Architecture for AI-Enabled Multimodal Semantic Communication and Distributed Computing

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00389505" target="_blank" >RIV/68407700:21230/25:00389505 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/VTC2025-Spring65109.2025.11174887" target="_blank" >https://doi.org/10.1109/VTC2025-Spring65109.2025.11174887</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/VTC2025-Spring65109.2025.11174887" target="_blank" >10.1109/VTC2025-Spring65109.2025.11174887</a>

Result language
angličtina
Original language name
Architecture for AI-Enabled Multimodal Semantic Communication and Distributed Computing
Original language description
In this paper, we propose novel architecture supporting artificial intelligence-based multimodal semantic communication and distributed computing. The proposed architecture is built on existing concepts in adopted mobile networks, including cloud radio access network (C-RAN) and open-RAN (O-RAN). On top of current architectures, we introduce new key features including block for artificial intelligence (AI) training models for semantic encoding and decoding, semantic modules, and hierarchical edge cloud for distributed and parallel processing. Then, we formulate a delay minimization problem for processing of semantically encoded tasks by the hierarchical edge cloud. First, we derive optimal closed-form solutions for splitting the tasks between individual tiers of the hierarchical edge cloud while assuming actual communication and computing queues. Second, we propose a low-complexity algorithm selecting place, where the individual tasks are processed while adopting the optimal splitting of the tasks. Via simulations, we demonstrate that the proposed solution decreases average processing time and energy consumption due to computing by up to 50 % and 23 % when compared to the best performing state-of-the-art scheme.
Czech name
—
Czech description
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Project
<a href="/en/project/TH85010001" target="_blank" >TH85010001: AI-enabled Multimodal Semantic Communications and Computing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2025 IEEE 101st Vehicular Technology Conference: VTC2025-Spring
ISBN
979-8-3315-3147-8
ISSN
2577-2465
e-ISSN
2577-2465
Number of pages
7
Pages from-to
1-7
Publisher name
IEEE
Place of publication
Piscataway
Event location
Oslo
Event date
Jun 17, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001699882900605

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