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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Penderiaan Mampat (CS) diketahui memberikan prestasi anggaran saluran yang lebih baik daripada kaedah Kuasa Dua Terkecil (LS) untuk anggaran saluran. Walau bagaimanapun, kelewatan berbilang laluan mungkin tidak dapat diselesaikan jika ia menjangkau antara grid. Masalah grid CS ini merupakan penghalang kepada anggaran saluran resolusi super. Pengecilan Norma Atom (AN) adalah salah satu kaedah untuk menganggar parameter berterusan. Pengurangan AN boleh berjaya memulihkan isyarat spektrum jarang daripada beberapa sampel domain masa walaupun kamus adalah berterusan. Terdapat kajian menunjukkan bahawa kaedah pengecilan AN mempunyai resolusi yang lebih baik daripada kaedah CS konvensional. Dalam kertas ini, kami mencadangkan kaedah anggaran saluran berdasarkan pengecilan AN untuk sistem Spread Spectrum (SS). Ketepatan anggaran saluran yang dicadangkan dibandingkan dengan kaedah LS konvensional dan Pemilih Dantzig (DS) CS. Sebagai tambahan kepada aplikasi anggaran saluran dalam komunikasi tanpa wayar, kami juga menunjukkan bahawa pengecilan AN boleh digunakan untuk Sistem Kedudukan Global (GPS) menggunakan jujukan Emas.
Dongshin YANG
The University of Kyushu
Yutaka JITSUMATSU
The University of Kyushu
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Salinan
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
Salinan
@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},}
Salinan
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 -