Intelligent UAV Based Energy Supply for 6G Wireless Powered IoT Networks

In this paper,we develop a 6G wireless powered Internet of Things(IoT)system assisted by unmanned aerial vehicles(UAVs)to intelligently supply energy and collect data at the same time.In our dual-UAV scheme,UAV-E,with a constant power supply,transmits energy to charge the IoT devices on the ground,whereas UAV-B serves the IoT devices by data collection as a base station.In this framework,the system's energy efficiency is maximized,which we define as a ratio of the sum rate of IoT devices to the energy consumption of two UAVs during a fixed working duration.With the constraints of duration,transmit power,energy,and mobility,a difficult non-convex issue is presented by optimizing the trajectory,time duration allocation,and uplink transmit power of concurrently.To tackle the non-convex fractional optimization issue,we deconstruct it into three subproblems and we solve each of them iteratively using the descent method in conjunction with sequential convex approximation(SCA)approaches and the Dinkelbach algorithm.The simulation findings indicate that the suggested cooperative design has the potential to greatly increase the energy efficiency of the 6G intelligent UAV-assisted wireless powered IoT system when compared to previous benchmark systems.

Intelligent Network-Connected New Energy Vehicle Technology and Application Under the Dual-Carbon Strategy

In responding to the“dual carbon”strategy,intelligent networked new energy vehicle technology plays a crucial role.This type of vehicle combines the advantages of new energy technology and intelligent network technology,effectively reduces carbon emissions in the transportation sector,improves energy utilization efficiency,and contributes to the green transportation system through intelligent transportation management and collaborative work between vehicles,making significant contributions.This article aims to explore the development of intelligent network-connected new energy vehicle technology and applications under the dual-carbon strategy and lay the foundation for the future development direction of the automotive industry.

Generative Adversarial Networks Based Digital Twin Channel Modeling for Intelligent Communication Networks

Integration of digital twin(DT)and wireless channel provides new solution of channel modeling and simulation,and can assist to design,optimize and evaluate intelligent wireless communication system and networks.With DT channel modeling,the generated channel data can be closer to realistic channel measurements without requiring a prior channel model,and amount of channel data can be significantly increased.Artificial intelligence(AI)based modeling approach shows outstanding performance to solve such problems.In this work,a channel modeling method based on generative adversarial networks is proposed for DT channel,which can generate identical statistical distribution with measured channel.Model validation is conducted by comparing DT channel characteristics with measurements,and results show that DT channel leads to fairly good agreement with measured channel.Finally,a link-layer simulation is implemented based on DT channel.It is found that the proposed DT channel model can be well used to conduct link-layer simulation and its performance is comparable to using measurement data.The observations and results can facilitate the development of DT channel modeling and provide new thoughts for DT channel applications,as well as improving the performance and reliability of intelligent communication networking.

Research on Network Cognition Model and Mechanism of Intelligent Information Network

Intellectualization has been an inevitable trend in the information network,allowing the network to achieve the capabilities of self-learning,self-optimization,and self-evolution in the dynamic environment.Due to the strong adaptability to the environment,the cognitive theory methods from psychology gradually become an excellent approach to construct the intelligent information network(IIN),making the traditional definition of the intelligent information network no longer appropriate.Moreover,the thinking capability of existing IINs is always limited.This paper redefines the intelligent information network and illustrates the required properties of the architecture,core theory,and critical technologies by analyzing the existing intelligent information network.Besides,we innovatively propose a novel network cognition model with the network knowledge to implement the intelligent information network.The proposed model can perceive the overall environment data of the network and extract the knowledge from the data.As the model’s core,the knowledge guides the model to generate the optimal decisions adapting to the environmental changes.At last,we present the critical technologies needed to accomplish the proposed network cognition model.

