The global adoption of Electric Vehicles(EVs)is on the rise due to their advanced features,with projections indicating they will soon dominate the private vehicle market.However,improper management of EV charging can ...The global adoption of Electric Vehicles(EVs)is on the rise due to their advanced features,with projections indicating they will soon dominate the private vehicle market.However,improper management of EV charging can lead to significant issues.This paper reviews the development of high-power,reliable charging solutions by examining the converter topologies used in rectifiers and converters that transfer electricity from the grid to EV batteries.It covers technical details,ongoing developments,and challenges related to these topologies and control strategies.The integration of rapid charging stations has introduced various Power Quality(PQ)issues,such as voltage fluctuations,harmonic distortion,and supra-harmonics,which are discussed in detail.The paper also highlights the benefits of controlled EV charging and discharging,including voltage and frequency regulation,reactive power compensation,and improved power quality.Efficient energy management and control strategies are crucial for optimizing EV battery charging within microgrids to meet increasing demand.Charging stations must adhere to specific converter topologies,control strategies,and industry standards to function correctly.The paper explores microgrid architectures and control strategies that integrate EVs,energy storage units(ESUs),and Renewable Energy Sources(RES)to enhance performance at charging points.It emphasizes the importance of various RES-connected architectures and the latest power converter topologies.Additionally,the paper provides a comparative analysis of microgrid-based charging station architectures,focusing on energy management,control strategies,and charging converter controls.The goal is to offer insights into future research directions in EV charging systems,including architectural considerations,control factors,and their respective advantages and disadvantages.展开更多
In this paper,a novel wideband 8-element multiple-input and multiple-output(MIMO)antenna based on Booker’s relation is proposed for the fifth generation(5G)handset applications.The 8 antenna elements are arranged sym...In this paper,a novel wideband 8-element multiple-input and multiple-output(MIMO)antenna based on Booker’s relation is proposed for the fifth generation(5G)handset applications.The 8 antenna elements are arranged symmetrically along the two longer vertical side-edge frames of the handset.Each antenna element is composed of a monopole and a slot radiation structure,in which wideband characteristic covering 3140-5620MHz can be obtained.Note that the L-shaped monopole and the slot can be deemed as complementary counterparts approximatively.Furthermore,the Z-parameter of the proposed wideband antenna element is equivalent to the shunt impedance of monopole as well as slot radiator.Based on Booker’s relation,the wideband input impedance characteristic is therein achieved compared with conventional wideband technique such as multiresonance.Four L-shaped stubs as well as two slots etched on the ground plane are utilized to achieve acceptable isolation performance better than 13 dB,with total efficiency higher than 60%and envelope correlation coefficients(ECCs)lower than 0.1.The proposed antenna scheme can be a good candidate for 5G handset applications with the advantages of wideband,simple structure,high efficiency,and acceptable isolation performance.Also,the scheme might be a rewarding attempt to promote the Booker’s relation in the application of 5G terminal MIMO antenna designs.展开更多
Wireless networks support numerous terminals,manage large data volumes,and provide diverse services,but the vulnerability to environmental changes leads to increased complexity and costs.Situational awareness has been...Wireless networks support numerous terminals,manage large data volumes,and provide diverse services,but the vulnerability to environmental changes leads to increased complexity and costs.Situational awareness has been widely applied in network management,but existing methods fail to find optimal solutions due to the high heterogeneity of base stations,numerous metrics,and complex intercell dependencies.To address this gap,this paper proposes a specialized framework for wireless networks,integrating an evaluation model and control approach.The framework expands the indicator set into four key areas,introduces an evaluation method,and proposes the indicator perturbation greedy(IPG)algorithm and the adjustment scheme selection method based on damping coefficient(DCSS)for effective network optimization.A case study in an urban area demonstrates the framework’s ability to balance and improve network performance,enhancing situational awareness and operational efficiency under dynamic conditions.展开更多
High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support s...High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support stable and efficient transmission.The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion,meeting fairness requirements and improving transmission efficiency.However,current algorithms’Congestion Window(CWND)reduction approach significantly decreases CWND upon packet loss,which lowers effective throughput,regardless of the congestion origin.Furthermore,the uncoupled Slow-Start(SS)in MPQUIC leads to independent exponential CWND growth on each path,potentially causing buffer overflow.To address these issues,we propose the CC-OLIA,which incorporates Packet Loss Classifcation(PLC)and Coupled Slow-Start(CSS).The PLC distinguishes between congestion-induced and random packet losses,adjusting CWND reduction accordingly to maintain throughput.Concurrently,the CSS module coordinates CWND growth during the SS,preventing abrupt increases.Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.展开更多
