In view of the problems of inconsistent data semantics,inconsistent data formats,and difficult data quality assurance between the railway engineering design phase and the construction and operation phase,as well as th...In view of the problems of inconsistent data semantics,inconsistent data formats,and difficult data quality assurance between the railway engineering design phase and the construction and operation phase,as well as the difficulty in fully realizing the value of design results,this paper proposes a design and implementation scheme for a railway engineering collaborative design platform.The railway engineering collaborative design platform mainly includes functional modules such as metadata management,design collaboration,design delivery management,model component library,model rendering services,and Building Information Modeling(BIM)application services.Based on this,research is conducted on multi-disciplinary parameterized collaborative design technology for railway engineering,infrastructure data management and delivery technology,and design multi-source data fusion and application technology.The railway engineering collaborative design platform is compared with other railway design software to further validate its advantages and advanced features.The platform has been widely applied in multiple railway construction projects,greatly improving the design and project management efficiency.展开更多
The emergence of artificial intelligence natural language large models has brought new dawn for the in-depth empowerment of the industry.Research on key technologies and applications of railway natural language large ...The emergence of artificial intelligence natural language large models has brought new dawn for the in-depth empowerment of the industry.Research on key technologies and applications of railway natural language large model is of great significance to promoting and coordinating the development of railway artificial intelligence.This paper puts forward the application scenarios of railway natural language large model according to the application requirements of railway artificial intelligence;designs the overall architecture of the railway natural language large model by relying on the railway artificial intelligence platform,studies the key technologies of the natural language large model,builds a railway industry large model oriented to intelligent question-answering,and verifies the model with actual data;finally,this paper prospects for the development and application of railway natural language large model from the aspects of railway traffic organization,railway operation safety and passenger service.展开更多
The advancement of modern integrated transport systems has made the promotion of passenger intermodal transport an effective strategy for enhancing the quality of transport services.The railway sector is capitalizing ...The advancement of modern integrated transport systems has made the promotion of passenger intermodal transport an effective strategy for enhancing the quality of transport services.The railway sector is capitalizing on its strengths to offer passenger intermodal services centered around rail transport,resulting in the development of an integrated service platform for railway passenger intermodal transport,i.e.R-MaaS.This paper defines R-MaaS,outlines its objectives,and explores its fundamental concepts.A comprehensive architecture and key technologies for the R-MaaS platform are proposed,featuring a“vertical layering+horizontal modularization”design.Detailed designs are provided in areas such as data integration,intermodal order structure,ticketing process,and reconciliation settlement.This architecture facilitates the integration of ticketing services across various industries and systems,enabling users to access unified intermodal ticketing services,and supporting the vision of“one-time ticket purchase,one-time payment,and one-ID card(QR code)pass”.Through practical case studies of R-MaaS engineering applications,this paper analyzes and summarizes the effectiveness of R-MaaS implementation.On this basis,railway sector will play a leading and exemplary role in advancing passenger intermodal transport in China.展开更多
By relying on the major projects of Beijing-Zhangjiakou HSR,China's railway industry has integrated and applied several digital intelligence technologies to form a complete set of intelligent HSR 1.0 technology,wh...By relying on the major projects of Beijing-Zhangjiakou HSR,China's railway industry has integrated and applied several digital intelligence technologies to form a complete set of intelligent HSR 1.0 technology,which has been popularized and applied to several new lines.With the continuous deepening of intelligent applications in construction,equipment,operation and other fields,there is an increasingly urgent need for integrated sharing and analysis of models and data.The paper analyzes the connotation and key points of model-data integration and puts forward the overall architecture of model-data integration platform composed of model-data convergence tier,model-data storage tier,model-data management tier,model-data calculation tier,model data aggregation tier,etc.Moreover,it looks forward to the prospect of leading key technologies and multiple innovative key technologies such as intelligent engineering survey and generative design,all-discipline intelligent construction,digital twin of railway engineering,CR450 intelligent EMU,new generation of dedicated mobile communication for railway (5G-R), operation safety protection based on multi-source information perception, transmission and fusion analysis, displacement-based full-travel intelligent service (MaaS+), intelligent comprehensive dispatching of regional railway network, wheel-rail integrated intelligent maintenance of EMU, etc. It can provide guidance and reference for digital railway construction and intelligent HSR 2.0 scientific & technological breakthroughs.展开更多
