Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

Double-Edge Intelligent Integrated Satellite Terrestrial Networks

The efficient integration of satellite and terrestrial networks has become an important component for 6 G wireless architectures to provide highly reliable and secure connectivity over a wide geographical area.As the satellite and cellular networks are developed separately these years,the integrated network should synergize the communication,storage,computation capabilities of both sides towards an intelligent system more than mere consideration of coexistence.This has motivated us to develop double-edge intelligent integrated satellite and terrestrial networks(DILIGENT).Leveraging the boost development of multi-access edge computing(MEC)technology and artificial intelligence(AI),the framework is entitled with the systematic learning and adaptive network management of satellite and cellular networks.In this article,we provide a brief review of the state-of-art contributions from the perspective of academic research and standardization.Then we present the overall design of the proposed DILIGENT architecture,where the advantages are discussed and summarized.Strategies of task offloading,content caching and distribution are presented.Numerical results show that the proposed network architecture outperforms the existing integrated networks.

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.

APPLICATION OF INTEGRATED INTELLIGENT METHODOLOGY TO PREDICT STABILITY AND SUPPORTING DECISION IN UNDERGROUND DRIFT

The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non linearity hazardous simulation experiment, response analysis and computing theory have been regarded as a high level question in the architecture, bridge, tunnel, hydraulic, etc engineering fields.Approaches an integrated intelligent methodology to predict stability and supporting decision in underground drift based on neural network modelling on coal rock mechanical problem is proposed.By the terms of the non linearity numerical simulation, this paper develops integrated intelligent methodology to research on the structure hazardous response strata soft rock drifts.

Service Customized Space-Air-Ground Integrated Network for Immersive Media: Architecture, Key Technologies, and Prospects

The space-air-ground integrated network(SAGIN) is regarded as the key approach to realize global coverage in future network and it reaches broad access for various services. Being the new paradigm of service, immersive media(IM) has attracted users’ attention for its virtualization, but it poses challenges to network performance, e.g. bandwidth, rate, latency. However, the SAGIN has limitations in supporting IM services, such as 4 K/8 K video, virtual reality, and interactive games. In this paper, a novel service customized SAGIN architecture for IM applications(SAG-IM) is proposed, which achieves content interactive and real-time communication among terminal users. State-of-the-art research is investigated in detail to facilitate the combination of SAGIN and service customized technology, which provides endto-end differentiated services for users. Besides, the functional components of SAG-IM contain the infrastructure layer, perception layer, intelligence layer, and application layer, reaching the capabilities of intelligent management of the network. Moreover, to provide IM content with ultra-high-definition and high frame rate for the optimal user experience, the promising key technologies on intelligent routing and delivery are discussed. The performance evaluation shows the superiority of SAG-IM in supporting IM service.Finally, the prospects in practical application are high-lighted.

Key Technologies and Development Trends in Advanced Intelligent Sawing Equipments

As a starting point in equipment manufacturing,sawing plays an important role in industrial production.Intelligent manufacturing equipment is an important carrier of intelligent manufacturing technologies.Due to the backwardness of intelligent technology,the comprehensive performance of sawing equipments in China is obviously different from that in foreign countries.State of the art of advanced sawing equipments is investigated along with the technical bottleneck of sawing machine tool manufacturing,and a new industrial scheme of replacing turning-milling by sawing is described.The key technologies of processing-measuring integrated control,multi-body dynamic optimization,the collaborative sawing network framework,the distributed cloud sawing platform,and the self-adapting service method are analyzed;with consideration of the problems of poor processing control stableness,low single machine intelligence level,no on-line processing data service and active flutter suppression of sawing with wide-width and heavy-load working conditions.Suggested directions for further research,industry implementation,and industry-research collaboration are provided.

Pervasive intelligent endogenous 6G wireless systems:Prospects,theories and key technologies

The worldwide large-scale commercial deployment of 5G has commenced in 2020 for supporting enhanced Mobile BroadBand(eMBB),ultra-Reliable and Low-Latency Communications(uRLLC),and massive Machine-Type Communications(mMTC)services.Nevertheless,the upsurge of Artificial Intelligence(AI)-powered applications,the developmental law of one-decade-one-generation of wireless communications and the inherent limitations of 5G have also been spurring the industry and academia to dedicate their efforts to the research of future 6G wireless systems.6G will be a disruptive,pervasive,intelligent,and endogenous wireless system,which will revolutionize all walks of life and accelerate the transformation and innovation of the global society.In this paper,we present a forward-looking,comprehensive and in-depth analysis and technical identification of 6G.Specifically,we firstly introduce the fundamental theories of 6G in terms of potential requirements.Then,we focus our attention on the discussion of promising key technologies in terms of spectrum,air interface,delay,access,energy consumption,coverage,AI,electromagnetism,interaction,etc.

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.

