Space/Air Covert Communications:Potentials,Scenarios,and Key Technologies

Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface(RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.

Impact of Artificial Intelligence on Corporate Leadership

Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.

ZTE Communications Call for Papers Special Issue on Using Artificial Intelligence in Internet of Things

Internet of Things has received much attention over the past de- cade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gather- ing and related problems are becoming more complex and uncer- tain. Researchers have therefore turned to AI as an efficient way of dealing with the problems created by big data. This special issue of ZTE Communications will be dedicated to development, trends, challenges, and current practices in artificial intelligence for the Internet of Things. Position papers, technology overviews, and case studies are all welcome. Appropriate topics include but are not limited to：

How Artificial Intelligence and Virtual Reality Benefit the Elderly and Individuals with Disabilities

The growing and evolving use of emerging technology including Artificial Intelligence(AI)and Virtual Reality(VR),has significantly impacted the lives of two specific groups-the elderly and the disabled.This paper investigates potential reasons for this phenomenon.Clearly,AI and VR Technology alters the everyday lives of people with disabilities and how they navigate the world.Technological developments increasingly work to address the isolation that people with disabilities as well as the elderly experience for they are often unable or limited in how they engage with their communities.This research paper outlines the way technology has improved social communication,information distribution,and day-to-day living for those with disabilities and the elderly.Undoubtedly,the internet has transformed social communication and interaction for most people.Socially isolated individuals with disabilities have gained exposure to social environments through social media.Moreover,the broad range of information available on the internet has increased access to resources such as government services,health services,and social services support.On a related point,assistive devices have enabled disabled people including many seniors to overcome motor,sensory,or cognitive difficulties that may have previously hindered them from performing daily tasks.However,although AI and VR technology has been effectively integrated in the lives of those with disabilities,many such individuals lack access to commonplace technologies,like a personal computer.This paper examines how AI and VR technology has enhanced communication,information access,and everyday activities for the disabled and aging communities despite such socio-economic limitations.

An Overview of Wireless Communication Technology Using Deep Learning

with the development of 5G,the future wireless communication network tends to be more and more intelligent.In the face of new service de-mands of communication in the future such as super-heterogeneous network,multiple communication sce-narios,large number of antenna elements and large bandwidth,new theories and technologies of intelli-gent communication have been widely studied,among which Deep Learning(DL)is a powerful technology in artificial intelligence(AI).It can be trained to con-tinuously learn to update the optimal parameters.This paper reviews the latest research progress of DL in in-telligent communication,and emphatically introduces five scenarios including Cognitive Radio(CR),Edge Computing(EC),Channel Measurement(CM),End to end Encoder/Decoder(EED)and Visible Light Com-munication(VLC).The prospect and challenges of further research and development in the future are also discussed.

AI Assisted PHY in Future Wireless Systems: Recent Developments and Challenges

Nowadays,the rapid development of artificial intelligence(AI)provides a fresh perspective in designing future wireless communication systems.Innumerable attempts exploiting AI methods have been carried out,which results in the state-of-the-art performance in many different areas of wireless communications.In this article,we present the most recent and insightful developments that demonstrate the potentials of AI techniques in different physical layer(PHY)components and applications including channel characterization,channel coding,intelligent signal identification,channel estimation,new PHY for random access in massive machine-type communication(mMTC),massive multiple-input multiple-output(MIMO)power control and PHY resource management.Open challenges and potential future directions are identified and discussed along this research line.

基于AI技术的广电融媒体智慧服务模型设计

随着人工智能(Artificial Intelligence,AI)技术在广播电视领域的应用,在媒体融合时代探索AI技术如何赋能广电智慧服务模型设计,进而优化用户体验效果,已经逐步成为研究的热点问题。基于此,在分析相关文献的基础上,分别从用户需求分析、用户群体画像、模型设计理念及智慧价值体现等方面深入分析广电融媒体智慧服务模型的设计方案,旨在利用AI技术促进广电智慧服务由融媒体向智媒体转化。

Early warning of core network capacity in space-terrestrial integrated networks

With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial networks with limi-ted resources,the utilization efficiency of the entire space-terres-trial integrated networks resources can be affected by the core network indirectly.In order to improve the response efficiency of core networks expansion construction,early warning of the core network elements capacity is necessary.Based on the inte-grated architecture of space and terrestrial network,multidimen-sional factors are considered in this paper,including the number of terminals,login users,and the rules of users’migration during holidays.Using artifical intelligence(AI)technologies,the regis-tered users of the access and mobility management function(AMF),authorization users of the unified data management(UDM),protocol data unit(PDU)sessions of session manage-ment function(SMF)are predicted in combination with the num-ber of login users,the number of terminals.Therefore,the core network elements capacity can be predicted in advance.The proposed method is proven to be effective based on the data from real network.

