SemRAN: Semantic Radio Access Networks with Collective Knowledge Sharing in 6G and Beyond

Semantic communications are considered the next stage for the communications industry, particularly the unique fusion of channel coding and source coding for wireless communications, such as the joint source channel coding (JSCC) with AL/ML trained encoders/decoders. However, the critical challenge of implementing semantic communications methodology in 6G and beyond are two folds: a) The circulation of source and channel information and b) The distribution of shared knowledge both in the public domain and between peers. This paper introduces a generic semantic-ready architecture for future networks by exchanging channel information with source information in purpose-built reasoning plane functions and service-oriented integration architecture. Besides, the paper proposes a novel distributed knowledge exchange scheme resembling social network characteristics. The proposed architecture enables collaborative semantic processing between users and networks with privacy-preserving computing and storage resource configuration using coherent social knowledge bases. With extensive simulations on three datasets, our proposed architecture demonstrates advancements in decoding accuracy, transmission latency, as well as computational efficiency.

Authors

Institutions

Publication Details

Published
2024-11-18
DOI
https://doi.org/10.1109/fcn64323.2024.10985555
Primary Topic
Cooperative Communication and Network Coding
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SemRAN: Semantic Radio Access Networks with Collective Knowledge Sharing in 6G and Beyond

Kan Zhu, Mérouane Debbah, Hao Xu, Weichao Chen
Cooperative Communication and Network Coding
article

SemRAN: Semantic Radio Access Networks with Collective Knowledge Sharing in 6G and Beyond

Kan Zhu, Mérouane Debbah, Hao Xu, Weichao Chen
article en

Abstract

Semantic communications are considered the next stage for the communications industry, particularly the unique fusion of channel coding and source coding for wireless communications, such as the joint source channel coding (JSCC) with AL/ML trained encoders/decoders. However, the critical challenge of implementing semantic communications methodology in 6G and beyond are two folds: a) The circulation of source and channel information and b) The distribution of shared knowledge both in the public domain and between peers. This paper introduces a generic semantic-ready architecture for future networks by exchanging channel information with source information in purpose-built reasoning plane functions and service-oriented integration architecture. Besides, the paper proposes a novel distributed knowledge exchange scheme resembling social network characteristics. The proposed architecture enables collaborative semantic processing between users and networks with privacy-preserving computing and storage resource configuration using coherent social knowledge bases. With extensive simulations on three datasets, our proposed architecture demonstrates advancements in decoding accuracy, transmission latency, as well as computational efficiency.

Tongji University (CN), Khalifa University of Science and Technology (AE)
National Natural Science Foundation of China, Tongji University, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 65%
Cooperative Communication and Network Coding
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

SemRAN: Semantic Radio Access Networks with Collective Knowledge Sharing in 6G and Beyond — Kan Zhu, Mérouane Debbah, et al. · (2024) | TGRS Research Map | TGRS