The advent of Grover’s algorithm presents a significant threat to classical block cipher security,spurring research into post-quantum secure cipher design.This study engineers quantum circuit implementations for thre...The advent of Grover’s algorithm presents a significant threat to classical block cipher security,spurring research into post-quantum secure cipher design.This study engineers quantum circuit implementations for three versions of the Ballet family block ciphers.The Ballet‑p/k includes a modular-addition operation uncommon in lightweight block ciphers.Quantum ripple-carry adder is implemented for both“32+32”and“64+64”scale to support this operation.Subsequently,qubits,quantum gates count,and quantum circuit depth of three versions of Ballet algorithm are systematically evaluated under quantum computing model,and key recovery attack circuits are constructed based on Grover’s algorithm against each version.The comprehensive analysis shows:Ballet-128/128 fails to NIST Level 1 security,while when the resource accounting is restricted to the Clifford gates and T gates set for the Ballet-128/256 and Ballet-256/256 quantum circuits,the design attains Level 3.展开更多
Purpose–This paper conducts a joint analysis of monitoring data in the hidden danger areas of railway subgrade deformation using a data-driven method,thereby realizing the systematic risk identification of regional h...Purpose–This paper conducts a joint analysis of monitoring data in the hidden danger areas of railway subgrade deformation using a data-driven method,thereby realizing the systematic risk identification of regional hidden dangers.Design/methodology/approach–The paper proposes a regional systematic risk identification method based on Bayesian and independent component analysis(ICA)theories.Firstly,the Gray Wolf Optimization(GWO)algorithm is used to partition each group of monitoring data in the hidden danger area,so that the data distribution characteristics within each sub-block are similar.Then,a distributed ICA early warning model is constructed to obtain prior knowledge such as control limits and statistics of the area under normal conditions.For the online evaluation process,the input data is partitioned following the above-mentioned procedure and the ICA statistics of each sub-block are calculated.The Bayesian method is applied to fuse online parameters with offline parameters,yielding statistics under a specific confidence interval.These statistics are then compared with the control limits–specifically,checking whether they exceed the pre-set confidence parameters–thus realizing the systematic risk identification of the hidden danger area.Findings–Through simulation experiments,the proposed method can integrate prior knowledge such as control limits and statistics to effectively determine the overall stability status of the area,thereby realizing the systematic risk identification of the hidden danger area.Originality/value–The proposed method leverages Bayesian theory to fuse online process parameters with offline parameters and further compares them with confidence parameters,thereby effectively enhancing the utilization efficiency of monitoring data and the robustness of the analytical model.展开更多
Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and ...Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and compaction parameters.Design/methodology/approach-To address these issues,a novel multi-indicator IVCT method was proposed,including physical indicator dry density(ρd)and mechanical indicators dynamic stiffness(Krb)and bearing capacity coefficient(K20).Then,a series of IVCTs on HRGA under different compaction parameters were conducted with an improved vibration compactor,which could monitor the physical-mechanical indicators in real-time.Finally,the optimal vibration compaction parameters,including the moisture content(ω),the diameter-to-maximum particle size ratio(Rd),the thickness-to-maximum particle size ratio(Rh),the vibration frequency(f),the vibration mass(Mc)and the eccentric distance(re),were determined based on the evolution characteristics for the physical-mechanical indicators during compaction.Findings-All results indicated that theρd gradually increased and then stabilized,and the Krb initially increased and then decreased.Moreover,the inflection time of the Krb was present as the optimal compaction time(Tlp)during compaction.Additionally,optimal compaction was achieved whenωwas the water-holding content after mud pumping,Rd was 3.4,Rh was 3.5,f was the resonance frequency,and the ratio between the excitation force and the Mc was 1.8.Originality/value-The findings of this paper were significant for the quality control of HRGA compaction.展开更多
Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed ...Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.展开更多
Both accuracy and timeliness are key factors in detecting fake news on social media.However,most existing methods encounter an accuracy-timeliness dilemma:Content-only methods guarantee timeliness but perform moderate...Both accuracy and timeliness are key factors in detecting fake news on social media.However,most existing methods encounter an accuracy-timeliness dilemma:Content-only methods guarantee timeliness but perform moderately because of limited available information,while social context-based ones generally perform better but inevitably lead to latency because of social context accumulation needs.To break such a dilemma,a feasible but not well-studied solution is to leverage social contexts(e.g.,comments)from historical news for training a detection model and apply it to newly emerging news without social contexts.This requires the model to(1)sufficiently learn helpful knowledge from social contexts,and(2)be well compatible with situations that social contexts are available or not.To achieve this goal,we propose to absorb and parameterize useful knowledge from comments in historical news and then inject it into a content-only detection model.Specifically,we design the Comments ASsisted FakENews Detection method(CAS-FEND),which transfers useful knowledge from a comment-aware teacher model to a content-only student model and detects newly emerging news with the student model.Experiments show that the CAS-FEND student model outperforms all content-only methods and even comment-aware ones with 1/4 comments as inputs,demonstrating its superiority for early detection.展开更多
