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The aim is to explore the integration of edge learning with communication optimization for effective data processing in B5G networks.

Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing

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The aim is to explore the integration of edge learning with communication optimization for effective data processing in B5G networks.
Overview of distributed edge learning techniques and their communication optimization.
Discussion of performance metrics for dual-functional networks.
Presentation of a mathematical model for goal-oriented semantic communication.
Identified challenges such as excessive signaling overhead and unstable learning convergence.
Proposed an optimization problem for goal-oriented source entropy in semantic communication.
Outlined emerging applications and research opportunities in edge learning within B5G networks.

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Provides an overview of edge learning and its impact on communication optimization in B5G networks, suggesting future research directions.

Xu et al. (2023) studied this question.

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Provides an overview of edge learning and its impact on communication optimization in B5G networks, suggesting future research directions.