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.

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.

Satellite Communications with 5G, B5G, and 6G: Challenges and Prospects

Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.

Adversarial attacks and defenses for digital communication signals identification

As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.

Leveraging Predictive Analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.

Communication-Efficient Edge AI Inference over Wireless Networks

Given the fast growth of intelligent devices, it is expected that a large number of high-stakes artificial intelligence (AI) applications, e. g., drones, autonomous cars, and tac?tile robots, will be deployed at the edge of wireless networks in the near future. Therefore, the intelligent communication networks will be designed to leverage advanced wireless tech?niques and edge computing technologies to support AI-enabled applications at various end devices with limited communication, computation, hardware and energy resources. In this article, we present the principles of efficient deployment of model inference at network edge to provide low-latency and energy-efficient AI services. This includes the wireless distribut?ed computing framework for low-latency device distributed model inference as well as the wireless cooperative transmission strategy for energy-efficient edge cooperative model infer?ence. The communication efficiency of edge inference systems is further improved by build?ing up a smart radio propagation environment via intelligent reflecting surface.

ZTE Communications Special Issue on Data Intelligence

The new ear of AI is brought about by three converging forces:the advance of AI algorithms,the availability of big data,and the increasing popularity of high performance computing platforms.Data-driven intelligence,or data intelligence,is a new form of AI technologies that leverages the

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：

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.

慢性病计算机辅助诊断系统的构建研究

目的通过对慢性病诊疗规范的研究,结合临床医师诊疗经验,实施计算机与临床知识的人机交互,构建较为精确的慢性病诊断计算机辅助系统。方法通过数学建模与计算机逻辑思维相结合的方法,实现智能辅助诊疗系统(计算机辅助诊断系统)的设计。结果研究方法表明,基于慢性病的计算机辅助诊断系统(CCDCADS)能够对慢性病的诊断提出具有循证医学的辅助决策信息。结论通过建立CCDCADS,能够较好地实现慢性病诊疗模式由经验式诊疗向循证化和信息化的转变,具有良好的应用前景。

民用目标监视系统在机载C2平台上的应用研究

在机载C2平台上接入民用目标监视系统后,可有效的丰富探测手段,支持任务区域内目标的完备掌握,支持机载C2平台各类任务的完成。对空中目标监视系统(ADS-B)、海面目标监视系统(AIS)在机载C2平台上的应用进行了研究,包括目标监视系统定位分析,在机载C2平台上的集成方式、信息处理与应用方式、需要考虑的重点问题等,为民用目标监视系统在机载C2平台上的应用提供参考。进一步对新形势与新技术发展下的民用目标监视系统及其在机载C2平台上的应用进行了展望和分析,对系统的接入方式、接入后的信息对抗与反对抗等进行了探讨。

Green Concerns in Federated Learning over 6G

As Information,Communications,and Data Technology(ICDT)are deeply integrated,the research of 6G gradually rises.Meanwhile,federated learning(FL)as a distributed artificial intelligence(AI)framework is generally believed to be the most promising solution to achieve“Native AI”in 6G.While the adoption of energy as a metric in AI and wireless networks is emerging,most studies still focused on obtaining high levels of accuracy,with little consideration on new features of future networks and their possible impact on energy consumption.To address this issue,this article focuses on green concerns in FL over 6G.We first analyze and summarize major energy consumption challenges caused by technical characteristics of FL and the dynamical heterogeneity of 6G networks,and model the energy consumption in FL over 6G from aspects of computation and communication.We classify and summarize the basic ways to reduce energy,and present several feasible green designs for FL-based 6G network architecture from three perspectives.According to the simulation results,we provide a useful guideline to researchers that different schemes should be used to achieve the minimum energy consumption at a reasonable cost of learning accuracy for different network scenarios and service requirements in FL-based 6G network.

基于末子级应用的可重构通信载荷研究设想

随着对空间碎片、空间飞行器安全的关注及大范围海空实时监控态势感知需求的增强,有效利用在轨运载末子级及构建天基AIS/ADS-B通信系统已成为发展趋势。在此背景下,首次提出将二者结合优势互补的设想,分析了基于末子级留轨应用的AIS/ADS-B可重构通信载荷的民用及军用研究价值,比较了国内外研究现状,设计了总体方案,并对后续工作开展面临的技术难题等进行了阐述。该设想对该领域研究的深入开展具有借鉴意义。

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.

Next Decade of Telecommunications Artificial Intelligence

It has been an exciting journey since the mobile communications and artificial intelligence(AI)were conceived in 1983 and 1956.While both fields evolved independently and profoundly changed communications and computing industries,the rapid convergence of 5th generation mobile communication technology(5G)and AI is beginning to significantly transform the core communication infrastructure,network management,and vertical applications.The paper first outlined the individual roadmaps of mobile communications and AI in the early stage,with a concentration to review the era from 3rd generation mobile communication technology(3G)to 5G when AI and mobile communications started to converge.With regard to telecommunications AI,the progress of AI in the ecosystem of mobile communications was further introduced in detail,including network infrastructure,network operation and management,business operation and management,intelligent applications towards business supporting system(BSS)&operation supporting system(OSS)convergence,verticals and private networks,etc.Then the classifications of AI in telecommunication ecosystems were summarized along with its evolution paths specified by various international telecommunications standardization organizations.Towards the next decade,the prospective roadmap of telecommunications AI was forecasted.In line with 3rd generation partnership project(3GPP)and International Telecommunication Union Radiocommunication Sector(ITU-R)timeline of 5G&6th generation mobile communication technology(6G),the network intelligence following 3GPP and open radio access network(O-RAN)routes,experience and intent-based network management and operation,network AI signaling system,intelligent middle-office based BSS,intelligent customer experience management and policy control driven by BSS&OSS convergence,evolution from service level agreement(SLA)to experience level agreement(ELA),and intelligent private network for verticals were further explored.The paper is concluded with the vision that AI will reshape the future beyond 5G(B5G)/6G landscape,and we need pivot our research and development(R&D),standardizations,and ecosystem to fully take the unprecedented opportunities.

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.

True-data testbed for 5G/B5G intelligent network

Future beyond fifth-generation(B5G)and sixth-generation(6G)mobile communications will shift from facilitating interpersonal communications to supporting internet of everything(IoE),where intelligent communications with full integration of big data and artificial intelligence(AI)will play an important role in improving network efficiency and providing high-quality service.As a rapid evolving paradigm,the AI-empowered mobile communications demand large amounts of data acquired from real network environment for systematic test and verification.Hence,we build the world’s first true-data testbed for 5G/B5G intelligent network(TTIN),which comprises 5G/B5G on-site experimental networks,data acquisition&data warehouse,and AI engine&network optimization.In the TTIN,true network data acquisition,storage,standardization,and analysis are available,which enable system-level online verification of B5G/6G-orientated key technologies and support data-driven network optimization through the closed-loop control mechanism.This paper elaborates on the system architecture and module design of TTIN.Detailed technical specifications and some of the established use cases are also showcased.