Accurate evaluation of elec-tron correlations is essential for the reliable quantitative de-scription of electronic struc-tures in strongly correlated sys-tems,including bond-dissociat-ing molecules,polyradicals,large...Accurate evaluation of elec-tron correlations is essential for the reliable quantitative de-scription of electronic struc-tures in strongly correlated sys-tems,including bond-dissociat-ing molecules,polyradicals,large conjugated molecules,and transition metal complex-es.To provide a user-friendly tool for studying such challeng-ing systems,our team developed Kylin 1.0[J.Comput.Chem.44,1316(2023)],an ab initio quantum chemistry program designed for efficient density matrix renormalization group(DMRG)and post-DMRG methods,enabling high-accuracy calculations with large active spaces.We have now further advanced the software with the release of Kylin 1.3,featuring optimized DMRG algorithms and an improved tensor contraction scheme in the diagonaliza-tion step.Benchmark calculations on the Mn_(4)CaO_(5)cluster demonstrate a remarkable speed-up of up to 16 fater than Kylin 1.0.Moreover,a more user-friendly and efficient algorithm[J.Chem.Theory Comput.17,3414(2021)]for sampling configurations from DMRG wavefunc-tion is implemented as well.Additionally,we have also implemented a spin-adapted version of the externally contracted multi-reference configuration interaction(EC-MRCI)method[J.Phys.Chem.A 128,958(2024)],further enhancing the program’s efficiency and accuracy for electron correlation calculations.展开更多
Behavioral scoring based on clinical observations remains the gold standard for screening,diagnosing,and evaluating infantile epileptic spasm syndrome(IESS).The accurate identification of seizures is crucial for clini...Behavioral scoring based on clinical observations remains the gold standard for screening,diagnosing,and evaluating infantile epileptic spasm syndrome(IESS).The accurate identification of seizures is crucial for clinical diagnosis and assessment.In this study,we propose an innovative seizure detection method based on video feature recognition of patient spasms.To capture the temporal characteristics of the spasm behavior presented in the videos effectively,we incorporate asymmetric convolutions and convolution–batch normalization–ReLU(CBR)modules.Specifically within the 3D-ResNet residual blocks,we split the larger convolutional kernels into two asymmetric 3D convolutional kernels.These kernels are connected in series to enhance the ability of the convolutional layers to extract key local features,both horizontally and vertically.In addition,we introduce a 3D convolutional block attention module to enhance the spatial correlations between video frame channels efficiently.To improve the generalization ability,we design a composite loss function that combines cross-entropy loss with triplet loss to balance the classification and similarity requirements.We train and evaluate our method using the PLA IESS-VIDEO dataset,achieving an average seizure recognition accuracy of 90.59%,precision of 90.94%,and recall of 87.64%.To validate its generalization capability further,we conducted external validation using six different patient monitoring videos compared with assessments by six human experts from various medical centers.The final test results demonstrate that our method achieved a recall of 0.6476,surpassing the average level achieved by human experts(0.5595),while attaining a high F1-score of 0.7219.These findings have substantial significance for the long-term assessment of patients with IESS.展开更多
With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular network...With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular networks(5G).The future sixth generation of mobile cellular networks(6G)is expected to have the capability to support new and unknown services with changing requirements.Hence,in addition to enhancing its capability by 10–100 times compared with 5G,6G should also be intelligent and open to adapt to the ever-changing services in the IoT,which requires a convergence of Communication,Computing and Caching(3C).Based on the analysis of the requirements of new services for 6G,this paper identifies key enabling technologies for an intelligent and open 6G network,all featured with 3C convergence.These technologies cover fundamental and emerging topics,including 3C-based spectrum management,radio channel construction,delay-aware transmission,wireless distributed computing,and network self-evolution.From the detailed analysis of these 3C-based technologies presented in this paper,we can see that although they are promising to enable an intelligent and open 6G,more efforts are needed to realize the expected 6G network.展开更多
With analysis of limitations Trusted Computing Group （TCG） has encountered, we argued that virtual machine monitor （VMM） is the appropriate architecture for implementing TCG specification. Putting together the VMM...With analysis of limitations Trusted Computing Group （TCG） has encountered, we argued that virtual machine monitor （VMM） is the appropriate architecture for implementing TCG specification. Putting together the VMM architecture, TCG hardware and application-oriented ＂thin＂ virtual machine （VM）, Trusted VMM-based security architecture is present in this paper with the character of reduced and distributed trusted computing base （TCB）. It provides isolation and integrity guarantees based on which general security requirements can be satisfied.展开更多
Purpose–Revenue management(RM)is a significant technique to improve revenue with limited resources.With the macro environment of dramatically increasing transit capacity and rapid railway transport development in Chi...Purpose–Revenue management(RM)is a significant technique to improve revenue with limited resources.With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China,it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.Design/methodology/approach–This paper proposes the theory and framework of generalized RM of railway passenger transport(RMRPT),and the thoughts and methods of the main techniques in RMRPT,involving demand forecasting,line planning,inventory control,pricing strategies and information systems,are all studied and elaborated.The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT.The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.Findings–The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.Originality/value–The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.展开更多
In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based ...In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based on the mMIMO under imperfect channel state information.Based on this,the SCE maximization problem is formulated by jointly optimizing the local computation frequency,the offloading time,the downloading time,the users and the base station transmit power.Due to its difficulty to directly solve the formulated problem,we first transform the fractional objective function into the subtractive form one via the dinkelbach method.Next,the original problem is transformed into a convex one by applying the successive convex approximation technique,and an iteration algorithm is proposed to obtain the solutions.Finally,the stimulations are conducted to show that the performance of the proposed schemes is superior to that of the other schemes.展开更多
In current research on task offloading and resource scheduling in vehicular networks,vehicles are commonly assumed to maintain constant speed or relatively stationary states,and the impact of speed variations on task ...In current research on task offloading and resource scheduling in vehicular networks,vehicles are commonly assumed to maintain constant speed or relatively stationary states,and the impact of speed variations on task offloading is often overlooked.It is frequently assumed that vehicles can be accurately modeled during actual motion processes.However,in vehicular dynamic environments,both the tasks generated by the vehicles and the vehicles’surroundings are constantly changing,making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios.Taking into account the actual dynamic vehicular scenarios,this paper considers the real-time non-uniform movement of vehicles and proposes a vehicular task dynamic offloading and scheduling algorithm for single-task multi-vehicle vehicular network scenarios,attempting to solve the dynamic decision-making problem in task offloading process.The optimization objective is to minimize the average task completion time,which is formulated as a multi-constrained non-linear programming problem.Due to the mobility of vehicles,a constraint model is applied in the decision-making process to dynamically determine whether the communication range is sufficient for task offloading and transmission.Finally,the proposed vehicular task dynamic offloading and scheduling algorithm based on muti-agent deep deterministic policy gradient(MADDPG)is applied to solve the optimal solution of the optimization problem.Simulation results show that the algorithm proposed in this paper is able to achieve lower latency task computation offloading.Meanwhile,the average task completion time of the proposed algorithm in this paper can be improved by 7.6%compared to the performance of the MADDPG scheme and 51.1%compared to the performance of deep deterministic policy gradient(DDPG).展开更多
Purpose–With the yearly increase of mileage and passenger volume in China’s high-speed railway,the problems of traditional paper railway tickets have become increasingly prominent,including complexity of business ha...Purpose–With the yearly increase of mileage and passenger volume in China’s high-speed railway,the problems of traditional paper railway tickets have become increasingly prominent,including complexity of business handling process,low efficiency of ticket inspection and high cost of usage and management.This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally.The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.Design/methodology/approach–Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system,the grid-oriented passenger service record(PSR)data storage model,efficient access to massive PSR data under high concurrency condition,the linkage between face recognition service platforms and various terminals in large scenarios,and two-factor authentication of the e-ticket identification code based on the key and the user identity information.Focusing on the key technologies and architecture the of existing ticketing system,multiple service resources are expanded and developed such as electronic ticket clusters,PSR clusters,face recognition clusters and electronic ticket identification code clusters.Findings–The proportion of paper ticket printed has dropped to 20%,saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide.The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds,significantly improving the efficiency of passenger transport organization.Meanwhile,problems of paper ticket counterfeiting,reselling and loss have been generally eliminated.Originality/value–E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.展开更多
Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affect...Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.展开更多
Prognostics and Health Management(PHM)technology is a critical component in establishing a precision-based Operation and Management(O&M)system for EMUs.This technology is essential for enhancing life cycle managem...Prognostics and Health Management(PHM)technology is a critical component in establishing a precision-based Operation and Management(O&M)system for EMUs.This technology is essential for enhancing life cycle management and advancing manufacturing and repair processes of EMUs.Through the analysis on O&M requirements of EMUs,this paper proposes the intelligent O&M objectives of EMUs based on PHM technology,as well as the system design architecture incorporating functions such as condition monitoring,fault prediction,health assessment,decision support and O&M analysis;and constructs a PHM-based standardized system for intelligent O&M of EMUs.The study also explores aspects such as the data lifecycle of EMUs,the development of PHM models,high-frequency streaming computation methods,unified management of heterogeneous models,and PHM-driven O&M production organization technologies.The PHM-based intelligent O&M system has been implemented across the railway network,achieving seamless information flow throughout the entire process of monitoring,decision-making and execution.展开更多
In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(...In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.展开更多
基金supported by the National Key Research and Development Program of China(2021YFB2600405).
