Precoder Optimization Using Data Correlation for Wireless Data Aggregation

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...

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Bibliographic Details
Published in:IEICE Transactions on Communications 2024/03/01, Vol.E107.B(3), pp.330-338
Main Authors: NAKAI-KASAI, Ayano, HAYASHI, Naoyuki, WADAYAMA, Tadashi
Format: Article
Language:English
Subjects:
Algorithms
Data correlation
Data management
Optimization
over-the-air computation
precoder optimization
projected gradient descent
Statistical correlation
wireless data aggregation
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Summary: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.
ISSN:0916-8516
1745-1345
DOI:10.23919/transcom.2023EBT0007