6G Network AI Architecture for Everyone-Centric Customized Services
Abstract
Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions.
Cite
@article{arxiv.2205.09944,
title = {6G Network AI Architecture for Everyone-Centric Customized Services},
author = {Yang Yang and Mulei Ma and Hequan Wu and Quan Yu and Ping Zhang and Xiaohu You and Jianjun Wu and Chenghui Peng and Tak-Shing Peter Yum and Sherman Shen and Hamid Aghvami and Geoffrey Y Li and Jiangzhou Wang and Guangyi Liu and Peng Gao and Xiongyan Tang and Chang Cao and John Thompson and Kat-Kit Wong and Shanzhi Chen and Merouane Debbah and Schahram Dustdar and Frank Eliassen and Tao Chen and Xiangyang Duan and Shaohui Sun and Xiaofeng Tao and Qinyu Zhang and Jianwei Huang and Shuguang Cui and Wenjun Zhang and Jie Li and Yue Gao and Honggang Zhang and Xu Chen and Xiaohu Ge and Yong Xiao and Cheng-Xiang Wang and Zaichen Zhang and Song Ci and Guoqiang Mao and Changle Li and Ziyu Shao and Yong Zhou and Junrui Liang and Kai Li and Liantao Wu and Fanglei Sun and Kunlun Wang and Zening Liu and Kun Yang and Jun Wang and Teng Gao and Hongfeng Shu},
journal= {arXiv preprint arXiv:2205.09944},
year = {2023}
}
Comments
The current version has partial Insufficient completion, so we would like to withdraw it. We hope you agree, thank you