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| 1 | 6G智慧内生:技术挑战、架构和关键特征显示文摘人工智能技术在5G网络中的应用促进了移动通信网络和垂直行业的智能化发展,但以'打补丁'和'外挂'的应用模式阻碍了AI应用效果的发挥。同时,人工智能在各行各业的应用探索,对未来网络新的基础能力提出了需求,如分布式训练、实时协作推理、本地数据处理等,要求未来网络具有'内生智慧'。从5G网络智能化和6G'智慧泛在'愿景两方面出发探讨了6G智慧内生的需求,分析了AI生命周期工作流和云网络AIaa S存在的技术挑战,总结了当前各行业组织对AI功能架构的研究进展和欠缺之处,提出了6G智慧内生端到端功能部署架构及其三大技术特征:基于Qo AIS的AI全生命周期服务编排、内生AI计算与通信的深度融合、内生AI与数字孪生的融合,并对后续研究方向进行了展望。 | 刘光毅 邓娟 郑青碧 李刚 孙欣 黄宇红 | 2021 | 移动通信2021，45，4： | 16 |
| 2 | 智能轨道交通中无线通信技术应用与展望显示文摘鉴于无线通信系统是轨道交通智能化升级改造的关键,首先分析了轨道交通无线通信的特征和面临的挑战,在此基础上,结合机器学习、毫米波、D2D通信等新兴的信息技术,提出了基于机器学习的信道建模方法、基于生成对抗网络(Generative Adversarial Network,GAN)的信道估计、毫米波波束切换和动态功率分配方案以及基于多智能体深度强化学习智能频谱共享方案,为智能轨道交通中无线通信应用提供解决方案;最后,展望未来智能轨道交通中无线通信技术的发展方向。 | 张青苗 赵军辉 张丹阳 吴遥 董翰智 | 2022 | 无线电通信技术2022，48，5： | 4 |
| 3 | 空天地网络确定性服务架构、挑战及关键技术显示文摘面向空天地全域垂直行业用户极致通信的需求,协同地面移动通信网络和快速发展的非地面(NTN)通信网络,打破传统“尽力而为”的僵化服务模式,为用户提供全域确定性服务是未来6G通信重要的发展方向之一。首先,概述了未来空天地一体化组网架构及该架构下的确定性服务内涵与场景需求,并提出了一种面向全域网络的确定性服务管控技术框架。然后,分析了全域确定性服务过程中面临的三大挑战,包括全域全场景用户业务感知难以保障、空天地一体端到端切片组网编排困难和切片子网内全域多维资源协同快速调度困难等问题。针对上述挑战,分别介绍了基于智能云的全域全场景业务感知技术、基于网络拓扑预测的星地端到端智能切片编排和数据与模型驱动的星地资源智能分配技术三个解决方案,为空天地一体网络极致服务技术的发展提供参考。 | 曹欢 陈岩 周一青 苏泳涛 刘子凡 陈道进 丁雅帅 | 2023 | 西安电子科技大学学报2023，50，3： | 3 |
| 4 | 意图抽象与知识联合驱动的6G内生智能网络架构显示文摘6G将以智能网络为演进形式,具备内生智能、开放性的特征。智能网络标准化研究中强调了意图驱动网络对实现网络智能化的必要性。但目前基于意图的网络将意图理解为“What to do”而非“What you want”,利用知识定义网络(KDN)可在一定程度上根据“What to do”完成“How to configure the network”。基于此,提出了意图抽象与知识联合驱动的6G内生智能网络架构,旨在根据“What you want”实现“How to configure the network”。首先,设计了意图抽象模块,通过意图获取、意图转译、意图映射和意图建模,从“What you want”获取“What to do”。其次,提出了认知模块,利用机器学习和逻辑推理联合动态优化获取网络知识,从而根据“What to do”完成“How to configure the network”。最后,介绍了支撑6G内生智能实现的意图映射、网络信息测量、网络策略生成、网络策略验证等关键技术及未来挑战。 | 杨静雅 唐晓刚 周一青 刘玲 Jiangzhou Wang | 2023 | 通信学报2023，44，2： | 2 |
| 5 | An intelligent wireless transmission toward 6G显示文摘With the deployment and commercial application of 5G,researchers start to think of 6G,which could meet more diversified and deeper intelligent communication requirements.In this paper,a four physical elements,i.e.,man,machine,object,and genie,featured 6G concept is introduced.Genie is explained as a new element toward 6G.This paper focuses on the genie realization as an intelligent wireless transmission toward 6G,including sematic information theory,end-to-end artificial intelligence(AI)joint transceiver design,intelligent wireless transmission block design,and user-centric intelligent access.A comprehensive state-of-the-art of each key technology is presented and main questions as well as some novel suggestions are given.Genie will work comprehensively in 6G wireless communication and other major industrial vertical,while its realization is concrete and step by step.It is realized that genie-based wireless communication link works with high intelligence and performs better than that controlled manually. | Ping Zhang Lihua Li Kai Niu Yaxian Li Guangyan Lu Zhaoyuan Wang | 2021 | Intelligent and Converged Networks2021，2，3： | 2 |
| 6 | 6G密集网络中基于深度强化学习的资源分配策略显示文摘6G密集网络(DN)中通过资源分配实现小区间无交叠干扰是提升网络性能的重要技术,但资源受限和节点密集分布使其很难通过传统的优化方法解决资源分配问题。针对此问题,建立了基于点线图染色的交叠干扰模型,将深度强化学习(DRL)和交叠干扰模型相结合,提出一种基于竞争深度Q网络(Dueling DQN)的资源分配方法。该方法利用交叠干扰模型与资源复用率设计即时奖励,利用Dueling DQN自主学习生成6G DN资源分配策略,实现小区间无交叠干扰的资源分配。仿真实验表明,所提方法可有效提高网络吞吐量和资源复用率,提升网络性能。 | 杨凡 杨成 黄杰 张仕龙 喻涛 左迅 杨川 | 2023 | 通信学报2023，44，8： | 1 |
| 7 | Intelligent Decision Making Framework for 6G Network显示文摘Sixth Generation(6G)wireless communication network has been expected to provide global coverage,enhanced spectral efficiency,and AI(Artificial Intelligence)-native intelligence,etc.To meet these requirements,the computational concept of Decision-Making of cognition intelligence,its implementation framework adapting to foreseen innovations on networks and services,and its empirical evaluations are key techniques to guarantee the generationagnostic intelligence evolution of wireless communication networks.In this paper,we propose an Intelligent Decision Making(IDM)framework,acting as the role of network brain,based on Reinforcement Learning modelling philosophy to empower autonomous intelligence evolution capability to 6G network.Besides,usage scenarios and simulation demonstrate the generality and efficiency of IDM.We hope that some of the ideas of IDM will assist the research of 6G network in a new or different light. | Zheng Hu Ping Zhang Chunhong Zhang Benhui Zhuang Jianhua Zhang Shangjing Lin Tao Sun | 2022 | China Communications2022，19，3： | 0 |
| 8 | REVIEW 6G and Internet of Things:a survey显示文摘The 5G networks which have begun to spread worldwide are expected to contribute to an increase in the use of Internet of Things(IoT)technologies and applications,which require massive connectivity,security,and ultra-low latency.However,it is known that 5G alone is not sufficient for many IoT devices to exchange various types of data in real time.These constraints promote the emergence of 6G technologies which can support higher network capacity,lower latency,and faster data transmission than 5G networks.To understand the current trends in 6G research and their relation to IoT,this paper introduces the main drivers of 6G technology,describes 6G’s enabling technologies,summarizes current 6G research,and introduces the possible applications of 6G to IoT technologies and service areas. | Jin Ho Kim | 2021 | Journal of Management Analytics2021，8，2： | 0 |
