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
Dalam makalah ini, kami mempertimbangkan reka bentuk prapengode untuk pengagregatan data wayarles dalam rangkaian penderia. Masalah pengoptimuman prakoder boleh dirumuskan sebagai meminimumkan ralat kuasa dua min di bawah kuasa penghantaran dan kekangan pepenjuru blok. Kami memasukkan korelasi statistik data ke dalam masalah pengoptimuman, yang muncul dalam aplikasi biasa tetapi diabaikan dalam kaedah reka bentuk konvensional. Kami mencadangkan algoritma pengoptimuman prakoder berdasarkan unjuran penurunan kecerunan dengan unjuran pada set kekangan. Kaedah yang dicadangkan boleh mencapai prestasi yang lebih baik daripada kaedah konvensional yang tidak menggabungkan korelasi data, terutamanya apabila data sangat berkorelasi. Kami juga melanjutkan pendekatan yang dicadangkan kepada konteks pengiraan melalui udara.
Ayano NAKAI-KASAI
https://orcid.org/0000-0003-0832-0423
Nagoya Institute of Technology
Naoyuki HAYASHI
https://orcid.org/0000-0003-4391-4294
Nagoya Institute of Technology
Tadashi WADAYAMA
Nagoya Institute of Technology
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Salinan
Ayano NAKAI-KASAI, Naoyuki HAYASHI, Tadashi WADAYAMA, "Precoder Optimization Using Data Correlation for Wireless Data Aggregation" in IEICE TRANSACTIONS on Communications,
vol. E107-B, no. 3, pp. 330-338, March 2024, doi: 10.23919/transcom.2023EBT0007.
Abstract: In this paper, we consider precoder design for wireless data aggregation in sensor networks. The precoder optimization problem can be formulated as minimization of mean squared error under transmit power and block diagonal constraints. We include statistical correlation of data into the optimization problem, which is appeared in typical applications but is ignored in conventional designing methods. We propose precoder optimization algorithms based on projected gradient descent with projection onto the constraint sets. The proposed method can achieve better performance than the conventional methods that do not incorporate data correlation, especially when data are highly correlated. We also extend the proposed approach to the context of over-the-air computation.
URL: https://global.ieice.org/en_transactions/communications/10.23919/transcom.2023EBT0007/_p
Salinan
@ARTICLE{e107-b_3_330,
author={Ayano NAKAI-KASAI, Naoyuki HAYASHI, Tadashi WADAYAMA, },
journal={IEICE TRANSACTIONS on Communications},
title={Precoder Optimization Using Data Correlation for Wireless Data Aggregation},
year={2024},
volume={E107-B},
number={3},
pages={330-338},
abstract={In this paper, we consider precoder design for wireless data aggregation in sensor networks. The precoder optimization problem can be formulated as minimization of mean squared error under transmit power and block diagonal constraints. We include statistical correlation of data into the optimization problem, which is appeared in typical applications but is ignored in conventional designing methods. We propose precoder optimization algorithms based on projected gradient descent with projection onto the constraint sets. The proposed method can achieve better performance than the conventional methods that do not incorporate data correlation, especially when data are highly correlated. We also extend the proposed approach to the context of over-the-air computation.},
keywords={},
doi={10.23919/transcom.2023EBT0007},
ISSN={1745-1345},
month={March},}
Salinan
TY - JOUR
TI - Precoder Optimization Using Data Correlation for Wireless Data Aggregation
T2 - IEICE TRANSACTIONS on Communications
SP - 330
EP - 338
AU - Ayano NAKAI-KASAI
AU - Naoyuki HAYASHI
AU - Tadashi WADAYAMA
PY - 2024
DO - 10.23919/transcom.2023EBT0007
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E107-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2024
AB - In this paper, we consider precoder design for wireless data aggregation in sensor networks. The precoder optimization problem can be formulated as minimization of mean squared error under transmit power and block diagonal constraints. We include statistical correlation of data into the optimization problem, which is appeared in typical applications but is ignored in conventional designing methods. We propose precoder optimization algorithms based on projected gradient descent with projection onto the constraint sets. The proposed method can achieve better performance than the conventional methods that do not incorporate data correlation, especially when data are highly correlated. We also extend the proposed approach to the context of over-the-air computation.
ER -