最新刊期
卷 39 ， 期 8 ， 2023
- 摘要：Unmanned aerial vehicle (UAV) communication network is an important part of the future integrated space-aerial-ground network, and an effective support to achieve the global three-dimensional coverage of the communication network.The open characteristics of wireless channels make UAV communication vulnerable to malicious attacks by illegal users.Covert communication provides a promising solution for improving the security defense and privacy protection capabilities of UAV communication.However, the overlapping characteristics of the mobility of UAV systems and the requirements of covert communication scenarios bring severe challenges to the collaborative optimization of network resources.The UAV covert communication network was investigated from requirements, challenges, framework and main technologies perspectives.The architecture and model, performance characteristic, as well as potential candidate technologies were analyzed and discussed, in an attempt to outline the overall framework of UAV covert communication, and provide guidance for the subsequent research on UAV covert communication.关键词：UAV communication;covert communication;resource allocation;game theory1062|2838|0更新时间：2024-06-05
Review
- 摘要：Beam hopping (BH) technology is one of effective ways to solve limitation of beam resources and enhance the system coverage ability of low earth orbit (LEO) satellite systems.Existing research typically considers beam hopping resource allocation for a single LEO satellite, however, the actual LEO system is covered by multiple satellites in multiple orbits, and existing research ignores beam interference between satellites, which can easily lead to a decrease in system throughput and service quality.To address these issues, this paper designs an interference aware cooperative resource allocation for LEO with beam hopping (IARA-BH), aiming to maximize the beam service satisfaction (BSS).A BH resource allocation scheme by multi satellite interference coordination based on simulated annealing algorithm (MSIC-SAA) is proposed to solve the optimization problem.Simulation experiments show that compared to beam hopping resource allocation schemes that only consider a single satellite, the BSS of the MSIC-SAA algorithm has been improved by 47.24%, the average signal to interference noise ratio (SINR) has been improved by 27.40%, and the system throughput has been improved by 22.92%.关键词：LEO;beam hopping;multi-satellite cooperation;interference perception780|1073|0更新时间：2024-06-05
- 摘要：Many network applications, such as industrial control and automatic driving, have high requirements for network reliability.Time-sensitive networking (TSN) is a new generation of network technology based on the evolution of standard Ethernet architecture, including the frame replication and elimination for reliability (FRER).Firstly, the redundancy mechanism in TSN standard was described, including the development process, relevant standards and research status.Secondly, the spatial redundancy and time redundancy mechanisms in TSN were classified and analyzed.Finally, the future development and application scenarios of the redundancy mechanism in TSN were prospected, and some inspiring research directions and ideas were put forward.关键词：TSN;FRER;PTRF;reliability;industrial Internet418|1151|0更新时间：2024-06-05
- 摘要：Multi-access edge computing (MEC) is deployed at the edge of the network, enabling efficient and fast data processing in mobile networks, while also undertaking important security functions, making MEC a prime target for attackers.Therefore, MEC nodes will face huge security risks.How to accurately evaluate and quantify MEC security capabilities is an urgent issue to be solved.For accurately evaluating and quantifying MEC security capabilities, the MEC safety assessment system was proposed in combination with MEC safety risks.The assessment indicators selected in the assessment system comprehensively reflect the basic characteristics of MEC and its complete safety capability.Based on this evaluation system, the MEC security evaluation method was designed by using the analytic hierarchy process (AHP) and fuzzy evaluation, the MEC vulnerability scoring system was creatively proposed, and the evaluation indicators were provided based on the results of MEC vulnerability scoring system, the MEC security capability quantification value was finally calculated.The experimental result proves the effectiveness of the method.关键词：5G MEC;security assessment system;vulnerability scoring system;AHP;fuzzy evaluation184|324|0更新时间：2024-06-05
- 摘要：Previous work on social media text-based geolocation focused on mapping language semantic space to geospatial space, which ignores the semantic correlation between social media texts and the distance correlation between geographical locations.To take advantage of these correlations, mCLF, a new unsupervised multiple-level contrastive learning framework was proposed, three contrastive learning modules were designed: a semantic learning module, a location learning module, and a cross-learning module.Transformer encoder was used to obtain semantic representation of posts, utilizing unsupervised contrastive learning method to decrease the distance of semantic representations and location representations of posts with near locations, and then fine-tuned the model with supervised method for geographic location regression or classification outputs.Compared with five baseline methods, extensive experiments based on four datasets demonstrate the effectiveness of the proposed framework.关键词：social media;geolocation;contrastive learning;information mining;Transformer210|671|0更新时间：2024-06-05
- 摘要：Unmanned aerial vehicles (UAV) are an important component of future air-space-ground integrated network due to their onboard storage, communication, and computing capabilities.However, existing research on UAV-assisted edge networks often focuses more on the network perspective and lacks consideration of user perspectives and their requirements.Therefore, a UAV service enhancement mechanism based on deep deterministic policy gradient (DDPG) for scalable video coding (SVC) transmission was proposed from the user’s perspective.Firstly, an elastic video transmission method based on SVC was proposed in conjunction with UAV to improve differentiated user experiences.Secondly, a UAV trajectory planning design based on the DDPG algorithm was proposed to maximize the number of users receiving enhanced layer videos and ensure effective coverage enhancement by UAV in hotspot areas.Simulation results show that compared with both the deep Q network (DQN) algorithm and shortest path (SP) algorithm under different user distributions, the proposed algorithm can increase the average number of enhanced layers received by 47.9% and 76.4%, respectively.This study successfully achieves improved coverage in hotspot areas while also providing differentiated user experiences through its proposed methods.关键词：DDPG;UAV;SVC;trajectory planning145|550|0更新时间：2024-06-05