Quantum Artificial Intelligence Based Node Localization Technique for Wireless Networks

Artificial intelligence(AI)techniques have received significant attention among research communities in the field of networking,image processing,natural language processing,robotics,etc.At the same time,a major problem in wireless sensor networks(WSN)is node localization,which aims to identify the exact position of the sensor nodes(SN)using the known position of several anchor nodes.WSN comprises a massive number of SNs and records the position of the nodes,which becomes a tedious process.Besides,the SNs might be subjected to node mobility and the position alters with time.So,a precise node localization(NL)manner is required for determining the location of the SNs.In this view,this paper presents a new quantum bird migration optimizer-based NL(QBMA-NL)technique for WSN.The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes.The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season.In addition,an objective function is derived based on the received signal strength indicator(RSSI)and Euclidean distance from the known to unknown SNs.For demonstrating the improved performance of the QBMA-NL technique,a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.

Special Issue on Using Artificial Intelligence in Internet of Things Guest Editors: Fuji Ren, Yu Gu

Interact of Things has received much attention over the past de cade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gather ing and related problems arc becoming more complex and uncer tain. Researchers have therefore turned to AI as an efficient way of dealing with the problems created by big data.

基于BIM与AI技术的地下三维管网构建与应用探索系统

探索基于建筑信息模型(Building Information Modeling,BIM)与人工智能(Artificial Intelligence,AI)技术的地下三维管网系统在新旧管网融合、AI缺陷识别和数字化交付能力方面的应用。深入分析地下管网管理中的问题和挑战,包括数据不准确、缺陷识别过程复杂和人工处理效率低下等,进而提出构建基于BIM与AI技术的地下三维管网系统,通过应用先进的BIM和三维建模技术,以三维模型展示地下管道的结构、属性、运行状态,旨在实现管网缺陷的快速分析与识别。强调数字化交付能力在地下管网系统中的重要性,通过构建数字模型和数据平台,实现地下管网的全生命周期管理和维护,有助于提高地下三维管网系统的管理效率和安全性。

AI与出版融合视角下图书选题策划与内容生产的优化路径

人工智能技术凭借高速的技术革新,对出版行业的渗透融合不断深入。传统出版行业图书选题策划与内容生产在人工智能技术的碰撞冲击下产生新的火花,创造出备受瞩目的新成绩,开辟了书籍内容生产新模式,引导图书选题策划与内容生产迈向新台阶。但是,对人工智能技术的依赖也让图书选题策划与内容生产面临新的发展挑战。基于AI与出版融合发展的必然性,讨论当前AI应用于图书选题策划与内容生产的优势与不足,并结合发展趋势探讨相关优化路径。

Design-Based Research on the Development and Implementation of AI Courses from the Perspective of University-Enterprise Cooperation

In recent years,China has been issuing artificial intelligence(AI)education policies to promote the deep integration between AI and education.Setting AI courses at the basic education phase can cultivate students’AI literacy and enhance the country’s science and technology competitiveness in the future.However,due to shortages of AI teachers and inadequate conditions for practice,the current AI courses in primary and secondary schools are not enough in effectiveness.In light of current problems,this study,based on the foundation of university-enterprise cooperation,integrates the“competition and education”mechanism into informal AI course design and practice.Using a design-based research paradigm,the study proposes the design framework from four dimensions:goals,themes and content,methods and steps,and evaluation,and then further refines the framework through two rounds of iterations,to provide a reference for the development and practice of AI courses.

Beyond Algorithms: A Comprehensive Analysis of AI-Driven Personalization in Strategic Communications

This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.

Artificial intelligence andwireless communications

The applications of artificial intelligence(AI)and machine learning(ML)technologies in wireless communications have drawn significant attention recently.AI has demonstrated real success in speech understanding,image identification,and natural language processing domains,thus exhibiting its great potential in solving problems that cannot be easily modeled.AI techniques have become an enabler in wireless communications to fulfill the increasing and diverse requirements across a large range of application scenarios.In this paper,we elaborate on several typical wireless scenarios,such as channel modeling,channel decoding and signal detection,and channel coding design,in which AI plays an important role in wireless communications.Then,AI and information theory are discussed from the viewpoint of the information bottleneck.Finally,we discuss some ideas about how AI techniques can be deeply integrated with wireless communication systems.

