TY - JOUR
T1 - GainNet
T2 - Coordinates the Odd Couple of Generative AI and 6G Networks
AU - Chen, Ning
AU - Yang, Jie
AU - Cheng, Zhipeng
AU - Fan, Xuwei
AU - Liu, Zhang
AU - Huang, Bangzhen
AU - Zhao, Yifeng
AU - Huang, Lianfen
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 1986-2012 IEEE.
PY - 2024
Y1 - 2024
N2 - The rapid expansion of AI-generated content (AIGC) reflects the iteration from assistive AI towards generative AI (GAI). Meanwhile, the 6G networks will also evolve from the Internet-of-Everything to the Internet-of-Intelligence. However, they seem to be an odd couple, due to the contradiction of data and resources. To achieve a better-coordinated interplay between GAI and 6G, the GAI-native Networks (GainNet), a GAI-oriented collaborative cloud-edge-end intelligence framework, is proposed in this article. By deeply integrating GAI with 6G network design, GainNet realizes the positive closed-loop knowledge flow and sustainable-evolution GAI model optimization. On this basis, the GAI-oriented generic Resource Orchestration Mechanism with Integrated Sensing, Communication, and Computing (GaiRomISCC) is proposed to guarantee the efficient operation of GainNet. Two simple case studies demonstrate the effectiveness and robustness of the proposed schemes. Finally, we envision the key challenges and future directions concerning the interplay between GAI models and 6G networks.
AB - The rapid expansion of AI-generated content (AIGC) reflects the iteration from assistive AI towards generative AI (GAI). Meanwhile, the 6G networks will also evolve from the Internet-of-Everything to the Internet-of-Intelligence. However, they seem to be an odd couple, due to the contradiction of data and resources. To achieve a better-coordinated interplay between GAI and 6G, the GAI-native Networks (GainNet), a GAI-oriented collaborative cloud-edge-end intelligence framework, is proposed in this article. By deeply integrating GAI with 6G network design, GainNet realizes the positive closed-loop knowledge flow and sustainable-evolution GAI model optimization. On this basis, the GAI-oriented generic Resource Orchestration Mechanism with Integrated Sensing, Communication, and Computing (GaiRomISCC) is proposed to guarantee the efficient operation of GainNet. Two simple case studies demonstrate the effectiveness and robustness of the proposed schemes. Finally, we envision the key challenges and future directions concerning the interplay between GAI models and 6G networks.
KW - 6G
KW - collaborative cloud-edge-end intelligence
KW - communication
KW - computing
KW - generative AI
KW - integrated sensing
KW - resource orchestration
UR - http://www.scopus.com/inward/record.url?scp=85197040545&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85197040545&partnerID=8YFLogxK
U2 - 10.1109/MNET.2024.3418671
DO - 10.1109/MNET.2024.3418671
M3 - Article
AN - SCOPUS:85197040545
SN - 0890-8044
VL - 38
SP - 56
EP - 65
JO - IEEE Network
JF - IEEE Network
IS - 5
ER -