Full Text:   <3249>

Suppl. Mater.: 

CLC number: 

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2022-04-22

Cited: 0

Clicked: 3572

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.1 P.1-4

http://doi.org/10.1631/FITEE.2210000


Theory and techniques for "intellicise" wireless networks


Author(s):  Ping ZHANG, Mugen PENG, Shuguang CUI, Zhaoyang ZHANG, Guoqiang MAO, Zhi QUAN, Tony Q. S. QUEK, Bo RONG

Affiliation(s):  State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; more

Corresponding email(s):   pzhang@bupt.edu.cn, pmg@bupt.edu.cn, shuguangcui@cuhk.edu.cn, ning_ming@zju.edu.cn, g.mao@ieee.org, zquan@szu.edu.cn, tonyquek@sutd.edu.sg, bo.rong@canada.ca

Key Words: 


Share this article to: More |Next Article >>>

Ping ZHANG, Mugen PENG, Shuguang CUI, Zhaoyang ZHANG, Guoqiang MAO, Zhi QUAN, Tony Q. S. QUEK, Bo RONG. Theory and techniques for "intellicise" wireless networks[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(1): 1-4.

@article{title="Theory and techniques for "intellicise" wireless networks",
author="Ping ZHANG, Mugen PENG, Shuguang CUI, Zhaoyang ZHANG, Guoqiang MAO, Zhi QUAN, Tony Q. S. QUEK, Bo RONG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="1",
pages="1-4",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2210000"
}

%0 Journal Article
%T Theory and techniques for "intellicise" wireless networks
%A Ping ZHANG
%A Mugen PENG
%A Shuguang CUI
%A Zhaoyang ZHANG
%A Guoqiang MAO
%A Zhi QUAN
%A Tony Q. S. QUEK
%A Bo RONG
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 1
%P 1-4
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2210000

TY - JOUR
T1 - Theory and techniques for "intellicise" wireless networks
A1 - Ping ZHANG
A1 - Mugen PENG
A1 - Shuguang CUI
A1 - Zhaoyang ZHANG
A1 - Guoqiang MAO
A1 - Zhi QUAN
A1 - Tony Q. S. QUEK
A1 - Bo RONG
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 1
SP - 1
EP - 4
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2210000


Abstract: 
With the acceleration of a new round of global scientific, technological, and industrial revolution, the next generation of information and communication technology, i.e., 6G, will inject new momentum into industry transformation and upgrad-ing, as well as into economic innovation and development. This will subsequently promote a global industrial integration. Wireless communication will be ubiquitous in all areas of future society, supporting novel applications with various performance requirements, such as immersive- or interactive-experience applications requiring a large bandwidth, autonomous driving and vehicle-to-everything applications requiring ultra-high reliability and ultra-low latency, and applications for industrial Internet requiring massive machine-type connectivity. Facing the challenges of the post-Moore and post-pandemic era, wireless communication needs breakthroughs in network architecture to improve the intelligence, security, robustness, bandwidth, and heterogeneity. With this background, several important tendencies have emerged in the development of 6G wireless communications:
1. Future wireless networks will evolve from “human-to-human” communications into intelligent “human-to-machine” communications. In addition to enabling communications among humans, future wireless networks will be able to support close connections among humans and machines. The behavior and intent of humans will be sensed and communicated to machines that will accordingly adjust their operations. Typical scenarios include smart building, intelligent transportation, mixed reality (MR), and others.
2. Network nodes will evolve from carrying out only traditional communications to carrying out communication, sensing, computation, management, and caching in an integrated manner. To meet the diverse service requirements of mobile MR, intelligent transportation, industrial Internet of Things, and other areas, future networks will possess multiple functionalities. For example, by sensing human head position, pre-caching necessary content, and rendering high-quality images, network nodes can provide fully immersive MR experiences. In addition, with artificial intelligence (AI), network nodes can manage multi-dimensional resources in an on-demand fashion, where intent-driven network management and control can be realized.
3. Network architecture will focus on collaborations between the cloud and the network edge, which will become more heterogenous.
To shorten latency and alleviate the backhaul/fronthaul burden, the network edge must collaborate with the cloud. The first method of collaboration is that the cloud finishes AI model training and then deploys AI models into the network edge, which supports the so-called edge intelligence. In the second method, users demanding high throughput are served via a cloud radio access mode, while users requiring ultra-low latency can benefit from edge computation and caching. As for architecture heterogeneity, future networks are envisioned to incorporate unmanned aerial vehicle (UAV) networks, satellite communica-tion networks, and dense cellular networks, bringing three-dimensional and hierarchical network coverage.
In short, the evolution of existing 5G technolo-gies and the development of 6G need to address more stringent and diverse application scenarios, a more strict energy constraint, and the orchestration of multi-dimensional resources. These challenges call for an intellicise wireless network operation paradigm, where “intellicise” is a new adjective that we coin, standing for intelligence-endogenous and primitive-concise. Built upon the integration of AI and next-generation networking technologies, an intellicise wireless network continually explores and exploits new intelligent primitives, e.g., semantic base (Seb) in semantic communications, proactively takes sys-tematic entropy reduction as the global optimization objective, adaptively reshapes the core models of information systems, and ultimately endows itself with endogenous intelligence and primitive conciseness.
In this context, the journal Frontiers of Information Technology & Electronic Engineering has organized a special feature on the theory and techniques for intellicise wireless networks. This special feature covers information theory, architecture design, and intellicise wireless networks for achieving air-space-ground-sea integration, resource management, hardware testbeds and platforms, as well as related applications. In addition, this feature is intended to provide a review of advancements and future research directions in the research field of intellicise wireless networks. After a rigorous review process, six papers have been selected for this feature, including one review article and five research articles.

