Coordinated multi-point by distributed hierarchical active inference with sensor feedback

Otoshi, Tatsuya; Murata, Masayuki

doi:https://doi.org/10.1016/j.comnet.2024.110989

Coordinated multi-point by distributed hierarchical active inference with sensor feedback

Otoshi, Tatsuya; Murata, Masayuki

Computer Networks, 2025, 257, 110989

アクセス数:278件（2025-08-16 09:40 集計）

固定URL: https://hdl.handle.net/11094/100386

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タイトル	Coordinated multi-point by distributed hierarchical active inference with sensor feedback
著者	NRID 1000060804458 1000060804458 researchmap permalink t_otoshi t_otoshi Scopus Author ID 56263363100 56263363100 著者名 Otoshi, Tatsuya
著者	NRID 1000080200301 1000080200301 ORCID 0000-0002-4168-2875 0000-0002-4168-2875 researchmap permalink Masayuki-Murata Masayuki-Murata Scopus Author ID 55710952700 55710952700 著者名 Murata, Masayuki
キーワード等	Active inference
	Coordinated multi-point
	Free energy principle
	Position estimation
	Propagation channel estimation
内容	Otoshi T., Murata M. Coordinated multi-point by distributed hierarchical active inference with sensor feedback. Computer Networks 257, 110989 (2025); https://doi.org/10.1016/j.comnet.2024.110989.
抄録	This study focuses on cooperative beamforming among base stations in wireless communication technology and proposes a new approach based on the Free Energy Principle (FEP). Traditionally, the trade-off between the accuracy of channel information acquisition and overhead has posed a challenge in beamforming. FEP addresses this trade-off by balancing the value from observation and the value from action to select the optimal behavior. This enables adaptive responses to dynamic environmental fluctuations through integrated search, reasoning, and learning. Additionally, by introducing a hierarchical coordination structure, information sharing among base stations and indirect state sharing among agents are achieved, enhancing the efficiency and stability of beamforming. Furthermore, this study utilizes Integrated Sensing and Communication (ISAC) to perform simultaneous communication and real-world sensing. By integrating feedback from terminals and terminal location information for channel state estimation, the overhead is reduced. Simulation results demonstrate that the proposed method effectively improves the Signal to Interference and Noise Ratio (SINR) and energy efficiency.
出版者	Elsevier B.V.
収録物名	Computer Networks
巻(号)	257
ページ	110989
刊行年月	2025-02-01
言語	英語
ハンドルURL	https://hdl.handle.net/11094/100386
PISSN	13891286
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1016/j.comnet.2024.110989
アクセス権	open access
権利情報	This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCTERMS.bibliographicCitation	Computer Networks. 2025, 257, p. 110989
DC.title	Coordinated multi-point by distributed hierarchical active inference with sensor feedback
DC.creator	Otoshi, Tatsuya
DC.creator	Murata, Masayuki
DC.publisher	Elsevier B.V.
DC.language' scheme='DCTERMS.RFC1766	英語
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-02-01
DC.identifier	https://doi.org/10.1016/j.comnet.2024.110989
DC.subject	Active inference
	Coordinated multi-point
	Free energy principle
	Position estimation
	Propagation channel estimation
DC.description	Otoshi T., Murata M. Coordinated multi-point by distributed hierarchical active inference with sensor feedback. Computer Networks 257, 110989 (2025); https://doi.org/10.1016/j.comnet.2024.110989.
DCTERMS.abstract	This study focuses on cooperative beamforming among base stations in wireless communication technology and proposes a new approach based on the Free Energy Principle (FEP). Traditionally, the trade-off between the accuracy of channel information acquisition and overhead has posed a challenge in beamforming. FEP addresses this trade-off by balancing the value from observation and the value from action to select the optimal behavior. This enables adaptive responses to dynamic environmental fluctuations through integrated search, reasoning, and learning. Additionally, by introducing a hierarchical coordination structure, information sharing among base stations and indirect state sharing among agents are achieved, enhancing the efficiency and stability of beamforming. Furthermore, this study utilizes Integrated Sensing and Communication (ISAC) to perform simultaneous communication and real-world sensing. By integrating feedback from terminals and terminal location information for channel state estimation, the overhead is reduced. Simulation results demonstrate that the proposed method effectively improves the Signal to Interference and Noise Ratio (SINR) and energy efficiency.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	100386
citation_title	Coordinated multi-point by distributed hierarchical active inference with sensor feedback
citation_author	Otoshi, Tatsuya
citation_author	Murata, Masayuki
citation_publisher	Elsevier B.V.
citation_language	英語
citation_date	2025-02-01
citation_journal_title	Computer Networks
citation_volume	257
citation_firstpage	110989
citation_doi	https://doi.org/10.1016/j.comnet.2024.110989
citation_public_url	https://hdl.handle.net/11094/100386

Coordinated multi-point by distributed hierarchical active inference with sensor feedback

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