Essential proteins are an indispensable part of cells and play an extremely significant role in genetic disease diagnosis and drug development.Therefore,the prediction of essential proteins has received extensive atte...Essential proteins are an indispensable part of cells and play an extremely significant role in genetic disease diagnosis and drug development.Therefore,the prediction of essential proteins has received extensive attention from researchers.Many centrality methods and machine learning algorithms have been proposed to predict essential proteins.Nevertheless,the topological characteristics learned by the centrality method are not comprehensive enough,resulting in low accuracy.In addition,machine learning algorithms need sufficient prior knowledge to select features,and the ability to solve imbalanced classification problems needs to be further strengthened.These two factors greatly affect the performance of predicting essential proteins.In this paper,we propose a deep learning framework based on temporal convolutional networks to predict essential proteins by integrating gene expression data and protein-protein interaction(PPI)network.We make use of the method of network embedding to automatically learn more abundant features of proteins in the PPI network.For gene expression data,we treat it as sequence data,and use temporal convolutional networks to extract sequence features.Finally,the two types of features are integrated and put into the multi-layer neural network to complete the final classification task.The performance of our method is evaluated by comparing with seven centrality methods,six machine learning algorithms,and two deep learning models.The results of the experiment show that our method is more effective than the comparison methods for predicting essential proteins.展开更多
With the emergence of new attack techniques,traffic classifiers usually fail to maintain the expected performance in real-world network environments.In order to have sufficient generalizability to deal with unknown ma...With the emergence of new attack techniques,traffic classifiers usually fail to maintain the expected performance in real-world network environments.In order to have sufficient generalizability to deal with unknown malicious samples,they require a large number of new samples for retraining.Considering the cost of data collection and labeling,data augmentation is an ideal solution.We propose an optimized noise-based traffic data augmentation system,ONTDAS.The system uses a gradient-based searching algorithm and an improved Bayesian optimizer to obtain optimized noise.The noise is injected into the original samples for data augmentation.Then,an improved bagging algorithm is used to integrate all the base traffic classifiers trained on noised datasets.The experiments verify ONTDAS on 6 types of base classifiers and 4 publicly available datasets respectively.The results show that ONTDAS can effectively enhance the traffic classifiers’performance and significantly improve their generalizability on unknown malicious samples.The system can also alleviate dataset imbalance.Moreover,the performance of ONTDAS is significantly superior to the existing data augmentation methods mentioned.展开更多
Space-division multiplexing(SDM)utilizing uncoupled multi-core fibers(MCF)is considered a promising candidate for nextgeneration high-speed optical transmission systems due to its huge capacity and low inter-core cros...Space-division multiplexing(SDM)utilizing uncoupled multi-core fibers(MCF)is considered a promising candidate for nextgeneration high-speed optical transmission systems due to its huge capacity and low inter-core crosstalk.In this paper,we demonstrate a realtime high-speed SDM transmission system over a field-deployed 7-core MCF cable using commercial 400 Gbit/s backbone optical transport network(OTN)transceivers and a network management system.The transceivers employ a high noise-tolerant quadrature phase shift keying(QPSK)modulation format with a 130 Gbaud rate,enabled by optoelectronic multi-chip module(OE-MCM)packaging.The network management system can effectively manage and monitor the performance of the 7-core SDM OTN system and promptly report failure events through alarms.Our field trial demonstrates the compatibility of uncoupled MCF with high-speed OTN transmission equipment and network management systems,supporting its future deployment in next-generation high-speed terrestrial cable transmission networks.展开更多
Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitat...Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitations,a novel two-level serially concatenated MLC scheme,in which the bitlevels with similar reliability are bundled and transmitted together,is proposed.The proposed scheme hierarchically protects the two bit-level sets:the bitlevel sets at the higher level are sufficiently reliable and do not require excessive resources for protection,whereas only the bit-level sets at the lower level are encoded by polar codes.The proposed scheme has the advantages of low power consumption,low delay and high reliability.Moreover,an optimized constellation signal labeling rule that can enhance the performance is proposed.Finally,the superiority of the proposed scheme is validated through the theoretical analysis and simulation results.Compared with the bit interleaving coding modulation(BICM)scheme,under 256-quadrature amplitude modulation(QAM),the proposed scheme attains a performance gain of 1.0 dB while reducing the decoding complexity by 54.55%.展开更多
Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth...Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.展开更多
