Related papers: Large AI Models for Wireless Physical Layer

Large AI Models for Wireless Physical Layer

URL: http://arxiv.org/abs/2508.02314v1
Date: Mon, 04 Aug 2025 11:30:33 GMT
Title: Large AI Models for Wireless Physical Layer
Authors: Jiajia Guo, Yiming Cui, Shi Jin, Jun Zhang,
Abstract summary: Large artificial intelligence models (LAMs) are transforming wireless physical layer technologies through their robust generalization, multitask processing, and multimodal capabilities.<n>This article reviews recent advancements in LAM applications for physical layer communications, addressing limitations of conventional AI-based approaches.
Score: 44.387744480376284
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Large artificial intelligence models (LAMs) are transforming wireless physical layer technologies through their robust generalization, multitask processing, and multimodal capabilities. This article reviews recent advancements in LAM applications for physical layer communications, addressing limitations of conventional AI-based approaches. LAM applications are classified into two strategies: leveraging pre-trained LAMs and developing native LAMs designed specifically for physical layer tasks. The motivations and key frameworks of these approaches are comprehensively examined through multiple use cases. Both strategies significantly improve performance and adaptability across diverse wireless scenarios. Future research directions, including efficient architectures, interpretability, standardized datasets, and collaboration between large and small models, are proposed to advance LAM-based physical layer solutions for next-generation communication systems.

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