- 摘要：In order to improve the effectiveness of mobile network scheduling operation information, a method of mobile network scheduling operation information sharing based on chaos reverse learning improved gray wolf algorithm was proposed.On the basis of studying the information sharing structure between the information intranet/provincial dispatching demilitarized zone (DMZ) and the network/provincial dispatching III area, the information sharing was realized through a three-layer scheduling network model including the sharing task layer, the information layer and the user layer, and the information scheduling optimization objective function to maximize the information utility was determined, and the information scheduling results were obtained by solving the objective function through the grey wolf algorithm.In order to obtain better solution results of the objective function, chaos reverse learning and information sharing search strategy were introduced to optimize the initial population and communication ability of the grey wolf algorithm, so as to obtain better solution results and realize the optimal information sharing.The test results show that the method has good application performance.The information utility values are all above 20, the deviation rate is lower than 0.12, and the goodness of fit is higher than 0.92.It can complete information sharing under different transmission modes and present the details of shared information.关键词：chaos reverse learning;improved grey wolf algorithm;mobile network;dispatch operation;information sharing;sharing search policy122|221|0更新时间：2024-06-05
- 摘要：The recommendation system is one of the important methods to realize the intelligent recommendation of massive Internet benefit products.In order to improve the accuracy of personalized benefits recommendation, a deep learning recommendation system based on graph computing method was proposed.Considering the heterogeneity of multi-source data, a graph representation technology based on deep learning was carried out to construct the multiple relationship graph between users and benefit products.The multiple relationship graph extracted the information of graph structure, and model the heterogeneous graphs for the multi-dimensional features of users and the multiple interaction modes between rights and interests products, which effectively aggregated various interactive information and the multiple feature.A heterogeneous graph convolutional neural network was built to learn the high-dimensional feature vectors for various nodes, and excavate users＇ latent preferences to provide a recommendation link with strong interpretability, which greatly improved the recommendation success rate and generating economic value.关键词：heterogeneous graph;graph convolutional neural network;benefit recommendation;multi-source data490|1215|0更新时间：2024-06-05
- 摘要：The adaptive unscented Kalman filter noise reduction algorithm for electronic archives information data was studied to address the issue of data loss during the noise reduction process, as well as the noise covariance and initial value deviation of the data after gross errors.The architecture of electronic archives informatization consisted of the data, business, and user layers.In the data layer, the electronic archives informatization data underwent pretreatment, decision-making, monitoring, and analysis based on user data requests from the user layer.Assumptions were made on the electronic archives informatization data using the Laida criterion to determine the standard deviation probability and establish intervals.Gross errors were eliminated and the noise covariance of the data after gross error removal was estimated using the Sage-Husa filter.This helped to suppress the deviation of the initial value and preserve the original data as much as possible.The traceless Kalman algorithm was utilized to estimate the unknown noise characteristics of electronic archives informatization data in real-time, enabling the noise reduction of electronic archives informatization data.The virtual induction service connected the data, users, and business layer, facilitating the presentation of the required electronic archives information to users in the business layer.Experimental results demonstrate that the algorithm effectively removes various noises from electronic archives information data while retaining the valid data.关键词：electronic archives;unscented Kalman;archives informatization;filtering and noise reduction;Sage-Husa filter;Laida criterion186|521|0更新时间：2024-06-05
- 摘要：A smart museum is a new form of a museum, which uses devices or technologies including the Internet of things (IoT) and artificial intelligence (AI) to build the information interaction channels between people, things, and space.Sign language recognition not only assists the visitors who have hearing or speech impairment to visit the museum without barriers but also helps study the visitors’ natural gesture interaction.However, the methods based on cameras and wearable devices mayhave issues like privacy or usability when applied to museum spaces.Therefore, a robust sign language recognition method based on millimeter-wave radar was proposed.Different features of distance and velocity changes relative to the radar device were firstly extracted in this method, then a physical data enhancement method was adopted to expand the training data.Finally, a ResNet based on the pre-processed distance time features and Doppler time features was designed to further remove the environment-related information and perform feature fusion for classification.Experimental results show that this method can effectively recognize sign language and achieve an averaged recognition accuracy of over 90% when the testing environment and the user＇s location change, providing a new method for smart museum wireless sign language and gesture recognition.关键词：sign language recognition;millimeter-wave radar;ResNet;smart museum275|759|0更新时间：2024-06-05