This letter describes the implementation of a high-precision time and frequency transmission system using a two-way and wavelength division multiplexing scheme over 3,143.6 km of field fiber links,connecting 21 sites ...This letter describes the implementation of a high-precision time and frequency transmission system using a two-way and wavelength division multiplexing scheme over 3,143.6 km of field fiber links,connecting 21 sites between Xi’an and Beijing,China.This scheme incorporates a link noise clean-up system(LNCUS),wherein a controlled very-low-phase noise BVA oscillator acts as an internal frequency source at the relay site to effectively suppress the interference caused by the fiber link noise.Additionally,the high-stability pulse generation technology in the LNCPS provides sufficient short-term stability to significantly improve the stability of the fiber time transfer.The results indicate a time transfer stability in terms of time deviation(TDEV)of less than2.07 ps@1s,5.9 ps@100,000s,and combined uncertainty of less than 49.29 ps for the 3,143.6 km field fiber link.The results represent a significant breakthrough in achieving high-accuracy time transfer and continuous operation over ultralong-span field optical fibers exceeding 3,000 km for the first time.This enabled time transfer and synchronization services over the longest international optical fiber distance,thereby establishing a fundamental basis for constructing a nationwide high-precision time service through optical fiber networks.展开更多
With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(...With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.展开更多
Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present ...Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.展开更多
Waste tyres(WTs)are a major global issue that needs immediate attention to ensure a sustainable environment.They are often dumped in landfills or incinerated in open environments,which leads to environmental pollution...Waste tyres(WTs)are a major global issue that needs immediate attention to ensure a sustainable environment.They are often dumped in landfills or incinerated in open environments,which leads to environmental pollution.However,various thermochemical conversion methods have shown promising results as treatment routes to tackle the WT problem while creating new materials for industries.One such material is WT char,which has properties comparable to those of carbon materials used as an active electrode material in batteries.Therefore,a systematic review of the various thermochemical approaches used to convert WTs into carbon materials for electrode applications was conducted.The review shows that pretreatment processes,various process routes,and operating parameters affect derived carbon properties and its respective electrochemical performance.WT-derived carbon has the potential to yield a high specific capacity greater than the traditional graphite(372 mAh g^(−1))commonly used in lithium-ion batteries.Finally,the review outlines the challenges of the process routes,as well as opportunities and future research directions for electrode carbon materials from WTs.展开更多
Introducing multi-UAV network with flexible deployment into mobile edge computing(MEC)can effectively improve the quality of service of Internet-of-Things services,reduce the coverage cost and resource waste rate of e...Introducing multi-UAV network with flexible deployment into mobile edge computing(MEC)can effectively improve the quality of service of Internet-of-Things services,reduce the coverage cost and resource waste rate of edge nodes,and also bring some challenges.This paper first introduces the current situation and pain points of mobile edge computing,then analyzes the significance and value of using multi-UAV network to assist mobile edge computing,and summarizes its key technologies and typical applications.In the end,some open research problems and technology prospects of multi-UAV network assisted intelligent edge computing are put forward,which provide new ideas for the future development of this field.展开更多
Telecom operators are deploying the fifth generation(5G) networks around the world which promises high information transmission rate, wide network coverage, low communication delay, and easy access to a large number o...Telecom operators are deploying the fifth generation(5G) networks around the world which promises high information transmission rate, wide network coverage, low communication delay, and easy access to a large number of devices. However, during the construction and operation of 5G, telecom operators face many challenges, such as insufficient frequency resources, low efficiency of network management, information opacity, risks of data interoperability, and network privacy vulnerabilities. As 5G is generally deployed in heterogeneous networks with massive ubiquitous devices, it is quite necessary to provide secure and decentralized solutions. Blockchain is a distributed system maintained by multiple parties with inherit features including decentralization,traceability and tamperproof. These features collectively contribute to a new application ecosystem where transactions are secure and trustworthy. Therefore,blockchain is expected to integrate with 5G networks to build safer and more reliable mobile network infrastructures. This paper firstly discusses the merits of blockchain technology and the benefits of integrating it with 5G networks. Then a variety of applications of blockchain technology in telecom network operation are reviewed, including spectrum sharing, international roaming settlement, network operation management, number selection management and supply chain management. In the end, we show our recently advance in integrating blockchain in 5G by introducing a multi framework based blockchain service network architecture deployed in real environment.展开更多