智简无线网络理论与技术

张平1,彭木根1,崔曙光2,张朝阳3,毛国强4,全智5,Tony Q.S. QUEK6,荣波7
1北京邮电大学网络与交换技术国家重点实验室,中国北京市,100876
2香港中文大学(深圳)理工学院,中国深圳市,518172
3浙江大学信息科学与工程学院,中国杭州市,310027
4西安电子科技大学智慧交通研究院,中国西安市,710071
5深圳大学电子与信息工程学院,中国深圳市,518060
6新加坡科技设计大学信息系统技术与设计系,新加坡,487372
7加拿大通信研究中心,加拿大渥太华市,K2K 2Y7
摘要:随着全球新一轮科技革命和产业革命加速推进,第六代移动无线通信系统(6G)将为产业转型升级和经济创新发展注入新动能,进一步促进全球产业一体化发展。在6G时代,无线通信将渗入各个领域,支持各种新型应用并满足其差异化的极致性能要求,例如沉浸式或交互式体验应用需要超大带宽的传输速率,自动驾驶和车联网应用需要超高可靠性和超低延迟,工业互联网应用需要海量机器类型连接。面对后摩尔和后疫情时代的挑战,无线通信需要在网络架构上突破,以提高智能性、安全性、鲁棒性、带宽和异构性。在此背景下,6G发展具有以下几个重要趋势:
1. 未来无线通信将从满足“人—人”通信发展为满足智能“人—机—物”通信
除实现传统人与人之间的个人通信外,未来无线网络还将支持个人、机器和物体相互之间的高效无线互联。人类的行为和意图将被智能实时感知,并及时让机器或物体知悉,机器或物体将适时地调整或者进行专门的操作。典型应用场景包括智能建筑、智能交通、混合现实(MR)甚至元宇宙等。
2. 通信节点将从纯粹的通信向通信、感知、计算、控制、管理深度融合扩展。
基于信息领域的多学科交叉融合,无线网络将对现有的通信功能进行扩展,深度融合感知、计算、控制和管理等,以满足移动MR、智能无人机群、智能体自组网、工业物联网等领域中多样化的极致性能服务需求。例如,通过感知人体头部位置、预缓存必要内容和渲染高质量图像,通信节点可以提供完全沉浸式的MR体验。通过无人机自身的态势感知,进行自动的轨迹调整、抗干扰和容量覆盖自优化,实现多无人机自组网;此外,借助人工智能(AI),网络节点可以进行无人化的网络规划优化,实现意图驱动的网络管控。
3. 体系架构将聚焦云、网、算、业务的协同,这将使协同更加异构泛在
为节约能源、缩短延迟并减轻回传/前传链路容量负担,边缘计算将与无线网络节点深度协作;此外,为了实现无线网络智能支撑不同的场景和应用,需要云计算、边缘计算、无线网络、算力和业务深度协同,例如针对低时延高可靠性能需求,在云端完成AI模型训练,然后将AI模型部署到网络边缘,实现边缘智能,从而减少时延,增强不同应用的实时智能支撑;针对大带宽高吞吐量需求,可以通过云化处理,也可以通过云化进行智能的网络管理运维等。在架构的异构性方面,基于云—网—算—业协同,进行多维资源的协同编排,可以实现高中低轨卫星、高空平台、无人机、密集蜂窝网络的多维分层一体化覆盖。
简而言之,现有5G向6G演进,需要适应更加苛刻、更多样化的应用场景,更为严格的能量约束,更加灵活的多维资源协同编排,同时避免网络扩张带来的资源需求急剧增大以及网络架构和协议的过度复杂化。这些挑战寻求一种智简(intellicise)无线网络新范式。其中,“intellicise”是应6G特征和场景应用需求提出的一个新形容词,代表“智慧内生、原生简约”。以人工智能与下一代组网技术的一体化为基础,智简无线网络持续探究和利用新的智能本原(例如,语义通信中的语义基等),主动以系统熵减为全局优化目标,自适应地重塑信息系统的核心模型,最终实现自身的智慧内生、原生简约。
在此背景下,《信息与电子工程前沿(英文)》(FITEE)期刊组织了本期“智简无线网络理论与技术”专题。专题涵盖信息论、架构设计和智简无线网络,涉及空天地海一体化、资源管理、硬件测试平台等相关应用。此外,专题旨在回顾智简无线网络研究领域的进展并展望未来研究方向。经严格评审,选录6篇文章,包括1篇综述和5篇研究论文。

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE