajets multiples peuvent ne pas être résolus s'ils s'étendent entre les grilles. Ce problème de grille de CS est un obstacle à l’estimation des canaux en super résolution. Une minimisation de norme atomique (AN) est l'une des méthodes d'estimation de paramètres continus. La minimisation AN peut récupérer avec succès un signal spectralement clairsemé à partir de quelques échantillons du domaine temporel, même si le dictionnaire est continu. Certaines études montrent que la méthode de minimisation AN a une meilleure résolution que les méthodes CS conventionnelles. Dans cet article, nous proposons une méthode d'estimation de canal basée sur la minimisation AN pour les systèmes à spectre étalé (SS). La précision de l'estimation de canal proposée est comparée à la méthode LS conventionnelle et au sélecteur Dantzig (DS) du CS. En plus de l'application de l'estimation de canal dans la communication sans fil, nous montrons également que la minimisation AN peut être appliquée au système de positionnement global (GPS) en utilisant la séquence Gold.
Dongshin YANG
The University of Kyushu
Yutaka JITSUMATSU
The University of Kyushu
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Dongshin YANG, Yutaka JITSUMATSU, "Super Resolution Channel Estimation by Using Spread Spectrum Signal and Atomic Norm Minimization" in IEICE TRANSACTIONS on Fundamentals,
vol. E101-A, no. 12, pp. 2141-2148, December 2018, doi: 10.1587/transfun.E101.A.2141.
Abstract: Compressed Sensing (CS) is known to provide better channel estimation performance than the Least Square (LS) method for channel estimation. However, multipath delays may not be resolved if they span between the grids. This grid problem of CS is an obstacle to super resolution channel estimation. An Atomic Norm (AN) minimization is one of the methods for estimating continuous parameters. The AN minimization can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. There are studies showing that the AN minimization method has better resolution than conventional CS methods. In this paper, we propose a channel estimation method based on the AN minimization for Spread Spectrum (SS) systems. The accuracy of the proposed channel estimation is compared with the conventional LS method and Dantzig Selector (DS) of the CS. In addition to the application of channel estimation in wireless communication, we also show that the AN minimization can be applied to Global Positioning System (GPS) using Gold sequence.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E101.A.2141/_p
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@ARTICLE{e101-a_12_2141,
author={Dongshin YANG, Yutaka JITSUMATSU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Super Resolution Channel Estimation by Using Spread Spectrum Signal and Atomic Norm Minimization},
year={2018},
volume={E101-A},
number={12},
pages={2141-2148},
abstract={Compressed Sensing (CS) is known to provide better channel estimation performance than the Least Square (LS) method for channel estimation. However, multipath delays may not be resolved if they span between the grids. This grid problem of CS is an obstacle to super resolution channel estimation. An Atomic Norm (AN) minimization is one of the methods for estimating continuous parameters. The AN minimization can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. There are studies showing that the AN minimization method has better resolution than conventional CS methods. In this paper, we propose a channel estimation method based on the AN minimization for Spread Spectrum (SS) systems. The accuracy of the proposed channel estimation is compared with the conventional LS method and Dantzig Selector (DS) of the CS. In addition to the application of channel estimation in wireless communication, we also show that the AN minimization can be applied to Global Positioning System (GPS) using Gold sequence.},
keywords={},
doi={10.1587/transfun.E101.A.2141},
ISSN={1745-1337},
month={December},}
Copier
TY - JOUR
TI - Super Resolution Channel Estimation by Using Spread Spectrum Signal and Atomic Norm Minimization
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2141
EP - 2148
AU - Dongshin YANG
AU - Yutaka JITSUMATSU
PY - 2018
DO - 10.1587/transfun.E101.A.2141
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E101-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2018
AB - Compressed Sensing (CS) is known to provide better channel estimation performance than the Least Square (LS) method for channel estimation. However, multipath delays may not be resolved if they span between the grids. This grid problem of CS is an obstacle to super resolution channel estimation. An Atomic Norm (AN) minimization is one of the methods for estimating continuous parameters. The AN minimization can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. There are studies showing that the AN minimization method has better resolution than conventional CS methods. In this paper, we propose a channel estimation method based on the AN minimization for Spread Spectrum (SS) systems. The accuracy of the proposed channel estimation is compared with the conventional LS method and Dantzig Selector (DS) of the CS. In addition to the application of channel estimation in wireless communication, we also show that the AN minimization can be applied to Global Positioning System (GPS) using Gold sequence.
ER -