The Service-based Architecture(SBA) is one of the key innovations of 5G architecture that leverage modularized, self-contained and independent services to provide flexible and cloud-native 5G network. In this paper, S...The Service-based Architecture(SBA) is one of the key innovations of 5G architecture that leverage modularized, self-contained and independent services to provide flexible and cloud-native 5G network. In this paper, SBA for Space-Air-Ground Integrated Network(SAGIN) is investigated to enable the 5G integration deployment. This paper proposes a novel Holistic Service-based Architecture(H-SBA)for SAGIN of 5G-Advanced and beyond, i.e., 6G. The H-SBA introduces the concept of end-to-end servicebased architecture design. The "Network Function Service", introduced in 5G SBA, is extended from Control Plane to User Plane, from core network to access network. Based on H-SBA, the new generation of protocol design is proposed, which proposes to use IETF QUIC and SRv6 to substitute 5G HTTP/2.0 and GTP-U. Testing results show that new protocols can achieve low latency and high throughput, making them promising candidate for H-SBA.展开更多
Unmanned Aerial Vehicles(UAVs)and Unmanned Ground Vehicles(UGVs)have been used in research and development community due to their strong potential in high-risk missions.One of the most important civilian implementatio...Unmanned Aerial Vehicles(UAVs)and Unmanned Ground Vehicles(UGVs)have been used in research and development community due to their strong potential in high-risk missions.One of the most important civilian implementations of UAV/UGV cooperative path planning is delivering medical or emergency supplies during disasters such as wildfires,the focus of this paper.However,wildfires themselves pose risk to the UAVs/UGVs and their paths should be planned to avert the risk as well as complete the mission.In this paper,wildfire growth is simulated using a coupled Partial Differential Equation(PDE)model,widely used in literature for modeling wildfires,in a grid environment with added process and measurement noise.Using principles of Proper Orthogonal Decomposition(POD),and with an appropriate choice of decomposition modes,a low-dimensional equivalent fire growth model is obtained for the deployment of the space-time Kalman Filtering(KF)paradigm for estimation of wildfires using simulated data.The KF paradigm is then used to estimate and predict the propagation of wildfire based on local data obtained from a camera mounted on the UAV.This information is then used to obtain a safe path for the UGV that needs to travel from an initial location to the final position while the UAV’s path is planned to gather information on wildfire.Path planning of both UAV and UGV is carried out using a PDE based method that allows incorporation of threats due to wildfire and other obstacles in the form of risk function.The results from numerical simulation are presented to validate the proposed estimation and path planning methods.展开更多
In this paper,we investigate and analyze the network security risks faced by 5G private industrial networks.Based on current network security architecture and 3GPP requirements and considering the actual application o...In this paper,we investigate and analyze the network security risks faced by 5G private industrial networks.Based on current network security architecture and 3GPP requirements and considering the actual application of 5G private industrial networks,a comparative analysis is used to plan and design a private network security construction scheme.The network security construction model,network organization,and key processes of 5G private industrial networks at the current stage are investigated.In addition,the key direction for the next stage of construction is discussed.展开更多
Inter-cell interference (ICI) mitigation is always a challenge issue in LTE system. In this paper, several common interference parameters are firstly analyzed for both cell edge users and center users, and then a nove...Inter-cell interference (ICI) mitigation is always a challenge issue in LTE system. In this paper, several common interference parameters are firstly analyzed for both cell edge users and center users, and then a novel fractional frequency reuse (FFR) architecture based on interference avoidance scheme coupled with power control is proposed to solve the problem of interference management in multi-cell LTE environment. The scheme divides the whole sub-carriers into three groups orthogonally. One is allocated to cell edge users, while another two are assigned to cell center users with different transmitter power. Then a parameter named interference avoidance factor (IAF) is defined to avoid ICI and adjust the number of allocated sub-carriers to match the number of users. The parameter also takes weight factor and fairness factor into consideration. The simulation results show the proposed scheme can improve the performance of cell edge users obviously.展开更多
Network virtualization(NV) is pushed forward by its proponents as a crucial attribute of next generation network, aiming at overcoming the gradual ossification of current networks, particularly to the worldwide Intern...Network virtualization(NV) is pushed forward by its proponents as a crucial attribute of next generation network, aiming at overcoming the gradual ossification of current networks, particularly to the worldwide Internet. Through virtualization, multiple customized virtual networks(VNs), requested by users, are allowed to coexist on the underlying substrate networks(SNs). In addition, the virtualization scheme contributes to sharing underlying physical resources simultaneously and seamlessly. However, multiple technical issues still stand in the way of NV successful implementation. One key technical issue is virtual network embedding(VNE), known as the resource allocation problem for NV. This paper conducts a survey of embedding algorithms for VNE problem. At first, the NV business model for VNE problem is presented. Then, the latest VNE problem description is presented. Main performance metrics for evaluating embedding algorithms are also involved. Afterwards, existing VNE algorithms are detailed, according to the novel proposed category approach. Next, key future research aspects of embedding algorithms are listed out. Finally, the paper is briefly concluded.展开更多