文摘In view of the problems of inconsistent data semantics,inconsistent data formats,and difficult data quality assurance between the railway engineering design phase and the construction and operation phase,as well as the difficulty in fully realizing the value of design results,this paper proposes a design and implementation scheme for a railway engineering collaborative design platform.The railway engineering collaborative design platform mainly includes functional modules such as metadata management,design collaboration,design delivery management,model component library,model rendering services,and Building Information Modeling(BIM)application services.Based on this,research is conducted on multi-disciplinary parameterized collaborative design technology for railway engineering,infrastructure data management and delivery technology,and design multi-source data fusion and application technology.The railway engineering collaborative design platform is compared with other railway design software to further validate its advantages and advanced features.The platform has been widely applied in multiple railway construction projects,greatly improving the design and project management efficiency.
文摘The emergence of artificial intelligence natural language large models has brought new dawn for the in-depth empowerment of the industry.Research on key technologies and applications of railway natural language large model is of great significance to promoting and coordinating the development of railway artificial intelligence.This paper puts forward the application scenarios of railway natural language large model according to the application requirements of railway artificial intelligence;designs the overall architecture of the railway natural language large model by relying on the railway artificial intelligence platform,studies the key technologies of the natural language large model,builds a railway industry large model oriented to intelligent question-answering,and verifies the model with actual data;finally,this paper prospects for the development and application of railway natural language large model from the aspects of railway traffic organization,railway operation safety and passenger service.
文摘The advancement of modern integrated transport systems has made the promotion of passenger intermodal transport an effective strategy for enhancing the quality of transport services.The railway sector is capitalizing on its strengths to offer passenger intermodal services centered around rail transport,resulting in the development of an integrated service platform for railway passenger intermodal transport,i.e.R-MaaS.This paper defines R-MaaS,outlines its objectives,and explores its fundamental concepts.A comprehensive architecture and key technologies for the R-MaaS platform are proposed,featuring a“vertical layering+horizontal modularization”design.Detailed designs are provided in areas such as data integration,intermodal order structure,ticketing process,and reconciliation settlement.This architecture facilitates the integration of ticketing services across various industries and systems,enabling users to access unified intermodal ticketing services,and supporting the vision of“one-time ticket purchase,one-time payment,and one-ID card(QR code)pass”.Through practical case studies of R-MaaS engineering applications,this paper analyzes and summarizes the effectiveness of R-MaaS implementation.On this basis,railway sector will play a leading and exemplary role in advancing passenger intermodal transport in China.
文摘By relying on the major projects of Beijing-Zhangjiakou HSR,China's railway industry has integrated and applied several digital intelligence technologies to form a complete set of intelligent HSR 1.0 technology,which has been popularized and applied to several new lines.With the continuous deepening of intelligent applications in construction,equipment,operation and other fields,there is an increasingly urgent need for integrated sharing and analysis of models and data.The paper analyzes the connotation and key points of model-data integration and puts forward the overall architecture of model-data integration platform composed of model-data convergence tier,model-data storage tier,model-data management tier,model-data calculation tier,model data aggregation tier,etc.Moreover,it looks forward to the prospect of leading key technologies and multiple innovative key technologies such as intelligent engineering survey and generative design,all-discipline intelligent construction,digital twin of railway engineering,CR450 intelligent EMU,new generation of dedicated mobile communication for railway (5G-R), operation safety protection based on multi-source information perception, transmission and fusion analysis, displacement-based full-travel intelligent service (MaaS+), intelligent comprehensive dispatching of regional railway network, wheel-rail integrated intelligent maintenance of EMU, etc. It can provide guidance and reference for digital railway construction and intelligent HSR 2.0 scientific & technological breakthroughs.
基金State Key Lab of Processors,Institute of Computing Technology,Chinese Academy of Sciences(CLQ202516)the Fundamental Research Funds for the Central Universities of China(3282025047,3282024051,3282024009)。
文摘The advent of Grover’s algorithm presents a significant threat to classical block cipher security,spurring research into post-quantum secure cipher design.This study engineers quantum circuit implementations for three versions of the Ballet family block ciphers.The Ballet‑p/k includes a modular-addition operation uncommon in lightweight block ciphers.Quantum ripple-carry adder is implemented for both“32+32”and“64+64”scale to support this operation.Subsequently,qubits,quantum gates count,and quantum circuit depth of three versions of Ballet algorithm are systematically evaluated under quantum computing model,and key recovery attack circuits are constructed based on Grover’s algorithm against each version.The comprehensive analysis shows:Ballet-128/128 fails to NIST Level 1 security,while when the resource accounting is restricted to the Clifford gates and T gates set for the Ballet-128/256 and Ballet-256/256 quantum circuits,the design attains Level 3.
基金supported by Science and Technology Research and Development Program Project of China State Railway Group Co.,Ltd.(award number:K2024X010).
