Wireless Large AI Model: Shaping the AI-Native Future of 6G and Beyond
Mérouane Debbah Kaibin Huang Wei Feng Tingting Yang Baoming Bai Feifei Gao Kun Yang Yuanwei Liu Sami Muhaidat Chau Yuen Fenghao Zhu Xinquan Wang Siming Jiang Xinyi Li Maojun Zhang Yixuan Chen Chongwen Huang Zhaohui Yang Xiaoming Chen Dusit Niyato Ying-Chang Liang Zhaoyang Zhang Richeng Jin Yongming Huang Kai-Kit Wong
作者信息
Abstract
The emergence of sixth-generation and beyond communication systems is expected to fundamentally transform digital experiences through introducing unparalleled levels of intelligence, efficiency, and connectivity. A promising technology poised to enable this revolutionary vision is the wireless large AI model (WLAM), characterized by its exceptional capabilities in data processing, inference, and decision-making. In light of these remarkable capabilities, this paper provides a comprehensive survey of WLAM, elucidating its fundamental principles, diverse applications, critical challenges, and future research opportunities. We begin by introducing the background of WLAM and analyzing the key synergies with wireless networks, emphasizing the mutual benefits. Subsequently, we explore the foundational characteristics of WLAM, delving into their unique relevance in wireless environments. Then, the role of WLAM in optimizing wireless communication systems across various use cases and the reciprocal benefits are systematically investigated. Furthermore, we discuss the integration of WLAM with emerging technologies, highlighting their potential to enable transformative capabilities and breakthroughs in wireless communication. Finally, we thoroughly examine the high-level challenges hindering the practical implementation of WLAM and discuss pivotal future research directions.引用本文复制引用
Mérouane Debbah,Kaibin Huang,Wei Feng,Tingting Yang,Baoming Bai,Feifei Gao,Kun Yang,Yuanwei Liu,Sami Muhaidat,Chau Yuen,Fenghao Zhu,Xinquan Wang,Siming Jiang,Xinyi Li,Maojun Zhang,Yixuan Chen,Chongwen Huang,Zhaohui Yang,Xiaoming Chen,Dusit Niyato,Ying-Chang Liang,Zhaoyang Zhang,Richeng Jin,Yongming Huang,Kai-Kit Wong.Wireless Large AI Model: Shaping the AI-Native Future of 6G and Beyond[EB/OL].(2025-12-18)[2025-12-23].https://arxiv.org/abs/2504.14653.学科分类
无线通信/通信/计算技术、计算机技术
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