High resolution 3D nonlinear integrated inversion

The high resolution 3D nonlinear integrated inversion method is based on nonlinear theory. Under layer control, the log data from several wells （or all wells） in the study area and seismic trace data adjacent to the wells are input to a network with multiple inputs and outputs and are integratedly trained to obtain an adaptive weight function of the entire study area. Integrated nonlinear mapping relationships are built and updated by the lateral and vertical geologic variations of the reservoirs. Therefore, the inversion process and its inversion results can be constrained and controlled and a stable seismic inversion section with high resolution with velocity inversion, impedance inversion, and density inversion sections, can be gained. Good geologic effects have been obtained in model computation tests and real data processing, which verified that this method has high precision, good practicality, and can be used for quantitative reservoir analysis.

Resource Allocation for Space-Air-Ground Integrated Networks:A Comprehensive Review

The space-air-ground integrated networks (SAGIN) has emerged as a critical paradigm to address the growing demands for global connectivity and enhanced communication services. This paper gives a thorough review of the strategies and methodologies for resource allocation within SAGIN, focusing on the challenges and solutions within its complex structure. With the advent of technologies such as 6G, the dynamics of resource optimization have become increasingly complex, necessitating innovative approaches for efficient management. We examine the application of mathematical optimization, game theory, artificial intelligence (AI), and dynamic optimization techniques in SAGIN,offering insights into their effectiveness in ensuring optimal resource distribution, minimizing delays, and maximizing network throughput and stability. The survey highlights the significant advances in AI-based methods,particularly deep learning and reinforcement learning, in tackling the inherent challenges of SAGIN resource allocation. Through a critical review of existing literature, this paper categorizes various resource allocation strategies, identifies current research gaps, and discusses potential future directions. Our findings highlight the crucial role of integrated and intelligent resource allocation mechanisms in realizing the full potential of SAGIN for next-generation communication networks.

An overview of multi-antenna technologies for space-ground integrated networks

Multi-antenna technologies have already achieved a series of great successes in the development of information networks. For future space-ground integrated networks(SGINs), the traditional various kinds of separated information networks will converge to a whole fully connected information network to provide more flexible and reliable services on a world scale. Regarding their great successes in existing systems, multiantenna technologies will be of critical importance for the realization of SGINs and multi-antenna technologies are definitely one of the most important enabling technologies for future converged SGINs. In this article, a comprehensive overview on multi-antenna technologies is given. We first investigate multi-antenna technologies from a theoretical viewpoint. It is shown that we can understand multi-antenna technologies in a general and unified point of view. This fact has two-fold meanings. First, the research on multi-antennas can help us understand the relationships between different technologies e.g., OFDMA, CDMA, etc. On the other hand,multi-antenna technologies are easy to integrate into various information systems. Following that, we discuss in depth the potentials and challenges of the multi-antenna technologies on different platforms and in different applications case by case. More specifically, we investigate spaceborne multi-antenna technologies, airborne multi-antenna technologies, shipborne multi-antenna technologies, etc. Moreover, the combinations of multiantenna technologies with other advanced wireless technologies e.g., physical layer network coding, cooperative communication, etc., are also elaborated.

基于成果转化的人工智能算法创新型实验设计

为了拓展深度学习、神经网络算法模型在不同学科领域中的应用,基于创新性教学、高阶性教学以及挑战性教学,提出以科研项目为依托,将科研成果反哺于实验教学,结合实验内容,构建出人工智能算法在能谱测量中的一系列应用实验。实验将脉冲处理、能谱测量、深度学习等多学科知识交叉融合到创新型实验中,利用不同的深度学习模型进行数据处理和分析,充分发挥人工智能算法在实验中的优势,提供了准确、快速和高效的实验结果。实验实施与评估结果表明,该实验不仅能够促进实验教学的创新和发展,也为学生进行科学研究、学科竞赛提供了更多实践与探索的机会。

盾构掘进姿态控制技术研究现状与未来展望

为系统地分析我国盾构掘进姿态控制技术的研究进展,基于知网检索到的32篇相关文献,总结盾构掘进姿态的主要表征参数和影响因素,并以盾构液压推进系统为例论述其控制原理。同时,结合盾构姿态智能控制的部分案例,总结PID控制、自适应控制、模糊控制、基于神经网络的控制和基于智能算法的控制等技术的优劣势及应用场景。基于以上分析,对盾构姿态控制技术的发展方向进行展望。研究发现:1)盾构掘进姿态的影响因素主要包括几何参数、地层参数和盾构掘进参数。2)由于盾构推进系统需要同时完成盾构向前推进和姿态调整等复杂任务,因此该系统的参数对盾构姿态有着很大的影响,是姿态控制的关键因素之一。3)相较于传统PID控制方法,智能控制方法与PID控制的结合可以提高系统的响应速度、精度、适应能力和鲁棒性。4)未来研究可以围绕基于多源数据融合的控制算法、构建数据-机制混合驱动的控制技术以及加强控制技术在实际工程中的实用性等方面展开,实现更精准、更高效的盾构掘进姿态控制。