文摘The global adoption of Electric Vehicles(EVs)is on the rise due to their advanced features,with projections indicating they will soon dominate the private vehicle market.However,improper management of EV charging can lead to significant issues.This paper reviews the development of high-power,reliable charging solutions by examining the converter topologies used in rectifiers and converters that transfer electricity from the grid to EV batteries.It covers technical details,ongoing developments,and challenges related to these topologies and control strategies.The integration of rapid charging stations has introduced various Power Quality(PQ)issues,such as voltage fluctuations,harmonic distortion,and supra-harmonics,which are discussed in detail.The paper also highlights the benefits of controlled EV charging and discharging,including voltage and frequency regulation,reactive power compensation,and improved power quality.Efficient energy management and control strategies are crucial for optimizing EV battery charging within microgrids to meet increasing demand.Charging stations must adhere to specific converter topologies,control strategies,and industry standards to function correctly.The paper explores microgrid architectures and control strategies that integrate EVs,energy storage units(ESUs),and Renewable Energy Sources(RES)to enhance performance at charging points.It emphasizes the importance of various RES-connected architectures and the latest power converter topologies.Additionally,the paper provides a comparative analysis of microgrid-based charging station architectures,focusing on energy management,control strategies,and charging converter controls.The goal is to offer insights into future research directions in EV charging systems,including architectural considerations,control factors,and their respective advantages and disadvantages.
基金supported in part by Natural Science Foundation of Fujian Province(2021J05178)in part by the Scientific Research Foundation of Jimei University(ZQ2021001).
文摘In this paper,a novel wideband 8-element multiple-input and multiple-output(MIMO)antenna based on Booker’s relation is proposed for the fifth generation(5G)handset applications.The 8 antenna elements are arranged symmetrically along the two longer vertical side-edge frames of the handset.Each antenna element is composed of a monopole and a slot radiation structure,in which wideband characteristic covering 3140-5620MHz can be obtained.Note that the L-shaped monopole and the slot can be deemed as complementary counterparts approximatively.Furthermore,the Z-parameter of the proposed wideband antenna element is equivalent to the shunt impedance of monopole as well as slot radiator.Based on Booker’s relation,the wideband input impedance characteristic is therein achieved compared with conventional wideband technique such as multiresonance.Four L-shaped stubs as well as two slots etched on the ground plane are utilized to achieve acceptable isolation performance better than 13 dB,with total efficiency higher than 60%and envelope correlation coefficients(ECCs)lower than 0.1.The proposed antenna scheme can be a good candidate for 5G handset applications with the advantages of wideband,simple structure,high efficiency,and acceptable isolation performance.Also,the scheme might be a rewarding attempt to promote the Booker’s relation in the application of 5G terminal MIMO antenna designs.
文摘Wireless networks support numerous terminals,manage large data volumes,and provide diverse services,but the vulnerability to environmental changes leads to increased complexity and costs.Situational awareness has been widely applied in network management,but existing methods fail to find optimal solutions due to the high heterogeneity of base stations,numerous metrics,and complex intercell dependencies.To address this gap,this paper proposes a specialized framework for wireless networks,integrating an evaluation model and control approach.The framework expands the indicator set into four key areas,introduces an evaluation method,and proposes the indicator perturbation greedy(IPG)algorithm and the adjustment scheme selection method based on damping coefficient(DCSS)for effective network optimization.A case study in an urban area demonstrates the framework’s ability to balance and improve network performance,enhancing situational awareness and operational efficiency under dynamic conditions.
文摘High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support stable and efficient transmission.The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion,meeting fairness requirements and improving transmission efficiency.However,current algorithms’Congestion Window(CWND)reduction approach significantly decreases CWND upon packet loss,which lowers effective throughput,regardless of the congestion origin.Furthermore,the uncoupled Slow-Start(SS)in MPQUIC leads to independent exponential CWND growth on each path,potentially causing buffer overflow.To address these issues,we propose the CC-OLIA,which incorporates Packet Loss Classifcation(PLC)and Coupled Slow-Start(CSS).The PLC distinguishes between congestion-induced and random packet losses,adjusting CWND reduction accordingly to maintain throughput.Concurrently,the CSS module coordinates CWND growth during the SS,preventing abrupt increases.Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.