文摘Purpose–This paper conducts a joint analysis of monitoring data in the hidden danger areas of railway subgrade deformation using a data-driven method,thereby realizing the systematic risk identification of regional hidden dangers.Design/methodology/approach–The paper proposes a regional systematic risk identification method based on Bayesian and independent component analysis(ICA)theories.Firstly,the Gray Wolf Optimization(GWO)algorithm is used to partition each group of monitoring data in the hidden danger area,so that the data distribution characteristics within each sub-block are similar.Then,a distributed ICA early warning model is constructed to obtain prior knowledge such as control limits and statistics of the area under normal conditions.For the online evaluation process,the input data is partitioned following the above-mentioned procedure and the ICA statistics of each sub-block are calculated.The Bayesian method is applied to fuse online parameters with offline parameters,yielding statistics under a specific confidence interval.These statistics are then compared with the control limits–specifically,checking whether they exceed the pre-set confidence parameters–thus realizing the systematic risk identification of the hidden danger area.Findings–Through simulation experiments,the proposed method can integrate prior knowledge such as control limits and statistics to effectively determine the overall stability status of the area,thereby realizing the systematic risk identification of the hidden danger area.Originality/value–The proposed method leverages Bayesian theory to fuse online process parameters with offline parameters and further compares them with confidence parameters,thereby effectively enhancing the utilization efficiency of monitoring data and the robustness of the analytical model.
基金funded by the National Key R&D Program“Transportation Infrastructure”project(No.2022YFB2603400)the Technology Research and Development Plan Program of China State Railway Group Co.,Ltd.(No.Q2024T001)the National project pre research project of Suzhou City University(No.2023SGY019).
文摘Purpose-The indoor vibration compaction test(IVCT)was a key step in controlling the compaction quality for high-speed railway graded aggregate(HRGA),which currently had a research gap on the assessment indicators and compaction parameters.Design/methodology/approach-To address these issues,a novel multi-indicator IVCT method was proposed,including physical indicator dry density(ρd)and mechanical indicators dynamic stiffness(Krb)and bearing capacity coefficient(K20).Then,a series of IVCTs on HRGA under different compaction parameters were conducted with an improved vibration compactor,which could monitor the physical-mechanical indicators in real-time.Finally,the optimal vibration compaction parameters,including the moisture content(ω),the diameter-to-maximum particle size ratio(Rd),the thickness-to-maximum particle size ratio(Rh),the vibration frequency(f),the vibration mass(Mc)and the eccentric distance(re),were determined based on the evolution characteristics for the physical-mechanical indicators during compaction.Findings-All results indicated that theρd gradually increased and then stabilized,and the Krb initially increased and then decreased.Moreover,the inflection time of the Krb was present as the optimal compaction time(Tlp)during compaction.Additionally,optimal compaction was achieved whenωwas the water-holding content after mud pumping,Rd was 3.4,Rh was 3.5,f was the resonance frequency,and the ratio between the excitation force and the Mc was 1.8.Originality/value-The findings of this paper were significant for the quality control of HRGA compaction.
基金supported by the National Natural Science Foundation of China under Grant U21A20449in part by Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2。
文摘Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.
基金supported by the National Key R&D Program of China(2022YFC3302102)the National Natural Science Foundation of China(Grant Nos.62406310,62203425)+3 种基金the Postdoctoral Fellowship Program of CPSF(GZC20232738)the China Postdoctoral Science Foundation(2022TQ0344,2024M763336)the International Postdoctoral Exchange Fellowship Program by Office of China Postdoc Council(YJ20220198)the Open Research Project of the State Key Laboratory of Media Convergence and Communication,Communication University of China(SKLMCC2022KF001).
文摘Both accuracy and timeliness are key factors in detecting fake news on social media.However,most existing methods encounter an accuracy-timeliness dilemma:Content-only methods guarantee timeliness but perform moderately because of limited available information,while social context-based ones generally perform better but inevitably lead to latency because of social context accumulation needs.To break such a dilemma,a feasible but not well-studied solution is to leverage social contexts(e.g.,comments)from historical news for training a detection model and apply it to newly emerging news without social contexts.This requires the model to(1)sufficiently learn helpful knowledge from social contexts,and(2)be well compatible with situations that social contexts are available or not.To achieve this goal,we propose to absorb and parameterize useful knowledge from comments in historical news and then inject it into a content-only detection model.Specifically,we design the Comments ASsisted FakENews Detection method(CAS-FEND),which transfers useful knowledge from a comment-aware teacher model to a content-only student model and detects newly emerging news with the student model.Experiments show that the CAS-FEND student model outperforms all content-only methods and even comment-aware ones with 1/4 comments as inputs,demonstrating its superiority for early detection.