Application of Zero-Watermarking for Medical Image in Intelligent Sensor Network Security

The field of healthcare is considered to be the most promising application of intelligent sensor networks.However,the security and privacy protection ofmedical images collected by intelligent sensor networks is a hot problem that has attracted more and more attention.Fortunately,digital watermarking provides an effective method to solve this problem.In order to improve the robustness of the medical image watermarking scheme,in this paper,we propose a novel zero-watermarking algorithm with the integer wavelet transform(IWT),Schur decomposition and image block energy.Specifically,we first use IWT to extract low-frequency information and divide them into non-overlapping blocks,then we decompose the sub-blocks by Schur decomposition.After that,the feature matrix is constructed according to the relationship between the image block energy and the whole image energy.At the same time,we encrypt watermarking with the logistic chaotic position scrambling.Finally,the zero-watermarking is obtained by XOR operation with the encrypted watermarking.Three indexes of peak signal-to-noise ratio,normalization coefficient(NC)and the bit error rate(BER)are used to evaluate the robustness of the algorithm.According to the experimental results,most of the NC values are around 0.9 under various attacks,while the BER values are very close to 0.These experimental results show that the proposed algorithm is more robust than the existing zero-watermarking methods,which indicates it is more suitable for medical image privacy and security protection.

Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment.In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment,we proposed a more effective and robust target detection framework based on deep learning,which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection.Firstly,the weighted box fusion method is adopted to generate a fusion box by weighted fusion of prediction boxes with high confidence,so as to obtain accurate acoustic shadow boxes.Further,the acoustic shadow box is cut down to get the feature map containing the acoustic shadow information,and then the acoustic shadow feature map and the target information feature map are adaptively fused to make full use of the acoustic shadow feature information.In addition,we introduce a threshold processing module to improve the attention of the model to important feature information.Through the underwater sonar dataset provided by Pengcheng Laboratory,the proposed method improved the average accuracy by 3.14%at the IoU threshold of 0.7,which is better than the current traditional target detection model.

Real-Time Prediction Algorithm for Intelligent Edge Networks with Federated Learning-Based Modeling

Intelligent healthcare networks represent a significant component in digital applications,where the requirements hold within quality-of-service(QoS)reliability and safeguarding privacy.This paper addresses these requirements through the integration of enabler paradigms,including federated learning(FL),cloud/edge computing,softwaredefined/virtualized networking infrastructure,and converged prediction algorithms.The study focuses on achieving reliability and efficiency in real-time prediction models,which depend on the interaction flows and network topology.In response to these challenges,we introduce a modified version of federated logistic regression(FLR)that takes into account convergence latencies and the accuracy of the final FL model within healthcare networks.To establish the FLR framework for mission-critical healthcare applications,we provide a comprehensive workflow in this paper,introducing framework setup,iterative round communications,and model evaluation/deployment.Our optimization process delves into the formulation of loss functions and gradients within the domain of federated optimization,which concludes with the generation of service experience batches for model deployment.To assess the practicality of our approach,we conducted experiments using a hypertension prediction model with data sourced from the 2019 annual dataset(Version 2.0.1)of the Korea Medical Panel Survey.Performance metrics,including end-to-end execution delays,model drop/delivery ratios,and final model accuracies,are captured and compared between the proposed FLR framework and other baseline schemes.Our study offers an FLR framework setup for the enhancement of real-time prediction modeling within intelligent healthcare networks,addressing the critical demands of QoS reliability and privacy preservation.

Research on the Development Trend of Electronic Communication Technology Based on Intelligent Network

With the rapid development of electronic communication technology,various new technical elements are constantly added to it,bringing many changes to people’s lives and work.The traditional data diversion mode can no longer truly meet the needs of actual work,and the electronic communication mode plays a huge role and occupies an important position in the communication market.Regarding how to develop and apply intelligent electronic communication technology more perfectly,there will be an overview of the specific principle of intelligent electronic communication technology,from the multi-faceted impact of electronic communication technology on human society.The article put forward the future development trend of electronic communication technology based on intelligent networks,emphasized expanding the scale of technology coverage,improved the comprehensive quality of technical products,optimized the structure of the communication industry,and formed a perfect industrial chain,so as to improve the intelligent level of electronic communication technology.

Intelligent Vehicle Auxiliary Handling System Based on the Internet of Things Technology

This paper proposes an intelligent vehicle auxiliary handling system based on Internet of Things(IoT)technology,featuring an innovative holding mechanism design that adjusts to the length and width of various vehicles.The system combines precise positioning using satellite tracking technology,intelligent recognition via OpenCV,and the interconnectivity of IoT.This intelligent vehicle auxiliary handling system can independently identify vehicle positions and plan optimal handling paths,eliminating the traditional reliance on manual operation.It offers efficient and accurate handling,setting a new trend in the handling industry.Additionally,the system integrates seamlessly with parking lot management systems,providing real-time updates on vehicle locations and statuses.This allows managers to monitor the parking lot operations clearly and efficiently.This intelligent coordination greatly enhances overall work efficiency and streamlines parking management.Overall,the innovative design of the intelligent vehicle auxiliary handling system represents a significant breakthrough in both function and performance,gaining user favor with its smooth operation.Looking ahead,continued technological advancements and the expansion of application fields will bring even more vitality and intelligence to societal development.

