In this paper, we introduce a framework of distributed orthogonal approximate message passing for recovering sparse vector based on sensing by multiple nodes. The iterative recovery process consists of local computation at each node, and global computation performed either by a particular node or joint computation on the overall network by exchanging messages. We then propose a method to reduce the communication cost between the nodes while maintaining the recovery performance.
Ken HISANAGA
Kwansei Gakuin University
Motohiko ISAKA
Kwansei Gakuin University
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Ken HISANAGA, Motohiko ISAKA, "Communication-Efficient Distributed Orthogonal Approximate Message Passing for Sparse Signal Recovery" in IEICE TRANSACTIONS on Fundamentals,
vol. E107-A, no. 3, pp. 493-502, March 2024, doi: 10.1587/transfun.2023TAP0018.
Abstract: In this paper, we introduce a framework of distributed orthogonal approximate message passing for recovering sparse vector based on sensing by multiple nodes. The iterative recovery process consists of local computation at each node, and global computation performed either by a particular node or joint computation on the overall network by exchanging messages. We then propose a method to reduce the communication cost between the nodes while maintaining the recovery performance.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2023TAP0018/_p
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@ARTICLE{e107-a_3_493,
author={Ken HISANAGA, Motohiko ISAKA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Communication-Efficient Distributed Orthogonal Approximate Message Passing for Sparse Signal Recovery},
year={2024},
volume={E107-A},
number={3},
pages={493-502},
abstract={In this paper, we introduce a framework of distributed orthogonal approximate message passing for recovering sparse vector based on sensing by multiple nodes. The iterative recovery process consists of local computation at each node, and global computation performed either by a particular node or joint computation on the overall network by exchanging messages. We then propose a method to reduce the communication cost between the nodes while maintaining the recovery performance.},
keywords={},
doi={10.1587/transfun.2023TAP0018},
ISSN={1745-1337},
month={March},}
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TY - JOUR
TI - Communication-Efficient Distributed Orthogonal Approximate Message Passing for Sparse Signal Recovery
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 493
EP - 502
AU - Ken HISANAGA
AU - Motohiko ISAKA
PY - 2024
DO - 10.1587/transfun.2023TAP0018
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E107-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2024
AB - In this paper, we introduce a framework of distributed orthogonal approximate message passing for recovering sparse vector based on sensing by multiple nodes. The iterative recovery process consists of local computation at each node, and global computation performed either by a particular node or joint computation on the overall network by exchanging messages. We then propose a method to reduce the communication cost between the nodes while maintaining the recovery performance.
ER -