基金supported by Shandong Provincial Nat-ural Science Foundation(ZR2024ZD30)the National Natural Science Foundation of China(Nos.22325302 and 22403100).
文摘Accurate evaluation of elec-tron correlations is essential for the reliable quantitative de-scription of electronic struc-tures in strongly correlated sys-tems,including bond-dissociat-ing molecules,polyradicals,large conjugated molecules,and transition metal complex-es.To provide a user-friendly tool for studying such challeng-ing systems,our team developed Kylin 1.0[J.Comput.Chem.44,1316(2023)],an ab initio quantum chemistry program designed for efficient density matrix renormalization group(DMRG)and post-DMRG methods,enabling high-accuracy calculations with large active spaces.We have now further advanced the software with the release of Kylin 1.3,featuring optimized DMRG algorithms and an improved tensor contraction scheme in the diagonaliza-tion step.Benchmark calculations on the Mn_(4)CaO_(5)cluster demonstrate a remarkable speed-up of up to 16 fater than Kylin 1.0.Moreover,a more user-friendly and efficient algorithm[J.Chem.Theory Comput.17,3414(2021)]for sampling configurations from DMRG wavefunc-tion is implemented as well.Additionally,we have also implemented a spin-adapted version of the externally contracted multi-reference configuration interaction(EC-MRCI)method[J.Phys.Chem.A 128,958(2024)],further enhancing the program’s efficiency and accuracy for electron correlation calculations.
基金the National Social Science Foundation of China(No.21BTQ106),the Natural Science Foundation of Beijing(No.7222187),and the Key Project of Innovation Cultivation Fund of the Seventh Medical Center of PLA General Hospital(No.qzx-2023-1)。
文摘Behavioral scoring based on clinical observations remains the gold standard for screening,diagnosing,and evaluating infantile epileptic spasm syndrome(IESS).The accurate identification of seizures is crucial for clinical diagnosis and assessment.In this study,we propose an innovative seizure detection method based on video feature recognition of patient spasms.To capture the temporal characteristics of the spasm behavior presented in the videos effectively,we incorporate asymmetric convolutions and convolution–batch normalization–ReLU(CBR)modules.Specifically within the 3D-ResNet residual blocks,we split the larger convolutional kernels into two asymmetric 3D convolutional kernels.These kernels are connected in series to enhance the ability of the convolutional layers to extract key local features,both horizontally and vertically.In addition,we introduce a 3D convolutional block attention module to enhance the spatial correlations between video frame channels efficiently.To improve the generalization ability,we design a composite loss function that combines cross-entropy loss with triplet loss to balance the classification and similarity requirements.We train and evaluate our method using the PLA IESS-VIDEO dataset,achieving an average seizure recognition accuracy of 90.59%,precision of 90.94%,and recall of 87.64%.To validate its generalization capability further,we conducted external validation using six different patient monitoring videos compared with assessments by six human experts from various medical centers.The final test results demonstrate that our method achieved a recall of 0.6476,surpassing the average level achieved by human experts(0.5595),while attaining a high F1-score of 0.7219.These findings have substantial significance for the long-term assessment of patients with IESS.
基金This work is supported by the National Natural Science Youth Fund of China granted by No.61901452 and Innovative Project of ICT/CAS granted by No.20196110
文摘With the proliferation of the Internet of Things(IoT),various services are emerging with totally different features and requirements,which cannot be supported by the current fifth generation of mobile cellular networks(5G).The future sixth generation of mobile cellular networks(6G)is expected to have the capability to support new and unknown services with changing requirements.Hence,in addition to enhancing its capability by 10–100 times compared with 5G,6G should also be intelligent and open to adapt to the ever-changing services in the IoT,which requires a convergence of Communication,Computing and Caching(3C).Based on the analysis of the requirements of new services for 6G,this paper identifies key enabling technologies for an intelligent and open 6G network,all featured with 3C convergence.These technologies cover fundamental and emerging topics,including 3C-based spectrum management,radio channel construction,delay-aware transmission,wireless distributed computing,and network self-evolution.From the detailed analysis of these 3C-based technologies presented in this paper,we can see that although they are promising to enable an intelligent and open 6G,more efforts are needed to realize the expected 6G network.
基金Supported by the National Program on Key Basic Re-search Project of China (G1999035801)
文摘With analysis of limitations Trusted Computing Group （TCG） has encountered, we argued that virtual machine monitor （VMM） is the appropriate architecture for implementing TCG specification. Putting together the VMM architecture, TCG hardware and application-oriented ＂thin＂ virtual machine （VM）, Trusted VMM-based security architecture is present in this paper with the character of reduced and distributed trusted computing base （TCB）. It provides isolation and integrity guarantees based on which general security requirements can be satisfied.
基金China State Railway Group Co.,Ltd(No.K2023X030)China Academy of Railway Sciences Corporation Limited(No.2021YJ017).