Softswitch Based Solution to Make Network Intelligent

The factors, such as the network optimization or the network amelioration by fixed telecommunication network operators, the convergence of the Personal Handy-phone System (PHS) network and the Public Switched Telephone Network (PSTN), the integration of PSTN and the Third Generation Mobile Communication (3G) Network, the broadband and multimedia based communication networks, causes the requirement for fixed network’s intelligentization. The Softswitch is a feasible approach to meet this kind of requirement. The solution to make the network comprehensively intelligent based on Softswitch is highly advantageous, which enriches communication services and promotes Fixed and Mobile Convergence (FMC).

Poisoning attacks and countermeasures in intelligent networks:Status quo and prospects

Over the past years,the emergence of intelligent networks empowered by machine learning techniques has brought great facilitates to different aspects of human life.However,using machine learning in intelligent networks also presents potential security and privacy threats.A common practice is the so-called poisoning attacks where malicious users inject fake training data with the aim of corrupting the learned model.In this survey,we comprehensively review existing poisoning attacks as well as the countermeasures in intelligent networks for the first time.We emphasize and compare the principles of the formal poisoning attacks employed in different categories of learning algorithms,and analyze the strengths and limitations of corresponding defense methods in a compact form.We also highlight some remaining challenges and future directions in the attack-defense confrontation to promote further research in this emerging yet promising area.

DESIGN ISSUES FOR BIT RATE-ADAPTIVE 3R O/E/O TRANSPONDER IN INTELLIGENT OPTICAL NETWORKS

This paper reported the design and implementation of a bit rate adaptive Optical Electronic Optical(O/E/O)transponder accomplishing almost full data rate transparency up to 2.5 Gb/s with 3R(Reamplifying,Reshaping and Retiming)processing in electronic domain.Based on the chipsets performing clock recovery in several continuous bit rate ranges,a clock and data regenerating circuit self adaptive to the bit rate of input signal was developed.Key design issues were presented,laying stress on the functional building blocks and scheme for the bit rate adaptive retiming circuit.The experimental results show a good scalability performance.

Intelligent Resources Management System Design in Information Centric Networking

Information centric networking(ICN) is a new network architecture that is centred on accessing content. It aims to solve some of the problems associated with IP networks, increasing content distribution capability and improving users' experience. To analyse the requests' patterns and fully utilize the universal cached contents, a novel intelligent resources management system is proposed, which enables effi cient cache resource allocation in real time, based on changing user demand patterns. The system is composed of two parts. The fi rst part is a fi ne-grain traffi c estimation algorithm called Temporal Poisson traffi c prediction(TP2) that aims at analysing the traffi c pattern(or aggregated user requests' demands) for different contents. The second part is a collaborative cache placement algorithm that is based on traffic estimated by TP2. The experimental results show that TP2 has better performance than other comparable traffi c prediction algorithms and the proposed intelligent system can increase the utilization of cache resources and improve the network capacity.

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks:Transforming Telecommunication Business

Open Air Interface(OAI)alliance recently introduced a new disaggregated Open Radio Access Networks(O-RAN)framework for next generation telecommunications and networks.This disaggregated architecture is open,automated,software defined,virtual,and supports the latest advanced technologies like Artificial Intelligence(AI)Machine Learning(AI/ML).This novel intelligent architecture enables programmers to design and customize automated applications according to the business needs and to improve quality of service in fifth generation(5G)and Beyond 5G(B5G).Its disaggregated and multivendor nature gives the opportunity to new startups and small vendors to participate and provide cheap hardware software solutions to keep the market competitive.This paper presents the disaggregated and programmable O-RAN architecture focused on automation,AI/ML services,and applications with Flexible Radio access network Intelligent Controller(FRIC).We schematically demonstrate the reinforcement learning,external applications(xApps),and automation steps to implement this disaggregated O-RAN architecture.The idea of this research paper is to implement an AI/ML enabled automation system for software defined disaggregated O-RAN,which monitors,manages,and performs AI/ML-related services,including the model deployment,optimization,inference,and training.