- 摘要：In order to accurately mine outliers and reduce the impact of outliers on communication data, a multi-scale outlier mining algorithm for stateless communication data in IPv6 remote monitoring network was investigated.The stateless communication data were obtained through an IPv6 remote monitoring network, and based on the seasonality, trend, and self-similarity characteristics of the extracted stateless communication data, the Fourier transform was used to divide the stateless communication data into two classes.Then, the K-mean method was used to cluster the two classes to determine the neighborhood of the stateless communication data, which was used as the basis for outlier mining using a convolutional neural network on the stateless communication data.The convolutional neural network was initialized, and according to the output value of the convolutional neural network, it was determined whether the network met the stopping condition.The operation steps of the convolutional neural network were repeated, all the outlier points were mined, and the multi-scale outlier mining of stateless communication data was achieved.The experimental results showed that the fewer the number of stateless communication data categories, the higher the mining efficiency; the proposed method can accurately mine the number of multiscale outliers of stateless communication data in IPv6 remote monitoring network and accurately analyze the reasons for the outliers.关键词：IPv6;remote monitoring network;stateless;communication data;multi-scale;outlier mining145|449|0更新时间：2024-06-05
Research and Development
- 摘要：The global telecom industry is carrying out research and exploration of potential 6G technical architectures and key techs, of which it has become a consensus in the industry to further realize the vision of 6G smart inclusion by better enabling all new 6G network technologies and services through joint communication ＆amp; computing (JC＆amp;C).Therefore, how to realize the deep integration and real-time collaboration of communication and computing to meet the needs of ultra-low latency and real-time response of new services in dynamic and complex network environments has become the challenge and key of JC＆amp;C.A computing native network (CNN) driven by JC＆amp;C was proposed, which realized the decoupling of communication and computing of base station or multiple base stations, computing pooling and intelligent JC＆amp;C scheduling through computing time division multiplexing and intelligent JC＆amp;C scheduling, thus realizing the base station to support communication and computation services simultaneously.The technology has been technically verified and piloted, and the experimental and pilot results demonstrate that CNN can effectively improve the computing utilization rate of wireless networks and realize the base station to support communication and computing services simultaneously, facilitating the evolution of 6G JC＆amp;C.关键词：joint communication ＆computing;computing native network;awareness unit;intelligent JC＆C scheduling382|1070|0更新时间：2024-06-05
- 摘要：The computing power network needs to maximize the system performance index on the basis of meeting user business needs, and the existing methods are mainly based on the multi-objective weighting method, which has problems such as difficult to determine hyperparameters and poor cross-scenario applicability.Based on this, based on the analysis of the characteristics of the computing power network target, the user business requirements were taken as the policy constraints, and the performance indicators of the computing power network was taken as the optimization goal based on constrained policy optimization, and the expectation certainty of user business needs and the optimization of system performance through the value-strategy-hyper-parameter multi-level iterative strategy was realized.At the same time, the multi-scale step length (MSL) method for hyper-parameter optimization was studied, which further improved the stability and accuracy of the system.Simulation results show that the proposed method has good convergence and stability under the conditions of single terminal-single edge server, multi-terminal-multi-edge server and system load change.关键词：computing power network;multi-objective optimization;reinforcement learning331|694|0更新时间：2024-06-05
- 摘要：With the needs of high-quality development of the digital economy, the research on computing power network is accelerating.How to realize the integrated scheduling of computing resources and network resources becomes the primary challenge for computing power network.The evolution of computing power network was introduced, the resource awaring and routing scheduling technology of computing power network were analyzed, and a hybrid routing scheduling solution for computing power network was proposed to realize the ability of flexible on-demand, fast routing and easy implementation.The implementation process of the hybrid routing scheduling solution in the remote driving scenario of the Internet of vehicles was introduced, which supported the provision of differentiated services integrating computing and networking and fast tuning when the vehicle was moving.关键词：computing power network;resource awaring;routing scheduling1018|1442|0更新时间：2024-06-05
- 摘要：With the promotion of national secret algorithm, in-depth research on the arithmetic network was carried out, a more efficient and reasonable security scheme for the arithmetic network was proposed, ensuring the data security and privacy of the arithmetic network with the help of the state secret algorithm.The main elements of the design program included: Supporting arithmetic demand and cryptographic invocation through the underlying resources, the arithmetic orchestration layer provided the ability to orchestrate data arithmetic, meanwhile, the arithmetic scheduling layer intelligently discerned the optimal nodes for arithmetic resource scheduling and allocation; the cryptographic reinforcement layer used the national secret algorithm based on hardware support with the help of public key cryptosystem, hash function, digital envelope, homomorphic encryption, blockchain and other technologies.Focusing on arithmetic network access security, transmission security, data security and privacy protection aspects of security implementation.An architecture and application form was innovatively proposed to guarantee the data security of the arithmetic network, which could meet the needs of the application layer arithmetic in the scenarios of big data, intelligent technology, etc..The security of the arithmetic network is enhanced by empowering the arithmetic network through the state-secret algorithm.关键词：compute first networking;national secret algorithm;privacy protection;fully homomorphic encryption;blockchain459|982|0更新时间：2024-06-05
Topic: Computing Power Network
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