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

Otoshi, Tatsuya; Murata, Masayuki

Computer Networks, 2025, 257, 110989

Number of Access:278（2025-08-14 07:22 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/100386

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Title
Coordinated multi-point by distributed hierarchical active inference with sensor feedback
Creator
NRID
1000060804458 1000060804458
researchmap permalink
t_otoshi t_otoshi
Scopus Author ID
56263363100 56263363100
CreatorName
Otoshi, Tatsuya
NRID
1000080200301 1000080200301
ORCID
0000-0002-4168-2875 0000-0002-4168-2875
researchmap permalink
Masayuki-Murata Masayuki-Murata
Scopus Author ID
55710952700 55710952700
CreatorName
Murata, Masayuki
Subject
Active inference
Coordinated multi-point
Free energy principle
Position estimation
Propagation channel estimation
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.
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.
Publisher
Elsevier B.V.
Source Title
Computer Networks
Volume (Issue)
257
Page
110989
Date of Issued
2025-02-01
Language
English
Handle URL
https://hdl.handle.net/11094/100386
PISSN
13891286
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.1016/j.comnet.2024.110989
Access Rights
open access
CopyRight
This article is licensed under a Creative Commons Attribution 4.0 International License.
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Version of Record
Category
学術雑誌論文 Journal Article