智能天地一体化网络的卫星跟踪测控技术综述

随着卫星互联网和我国航天测控技术的不断进步,航天测控网络朝着智能化、一体化的方向发展,在自主测控、资源分配等方面进展良好。因此,建立智能天地一体化的航天测控网是我国航天未来发展的重要目标。针对智能航天测控网中的跟踪测轨、遥测和遥控三个方面,分别介绍了相关原理与技术。同时,结合CCSDS提出的空间数据链路标准协议详细介绍了TM、TC、AOS、Proximity-1以及USLP标准,分析了不同标准所使用的技术与实际应用。本文从数据链路层和物理层的角度介绍了智能航天测控系统的工作原理及技术要求,为我国智能天地一体化卫星测控通信网的研究提供参考并予以展望。

面向6G的超可靠低延迟通信关键技术:研究进展与展望

URLLC作为5G和6G蜂窝网络的主要通信服务之一,对于支持各种新兴的关键任务应用至关重要。首先,介绍了6G的背景和URLLC的重要性,随后回顾了URLLC的基础知识、6G URLLC的应用需求及其面临的主要挑战。接着,重点讨论了6G URLLC的几项关键技术及其研究机遇,包括实现全覆盖的空天地一体化网络、高频段通信、智能计算、可重构智能表面,以及人工智能驱动的网络优化。最后,展望了未来通信感知计算一体化、元宇宙与数字孪生支持的无线网络演化及分布式框架的演进。这些技术的发展将显著提升6GURLLC的性能和可靠性,为未来新兴应用提供坚实的基础。

面向6G AI内生的星地融合组网研究

通过卫星通信、人工智能、地面网络三者的有机融合,面向6G智慧内生的星地融合网络能够达到更广的网络覆盖、更智能的网络连接和更高质量的通信服务。作为提升6G组网能力的重要手段之一,面向智慧内生的星载核心网不仅能够提高数据处理效率以满足多元用户需求,还能够有效减少星地间交互产生的信令开销。首先,在总结面向5G星地融合网络特点的基础上,分析一种5G广泛使用的外挂式网元赋能方案;接着,针对6G网络智简化、架构轻量化的组网需求,对比三种星载核心网架构,描述以任务为中心的星载核心网;最后,总结面向6G智慧内生星地融合网络的组网技术、存在的挑战以及未来发展方向。

无人机辅助智能边缘网络技术综述

简要介绍了无人机作为空基信息平台的主要应用场景,结合6G多接入网络和用户为中心网络架构,讨论了无人机在构建智能边缘网络中的重要作用。结合无人机平台在不同场景下的通、感、算能力特点,介绍无人机自组网、无人机通感一体化、无人机边缘计算等无人机辅助智能边缘网络关键技术。最后,围绕无人机在构建智能边缘网络过程中与无线接入网新技术结合时产生的新问题,探讨无人机通信信道建模、三维立体部署与路径规划、携能有限与续航问题、无人机网络安全、无人机集群异构网络融合等关键技术挑战和未来研究方向。

基于移动边缘计算的空天地一体化网络架构

下一代无线通信技术将通过支持智能交通、智能医疗、虚拟现实/增强等服务来提高用户的体验质量。这些新兴的服务通常都是计算密集型和时延敏感型的,必须满足严格的时延、能耗和可靠性要求,而基于云计算的服务难以满足这些要求。为了解决以上问题,提出移动边缘计算(Mobile Edge Computing,MEC)技术,解决将卸载请求回传到云计算中心所具有的高时延和高带宽消耗的问题。空天地一体化网络(Space-Air-Ground Integrated Network,SAGIN)作为6G的重要研究方向,可以弥补全球范围内的巨大覆盖缺口,受到广泛关注。通过将MEC技术、联邦学习技术和人工智能技术引入SAGIN,高效管理网络中海量、异构的资源,构建低时延、低能耗、高可靠性的SAGIN,以支持新兴的各种服务。

基于神经网络的基层智慧型融媒体系统传播能力预测方法

随着基层智慧型融媒体系统在各地的应用越来越广泛,为实现系统长期传播能力的预测,设计基于神经网络的基层智慧型融媒体系统传播能力预测方法。基于改进数据集结构设计高效用数据挖掘算法,实施基层智慧型融媒体系统结构、时间、文本、用户信息的挖掘。对于挖掘信息,设计异常事件检测模型对其实施数据异常事件检测,使用差分综合移动平均自回归模型实施单点噪声的修复。构建一种基于上下文依赖的动态图注意网络作为基层智慧型融媒体系统传播能力预测模型,由建模传播动态图模块、时—空依赖学习模块与预测模块构成,其输入为处理后的信息,输出信息为基层智慧型融媒体系统传播规模预测增量。实验结果表明,该方法预测用户列表精度整体较高,最高达到98.95%,预测用户列表召回率整体较高,最高达到97.24%。

IP承载网络技术演进方向研究

互联网业务的快速发展对IP承载网络提出了确定性、高可靠性、大带宽、弹性连接等新要求,而运营商业务本身的发展对IP承载网络提出了降本增效、差异化承载、安全可信的需求。基于业务演进对网络的需求、IP新技术的发展,对IP承载网络演进方向开展讨论,旨在打造高质量、差异化承载底座,满足多样化业务需求,提升网络价值,降低网络运营成本,筑牢网络安全底座,保障网络安全。