TY - GEN
T1 - AI-native User-Centric Network for 6G
AU - Li, Chen
AU - Hua, Wang
AU - Ming, Ai
AU - Shaohui, Sun
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - User-centric network (UCN) is a promising network architecture compared with the base station (BS) centric cellular network. However, it faces lots of challenges in deployment and standardization because of its coordination complexity, computation load and higher requirements for the equipment implementation. In 6G era, new technologies such as artificial intelligence (AI), cognitive communication and computing force network will be leveraged and integrated in the wireless network. For new services, such as eXtened Reality (XR) and holographic type communication (HTC), quality of experience satisfaction of user is more important. Taking into account those trends, we propose the AI-native UCN for 6G in this paper. The basic structure of UCN includes cloud based control plane, edge/distributed user plane and intelligence plane. Then two aspects of AI-native have been discussed i.e., the AI for network will be used to make the UCN achievable, and the network for AI will solve the generation, transmission and Quality of Service (QoS) guarantee of the AI workflow in radio access network (RAN) internal. With AI-native UCN, the 6G network will be simple, flexible, and energy saving.
AB - User-centric network (UCN) is a promising network architecture compared with the base station (BS) centric cellular network. However, it faces lots of challenges in deployment and standardization because of its coordination complexity, computation load and higher requirements for the equipment implementation. In 6G era, new technologies such as artificial intelligence (AI), cognitive communication and computing force network will be leveraged and integrated in the wireless network. For new services, such as eXtened Reality (XR) and holographic type communication (HTC), quality of experience satisfaction of user is more important. Taking into account those trends, we propose the AI-native UCN for 6G in this paper. The basic structure of UCN includes cloud based control plane, edge/distributed user plane and intelligence plane. Then two aspects of AI-native have been discussed i.e., the AI for network will be used to make the UCN achievable, and the network for AI will solve the generation, transmission and Quality of Service (QoS) guarantee of the AI workflow in radio access network (RAN) internal. With AI-native UCN, the 6G network will be simple, flexible, and energy saving.
KW - 6G
KW - AI-native
KW - UCN
KW - intelligence plane
UR - http://www.scopus.com/inward/record.url?scp=85141212560&partnerID=8YFLogxK
U2 - 10.1109/ICCCWorkshops55477.2022.9896699
DO - 10.1109/ICCCWorkshops55477.2022.9896699
M3 - Conference contribution
AN - SCOPUS:85141212560
T3 - 2022 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2022
SP - 494
EP - 499
BT - 2022 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2022
Y2 - 11 August 2022 through 13 August 2022
ER -