基金the National Natural Science Foundation of China(Nos.11861045 and 62162040)。
文摘Essential proteins are an indispensable part of cells and play an extremely significant role in genetic disease diagnosis and drug development.Therefore,the prediction of essential proteins has received extensive attention from researchers.Many centrality methods and machine learning algorithms have been proposed to predict essential proteins.Nevertheless,the topological characteristics learned by the centrality method are not comprehensive enough,resulting in low accuracy.In addition,machine learning algorithms need sufficient prior knowledge to select features,and the ability to solve imbalanced classification problems needs to be further strengthened.These two factors greatly affect the performance of predicting essential proteins.In this paper,we propose a deep learning framework based on temporal convolutional networks to predict essential proteins by integrating gene expression data and protein-protein interaction(PPI)network.We make use of the method of network embedding to automatically learn more abundant features of proteins in the PPI network.For gene expression data,we treat it as sequence data,and use temporal convolutional networks to extract sequence features.Finally,the two types of features are integrated and put into the multi-layer neural network to complete the final classification task.The performance of our method is evaluated by comparing with seven centrality methods,six machine learning algorithms,and two deep learning models.The results of the experiment show that our method is more effective than the comparison methods for predicting essential proteins.
基金supported in part by the National Key Research and Development Program of China(No.2022YFB4500800)the National Science Foundation of China(No.42071431).
文摘With the emergence of new attack techniques,traffic classifiers usually fail to maintain the expected performance in real-world network environments.In order to have sufficient generalizability to deal with unknown malicious samples,they require a large number of new samples for retraining.Considering the cost of data collection and labeling,data augmentation is an ideal solution.We propose an optimized noise-based traffic data augmentation system,ONTDAS.The system uses a gradient-based searching algorithm and an improved Bayesian optimizer to obtain optimized noise.The noise is injected into the original samples for data augmentation.Then,an improved bagging algorithm is used to integrate all the base traffic classifiers trained on noised datasets.The experiments verify ONTDAS on 6 types of base classifiers and 4 publicly available datasets respectively.The results show that ONTDAS can effectively enhance the traffic classifiers’performance and significantly improve their generalizability on unknown malicious samples.The system can also alleviate dataset imbalance.Moreover,the performance of ONTDAS is significantly superior to the existing data augmentation methods mentioned.
文摘Space-division multiplexing(SDM)utilizing uncoupled multi-core fibers(MCF)is considered a promising candidate for nextgeneration high-speed optical transmission systems due to its huge capacity and low inter-core crosstalk.In this paper,we demonstrate a realtime high-speed SDM transmission system over a field-deployed 7-core MCF cable using commercial 400 Gbit/s backbone optical transport network(OTN)transceivers and a network management system.The transceivers employ a high noise-tolerant quadrature phase shift keying(QPSK)modulation format with a 130 Gbaud rate,enabled by optoelectronic multi-chip module(OE-MCM)packaging.The network management system can effectively manage and monitor the performance of the 7-core SDM OTN system and promptly report failure events through alarms.Our field trial demonstrates the compatibility of uncoupled MCF with high-speed OTN transmission equipment and network management systems,supporting its future deployment in next-generation high-speed terrestrial cable transmission networks.
基金supported by the External Cooperation Program of Science and Technology of Fujian Province,China(2024I0016)the Fundamental Research Funds for the Central Universities(ZQN-1005).
文摘Multilevel coding(MLC)is a commonly used polar coded modulation scheme,but challenging to implement in engineering due to its high complexity and long decoding delay for high-order modulations.To address these limitations,a novel two-level serially concatenated MLC scheme,in which the bitlevels with similar reliability are bundled and transmitted together,is proposed.The proposed scheme hierarchically protects the two bit-level sets:the bitlevel sets at the higher level are sufficiently reliable and do not require excessive resources for protection,whereas only the bit-level sets at the lower level are encoded by polar codes.The proposed scheme has the advantages of low power consumption,low delay and high reliability.Moreover,an optimized constellation signal labeling rule that can enhance the performance is proposed.Finally,the superiority of the proposed scheme is validated through the theoretical analysis and simulation results.Compared with the bit interleaving coding modulation(BICM)scheme,under 256-quadrature amplitude modulation(QAM),the proposed scheme attains a performance gain of 1.0 dB while reducing the decoding complexity by 54.55%.
基金supported by the National Natural Science Foundation of China(62122064,62331021,62371410)the Natural Science Foundation of Fujian Province of China(2023J02005 and 2021J011184)+1 种基金the President Fund of Xiamen University(20720220063)the Nanqiang Outstanding Talents Program of Xiamen University.
文摘Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.