生成式人工智能的工业应用技术与前景

随着在工业应用中的不断深化,人工智能(AI)逐渐面临场景定制化、数据要求高、动态环境适应性差等问题。以生成式人工智能(AIGC)为代表的通用AI为突破传统AI的瓶颈提供了新思路。为推动AIGC与工业领域的融合创新、抢占下一轮科技革命的技术高地,对AIGC技术及其工业应用展开综述。首先,梳理了国内外AIGC技术的发展现状,总结了当前AIGC工业应用面临的问题和挑战。然后,提出了AIGC在工业领域应用的技术架构,以及通用大模型集成、通用大模型微调与知识库外挂、预训练工业大模型这三种应用模式。最后,从研发设计、生产制造、经营管理以及运维服务等四个方面的十二个场景作应用展望,以激发AIGC工业应用的新技术、新方向的进一步发展,赋能工业领域形成新质生产力。

人工智能的经济效应:现状、热点及展望——基于CiteSpace的文献综述

在有关人工智能对就业、产业融合、经济增长等方面的研究与日俱增背景下,从人工智能对就业、经济增长、产业融合应用等多方面进行相关文献的综述。基于Web…of…Science和中国知网数据库2003—2022年的1…908篇中外文文献,从发文量、文献刊载期刊、研究机构、合作网络、核心作者等角度,利用CiteSpace软件对人工智能与经济发展相关研究进行文献计量和知识图谱分析,识别出该领域的研究热点和演进特征。在研究进程上,人工智能与经济发展相关研究于2017年后数量大幅增长,呈现跨学科多领域交叉特征,且国外跨学科合作相较于国内而言更加密切,国内相关研究合作网络尚处于初始构建阶段,成效尚不明显。在研究内容上,现有相关研究主要聚焦于探究人工智能对就业、产业融合及经济增长影响等三大领域,且尚未形成一致结论。在研究方法上,相关研究呈现出“定性—建模—实证”的发展脉络,实证研究渐成主流,但对于人工智能指标的选取及度量仍存在较大的局限性。未来可进一步围绕人工智能指标选取及测度、人工智能带来的创新模式改变及人工智能政策分析等开展研究。

四链融合下运营商推进新一代人工智能服务能力建设研究

生成式AI技术正在从文本扩展到视频等多模态,对传统软件以及数智应用行业商业模式都产生了重大影响。文章分析面向通用人工智能的新一代人工智能服务的商业范式,对其商业本质和价值度量方式进行探索。其次,结合一年来生成式AI公司的商业实践,列举目前主要的商业落地思路。围绕创新链产业链资金链人才链的四链融合,分析国外产业投资趋势以及相关头部投资机构为推动新的商业范式落地开展的四链融合实践。最后,聚焦运营商发展新一代人工智能服务的挑战和优势,讨论和梳理运营商充分利用四链融合从模型、应用、数据闭环服务、基础设施、AI安全等方面推进智能服务能力建设相关举措和建议。

外军有/无人编组技术分析

有人/无人平台编队可以充分利用无人平台的低成本、可消耗优势,扩展有人平台的作战空间,提高有人平台态势感知、穿透杀伤和生存能力。针对美、英、法、澳、韩等国有/无人编组技术的发展动态进行了调研综述,举例说明了外军有/无人编组在海、陆、空等作战域中的典型应用,并分析了有/无人编组在传输组网、远程测控、自主决策和人机交互等方面的技术挑战和关键技术途径。最后对有/无人编组技术的发展趋势进行了展望,可为未来联合作战体系中的协同作战样式和相关领域的技术研究提供参考借鉴。

可解释人工智能在气象预报中的应用和展望

本研究探讨了可解释的人工智能在现代气象预报服务业务中的应用和展望。目前,AI技术在强对流监测、临近预报等方面提高了准确性,但仍存在训练数据集不完备、不平衡和模型解释性不足等问题。未来,可解释的人工智能将成为重要发展方向,提高预测模型可靠性和可信度,其与数值预报融合将成为另一趋势,提供更准确、可靠的天气预报。研究应关注解释性AI模型开发应用以及AI技术与传统数值预报融合方法,以推进可解释的人工智能在气象预报服务业务中的应用和发展。