| 9 | A vision of 6G-5G’s successor显示文摘6G represents the next generation of mobile communication and mobile networking.Following the previous five generations of mobile communication systems(from 1G to 5G),the development of the 6G mobile communication will be a revolution.As a holographic and ubiquitous multidimensional network,6G will present us with the ability to establish full coverage of the“air–space–sea–land”system and to integrate with AI,IoT,and blockchain to form a network ecosystem.Our study addresses and emphasizes the literature that focuses on the technological perspectives of 6G,most specifically,its technological characteristics,key enabling technologies,and potential applications.In addition,a thorough description of the development of the mobile communication system from 1G to 6G is illustrated.This paper plays the important role of introducing a technological view of 6G to practitioners and researchers. | Yang Lu Xue Ning | 2020 | Journal of Management Analytics2020，7，3： | 0 |
| 10 | Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey显示文摘Data-driven paradigms are well-known and salient demands of future wireless communication. Empowered by big data and machine learning techniques,next-generation data-driven communication systems will be intelligent with unique characteristics of expressiveness, scalability, interpretability, and uncertainty awareness, which can confidently involve diversified latent demands and personalized services in the foreseeable future. In this paper, we review a promising family of nonparametric Bayesian machine learning models,i.e., Gaussian processes(GPs), and their applications in wireless communication. Since GP models demonstrate outstanding expressive and interpretable learning ability with uncertainty, they are particularly suitable for wireless communication. Moreover, they provide a natural framework for collaborating data and empirical models(DEM). Specifically, we first envision three-level motivations of data-driven wireless communication using GP models. Then, we present the background of the GPs in terms of covariance structure and model inference. The expressiveness of the GP model using various interpretable kernels, including stationary, non-stationary, deep and multi-task kernels,is showcased. Furthermore, we review the distributed GP models with promising scalability, which is suitable for applications in wireless networks with a large number of distributed edge devices. Finally, we list representative solutions and promising techniques that adopt GP models in various wireless communication applications. | Kai Chen Qinglei Kong Yijue Dai Yue Xu Feng Yin Lexi Xu Shuguang Cui | 2022 | China Communications2022，19，1： | 0 |
| 11 | Native intelligence for 6G mobile network: technical challenges,architecture and key features显示文摘The application of the artificial intelligence(AI) technology in the 5 th generation mobile communication system(5 G) networks promotes the development of the mobile communication network and its application in vertical industries, however, the application models of 'patching' and 'plug-in' have hindered the effect of AI applications. Meanwhile, the application of AI in all walks of life puts forward requirements for new capabilities of the future network, such as distributed training, real-time collaborative inference, local data processing, etc., which require 'native intelligence design' in future networks. This paper discusses the requirements of native intelligence in the 6 th generation mobile communication system(6 G) networks from the perspectives of 5 G intelligent network challenges and the 'ubiquitous intelligence' vision of 6 G, and analyzes the technical challenges of the AI workflows in its lifecycle and the AI as a service(AIaaS) in cloud network. The progress and deficiencies of the current research on AI functional architecture in various industry organizations are summarized. The end-to-end functional architecture for native AI for 6 G network and its three key technical characteristics are proposed: quality of AI services(QoAIS) based AI service orchestration for its full lifecycle, deep integration of native AI computing and communication, and integration of native AI and digital twin network. The directions of future research are also prospected. | Liu Guangyi Deng Juan Zheng Qingbi Li Gang Sun Xin Huang Yuhong | 2022 | The Journal of China Universities of Posts and Telecommunications2022，29，1： | 0 |
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