Intelligence Driven Wireless Networks in B5G and 6G Era:A Survey

As the wireless communication network undergoes continuous expansion,the challenges associated with network management and optimization are becoming increasingly complex.To address these challenges,the emerging artificial intelligence(AI)and machine learning(ML)technologies have been introduced as a powerful solution.They empower wireless networks to operate autonomously,predictively,ondemand,and with smart functionality,offering a promising resolution to intricate optimization problems.This paper aims to delve into the prevalent applications of AI/ML technologies in the optimization of wireless networks.The paper not only provides insights into the current landscape but also outlines our vision for the future and considerations regarding the development of an intelligent 6G network.

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.

Warehouse Environment Parameter Monitoring System and Sensor Error Correction Model Based on PSO-BP

The warehouse environment parameter monitoring system is designed to avoid the networking and high cost of traditional monitoring system.A sensor error correction model which combines particle swarm optimization(PSO)with back propagation(BP)neural network algorithm is established to reduce nonlinear characteristics and improve test accuracy of the system.Simulation and experiments indicate that the PSO-BP neural network algorithm has advantages of fast convergence rate and high diagnostic accuracy.The monitoring system can provide higher measurement precision,lower power consume,stable network data communication and fault diagnoses function.The system has been applied to monitoring environment parameter of warehouse,special vehicles and ships,etc.

A Study of the Next Generation Intelligent Networks Interworking with IP Networks

In the past three years, the author has participated in several projects involved in Intelligent Network (IN). In 1997, we started our research on the project 'The Integration of IN and B ISDN' supported by National Science Foundation. Since 1999, the author has engaged in the project 'the Next Generation IN Based Service Platform Interworking with IP Networks' supported by the National 863 Project. While working on the project, the author made a deep research on the architecture and the key technology of the next generation IN defined by ITU T IN CS3 and CS4. In the following parts. 1. I conclude the research work and the innovation in my dissertation. The early research on the interworking of IN and Internet, despite the shortage of materials, the interworking architecture by means of IAF is analyzed. Some key techniques like triggering intelligent service and reporting dynamic IP address are solved. Some new SIBs and INAPs are added, and the dial up software of users is enhanced, too. The incoming call notification service is designed. What we have done paves the way for the future research. 2. The gateway based architecture for the interworking of IN and Internet is described. Considering the research results from ITU, PINT work group and TIPHON work group, we emphasize that the interworking scenario through MG,SCG and C/BG is promising. Based on the CIN software developed by ourselves, we provide the scenario to enhance the function entities and signaling protocol. We address the function of entities and the interaction of signaling with an example like ICW service. 3. With the introduction of mobile agent technology, the author proposes the distributed IN which can be integrated with IP networks. According to the drawbacks of the centralized IN, we address the architecture and conceptual model of distributed IN to support advanced service in IP Telephony. We try to illustrate the role and relationship between function entities. We also present a smooth evolution scenario from today's networks. 4. A novel service control software based on mobile agent technology is proposed. With the adiquately understanding of CIN 02 SCP, we present the OO based framework of MA SCP. And we explore how our new SCP works. We prove that our solution can work efficiently by a service called VPN in IP Telephony. 5. The concept, architecture and related research of active networks are introduced. We take the ticket order service as an example, give the simulation results and prove that active networks can improve the performance of distributed applications. We also compare active networks with mobile agent based IN. We highlight that the two techniques can complement each other and borrow lessons from the other one. 6. The architecture of Broadband IN is discussed. From the angles of architecture, access mode and software structure, a novel B IP that can support multimedia services such as VoD and B VPN is given. Moreover, B IP is introduced into VoD service. To improve the performance of VoD, we present a novel replacement algorithm with the multi layer decision with multi factors.

Study on the performance of the A*Prune QoS routing algorithm for intelligent optical networks and its improvements

The A＇Prune quality of service （QoS） routing algorithm was proposed to compute K-shortest paths satisfying multiple QoS constraints, The A＇Prune is considered to be one of the practical routing algorithms for intelligent optical networks because of its flexibility in handling many practical constraints, This article gives detailed performance studies of the algorithm through extensive simulation experiments. We found that both the running time and the memory space requirements of the algorithm are large, especially when the network size increases, in this article, we also propose an approach to improving the performance of the A＇Prune algorithm. The improvements should make the A＇Prune algorithm more attractive for practical use in intelligent optical networks.