Toward 6G Native-AI Network: Foundation Model based Cloud-Edge-End Collaboration Framework

A. Bongale, “5GSpecAnalyzer AI: The 3GPP expert system,” [Online]. Available: https://chatgpt.com/g/g-4nsEnCW9o-5gspecanalyzer-ai-the-3gpp-expert-system, Accessed on Mar., 2025

2008

Earlier work this paper cites.

G. Liu et al. , “Vision, requirements and network architecture of 6G mobile network beyond 2030,” China Commun. , vol. 17, no. 9, pp. 92–104, 2020

2020

Earlier work this paper cites.

W. Tong et al. , “Nine challenges in artificial intelligence and wireless communications for 6G,” IEEE Wireless Commun. , vol. 29, no. 4, pp. 140–145, 2022

2022

Earlier work this paper cites.

E. Kartsakli et al. , “An evolutionary edge computing architecture for the beyond 5G era,” in Proc. CAMAD 2023, Edinburgh, United Kingdom, November 6-8, 2023 , pp. 61–67

2023

Earlier work this paper cites.

N. Ding et al. , “Parameter-efficient fine-tuning of large-scale pre-trained language models,” Nat. Mac. Intell. , vol. 5, no. 3, pp. 220–235, 2023

2023

Earlier work this paper cites.

Y. Yang et al. , “Task-oriented 6G native-AI network architecture,” IEEE Network , vol. 38, no. 1, pp. 219–227, 2024

2024

Cited alongside, same era.

J. Du et al. , “Distributed foundation models for multi-modal learning in 6G wireless networks,” IEEE Wireless Commun. , vol. 31, no. 3, pp. 20–30, 2024

2024

Cited alongside, same era.

H. Du et al. , “Mixture of experts for network optimization: A large language model-enabled approach,” in Proc. IWCMC 2024, Ayia Napa, Cyprus, May 27-31, 2024 , pp. 1–6

2024

Cited alongside, same era.

Z. Chen et al. , “Big AI models for 6G wireless networks: Opportunities, challenges, and research directions,” IEEE Wireless Commun. , vol. 31, no. 5, pp. 164–172, 2024

2024

Cited alongside, same era.

Y. Chen et al. , “NetGPT: A native-AI network architecture beyond provisioning personalized generative services,” Available as ArXiv:2307.06148 , 2024

Y. Gao et al. , “Retrieval-augmented generation for large language models: A survey,” Available as ArXiv:/2312.10997 , 2024

2024

Closest in time.

D. Edge et al. , “From local to global: A graph RAG approach to query-focused summarization,” Available as ArXiv: 2404.16130 , 2024

2024

Closest in time.

Z. Tang, D. Rybin, and T. Chang, “Zeroth-order optimization meets human feedback: Provable learning via ranking oracles,” in Proc. ICLR 2024, Vienna, Austria, May 7-11, 2024 , pp. 1–31

2024

Closest in time.

B. J. D. Gort et al. , “Forecasting trends in cloud-edge computing: Unleashing the power of attention mechanisms,” IEEE Commun. Mag. , vol. 63, no. 1, pp. 108–114, 2025

2025

Closest in time.

C. Chaccour et al. , “Less data, more knowledge: Building next generation semantic communication networks,” IEEE Commun. Surv. Tut. , vol. 27, no. 1, pp. 37–76, 2025