文摘This letter describes the implementation of a high-precision time and frequency transmission system using a two-way and wavelength division multiplexing scheme over 3,143.6 km of field fiber links,connecting 21 sites between Xi’an and Beijing,China.This scheme incorporates a link noise clean-up system(LNCUS),wherein a controlled very-low-phase noise BVA oscillator acts as an internal frequency source at the relay site to effectively suppress the interference caused by the fiber link noise.Additionally,the high-stability pulse generation technology in the LNCPS provides sufficient short-term stability to significantly improve the stability of the fiber time transfer.The results indicate a time transfer stability in terms of time deviation(TDEV)of less than2.07 ps@1s,5.9 ps@100,000s,and combined uncertainty of less than 49.29 ps for the 3,143.6 km field fiber link.The results represent a significant breakthrough in achieving high-accuracy time transfer and continuous operation over ultralong-span field optical fibers exceeding 3,000 km for the first time.This enabled time transfer and synchronization services over the longest international optical fiber distance,thereby establishing a fundamental basis for constructing a nationwide high-precision time service through optical fiber networks.
基金supported by Tianshan Talent Training Project-Xinjiang Science and Technology Innovation Team Program(2023TSYCTD).
文摘With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.
文摘Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.
基金This work was financially supported by the Natural Science Fund from Ningbo Municipal Bureau of science and Technology(Nos.2023J040,2023J278)the NingboScience and Technology Project(No.2022-DST-004)This project was also supported partially by the TechnologyInnovation Center for Land Spatial Ecorestoration in theMetropolitan Area,the Ministry of Natural Resources,and the Fundamental Research Funds for the central Universities(CXZX2022A02)
文摘Waste tyres(WTs)are a major global issue that needs immediate attention to ensure a sustainable environment.They are often dumped in landfills or incinerated in open environments,which leads to environmental pollution.However,various thermochemical conversion methods have shown promising results as treatment routes to tackle the WT problem while creating new materials for industries.One such material is WT char,which has properties comparable to those of carbon materials used as an active electrode material in batteries.Therefore,a systematic review of the various thermochemical approaches used to convert WTs into carbon materials for electrode applications was conducted.The review shows that pretreatment processes,various process routes,and operating parameters affect derived carbon properties and its respective electrochemical performance.WT-derived carbon has the potential to yield a high specific capacity greater than the traditional graphite(372 mAh g^(−1))commonly used in lithium-ion batteries.Finally,the review outlines the challenges of the process routes,as well as opportunities and future research directions for electrode carbon materials from WTs.
基金supported by the National Natural Science Foundation of China(NSFC)with Grant 61720106001。
文摘Introducing multi-UAV network with flexible deployment into mobile edge computing(MEC)can effectively improve the quality of service of Internet-of-Things services,reduce the coverage cost and resource waste rate of edge nodes,and also bring some challenges.This paper first introduces the current situation and pain points of mobile edge computing,then analyzes the significance and value of using multi-UAV network to assist mobile edge computing,and summarizes its key technologies and typical applications.In the end,some open research problems and technology prospects of multi-UAV network assisted intelligent edge computing are put forward,which provide new ideas for the future development of this field.
文摘Telecom operators are deploying the fifth generation(5G) networks around the world which promises high information transmission rate, wide network coverage, low communication delay, and easy access to a large number of devices. However, during the construction and operation of 5G, telecom operators face many challenges, such as insufficient frequency resources, low efficiency of network management, information opacity, risks of data interoperability, and network privacy vulnerabilities. As 5G is generally deployed in heterogeneous networks with massive ubiquitous devices, it is quite necessary to provide secure and decentralized solutions. Blockchain is a distributed system maintained by multiple parties with inherit features including decentralization,traceability and tamperproof. These features collectively contribute to a new application ecosystem where transactions are secure and trustworthy. Therefore,blockchain is expected to integrate with 5G networks to build safer and more reliable mobile network infrastructures. This paper firstly discusses the merits of blockchain technology and the benefits of integrating it with 5G networks. Then a variety of applications of blockchain technology in telecom network operation are reviewed, including spectrum sharing, international roaming settlement, network operation management, number selection management and supply chain management. In the end, we show our recently advance in integrating blockchain in 5G by introducing a multi framework based blockchain service network architecture deployed in real environment.
基金funded by Tsinghua University-China Mobile Communications Group Co., Ltd. Joint Institute。
文摘The Service-based Architecture(SBA) is one of the key innovations of 5G architecture that leverage modularized, self-contained and independent services to provide flexible and cloud-native 5G network. In this paper, SBA for Space-Air-Ground Integrated Network(SAGIN) is investigated to enable the 5G integration deployment. This paper proposes a novel Holistic Service-based Architecture(H-SBA)for SAGIN of 5G-Advanced and beyond, i.e., 6G. The H-SBA introduces the concept of end-to-end servicebased architecture design. The "Network Function Service", introduced in 5G SBA, is extended from Control Plane to User Plane, from core network to access network. Based on H-SBA, the new generation of protocol design is proposed, which proposes to use IETF QUIC and SRv6 to substitute 5G HTTP/2.0 and GTP-U. Testing results show that new protocols can achieve low latency and high throughput, making them promising candidate for H-SBA.
文摘Unmanned Aerial Vehicles(UAVs)and Unmanned Ground Vehicles(UGVs)have been used in research and development community due to their strong potential in high-risk missions.One of the most important civilian implementations of UAV/UGV cooperative path planning is delivering medical or emergency supplies during disasters such as wildfires,the focus of this paper.However,wildfires themselves pose risk to the UAVs/UGVs and their paths should be planned to avert the risk as well as complete the mission.In this paper,wildfire growth is simulated using a coupled Partial Differential Equation(PDE)model,widely used in literature for modeling wildfires,in a grid environment with added process and measurement noise.Using principles of Proper Orthogonal Decomposition(POD),and with an appropriate choice of decomposition modes,a low-dimensional equivalent fire growth model is obtained for the deployment of the space-time Kalman Filtering(KF)paradigm for estimation of wildfires using simulated data.The KF paradigm is then used to estimate and predict the propagation of wildfire based on local data obtained from a camera mounted on the UAV.This information is then used to obtain a safe path for the UGV that needs to travel from an initial location to the final position while the UAV’s path is planned to gather information on wildfire.Path planning of both UAV and UGV is carried out using a PDE based method that allows incorporation of threats due to wildfire and other obstacles in the form of risk function.The results from numerical simulation are presented to validate the proposed estimation and path planning methods.
文摘In this paper,we investigate and analyze the network security risks faced by 5G private industrial networks.Based on current network security architecture and 3GPP requirements and considering the actual application of 5G private industrial networks,a comparative analysis is used to plan and design a private network security construction scheme.The network security construction model,network organization,and key processes of 5G private industrial networks at the current stage are investigated.In addition,the key direction for the next stage of construction is discussed.
基金Sponsored by the Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT0949)the Fundamental Research Funds for the Central Universities(Grant No.2010JBZ008),the Fundamental Research Funds for the Central Universities(Grant No.KWJB10006536)+1 种基金the Joint Funds of State Key Program of NSFC(Grant No.60830001)the State Key Laboratory of Rail Traffic Control and Safety(Grant No.RCS2008ZZ007)
文摘Inter-cell interference (ICI) mitigation is always a challenge issue in LTE system. In this paper, several common interference parameters are firstly analyzed for both cell edge users and center users, and then a novel fractional frequency reuse (FFR) architecture based on interference avoidance scheme coupled with power control is proposed to solve the problem of interference management in multi-cell LTE environment. The scheme divides the whole sub-carriers into three groups orthogonally. One is allocated to cell edge users, while another two are assigned to cell center users with different transmitter power. Then a parameter named interference avoidance factor (IAF) is defined to avoid ICI and adjust the number of allocated sub-carriers to match the number of users. The parameter also takes weight factor and fairness factor into consideration. The simulation results show the proposed scheme can improve the performance of cell edge users obviously.
基金supported by the National Key Research and Development of China under Grant 2018YFC1314903the National Natural Science Foundation of China under Grant 61372124 and Grant 61427801
文摘Network virtualization(NV) is pushed forward by its proponents as a crucial attribute of next generation network, aiming at overcoming the gradual ossification of current networks, particularly to the worldwide Internet. Through virtualization, multiple customized virtual networks(VNs), requested by users, are allowed to coexist on the underlying substrate networks(SNs). In addition, the virtualization scheme contributes to sharing underlying physical resources simultaneously and seamlessly. However, multiple technical issues still stand in the way of NV successful implementation. One key technical issue is virtual network embedding(VNE), known as the resource allocation problem for NV. This paper conducts a survey of embedding algorithms for VNE problem. At first, the NV business model for VNE problem is presented. Then, the latest VNE problem description is presented. Main performance metrics for evaluating embedding algorithms are also involved. Afterwards, existing VNE algorithms are detailed, according to the novel proposed category approach. Next, key future research aspects of embedding algorithms are listed out. Finally, the paper is briefly concluded.