文摘Purpose–Revenue management(RM)is a significant technique to improve revenue with limited resources.With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China,it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.Design/methodology/approach–This paper proposes the theory and framework of generalized RM of railway passenger transport(RMRPT),and the thoughts and methods of the main techniques in RMRPT,involving demand forecasting,line planning,inventory control,pricing strategies and information systems,are all studied and elaborated.The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT.The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.Findings–The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.Originality/value–The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.
基金The Natural Science Foundation of Henan Province(No.232300421097)the Program for Science&Technology Innovation Talents in Universities of Henan Province(No.23HASTIT019,24HASTIT038)+2 种基金the China Postdoctoral Science Foundation(No.2023T160596,2023M733251)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2023D11)the Song Shan Laboratory Foundation(No.YYJC022022003)。
文摘In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)network.We first derive the secure transmission rate based on the mMIMO under imperfect channel state information.Based on this,the SCE maximization problem is formulated by jointly optimizing the local computation frequency,the offloading time,the downloading time,the users and the base station transmit power.Due to its difficulty to directly solve the formulated problem,we first transform the fractional objective function into the subtractive form one via the dinkelbach method.Next,the original problem is transformed into a convex one by applying the successive convex approximation technique,and an iteration algorithm is proposed to obtain the solutions.Finally,the stimulations are conducted to show that the performance of the proposed schemes is superior to that of the other schemes.
文摘In current research on task offloading and resource scheduling in vehicular networks,vehicles are commonly assumed to maintain constant speed or relatively stationary states,and the impact of speed variations on task offloading is often overlooked.It is frequently assumed that vehicles can be accurately modeled during actual motion processes.However,in vehicular dynamic environments,both the tasks generated by the vehicles and the vehicles’surroundings are constantly changing,making it difficult to achieve real-time modeling for actual dynamic vehicular network scenarios.Taking into account the actual dynamic vehicular scenarios,this paper considers the real-time non-uniform movement of vehicles and proposes a vehicular task dynamic offloading and scheduling algorithm for single-task multi-vehicle vehicular network scenarios,attempting to solve the dynamic decision-making problem in task offloading process.The optimization objective is to minimize the average task completion time,which is formulated as a multi-constrained non-linear programming problem.Due to the mobility of vehicles,a constraint model is applied in the decision-making process to dynamically determine whether the communication range is sufficient for task offloading and transmission.Finally,the proposed vehicular task dynamic offloading and scheduling algorithm based on muti-agent deep deterministic policy gradient(MADDPG)is applied to solve the optimal solution of the optimization problem.Simulation results show that the algorithm proposed in this paper is able to achieve lower latency task computation offloading.Meanwhile,the average task completion time of the proposed algorithm in this paper can be improved by 7.6%compared to the performance of the MADDPG scheme and 51.1%compared to the performance of deep deterministic policy gradient(DDPG).
基金supported by the National Key R&D Program of China(No.2020YFF0304101).
文摘Purpose–With the yearly increase of mileage and passenger volume in China’s high-speed railway,the problems of traditional paper railway tickets have become increasingly prominent,including complexity of business handling process,low efficiency of ticket inspection and high cost of usage and management.This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally.The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.Design/methodology/approach–Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system,the grid-oriented passenger service record(PSR)data storage model,efficient access to massive PSR data under high concurrency condition,the linkage between face recognition service platforms and various terminals in large scenarios,and two-factor authentication of the e-ticket identification code based on the key and the user identity information.Focusing on the key technologies and architecture the of existing ticketing system,multiple service resources are expanded and developed such as electronic ticket clusters,PSR clusters,face recognition clusters and electronic ticket identification code clusters.Findings–The proportion of paper ticket printed has dropped to 20%,saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide.The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds,significantly improving the efficiency of passenger transport organization.Meanwhile,problems of paper ticket counterfeiting,reselling and loss have been generally eliminated.Originality/value–E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.
基金National Natural Science Foundation of China High Speed Rail Joint Fund(U2268217)。
文摘Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.
文摘Prognostics and Health Management(PHM)technology is a critical component in establishing a precision-based Operation and Management(O&M)system for EMUs.This technology is essential for enhancing life cycle management and advancing manufacturing and repair processes of EMUs.Through the analysis on O&M requirements of EMUs,this paper proposes the intelligent O&M objectives of EMUs based on PHM technology,as well as the system design architecture incorporating functions such as condition monitoring,fault prediction,health assessment,decision support and O&M analysis;and constructs a PHM-based standardized system for intelligent O&M of EMUs.The study also explores aspects such as the data lifecycle of EMUs,the development of PHM models,high-frequency streaming computation methods,unified management of heterogeneous models,and PHM-driven O&M production organization technologies.The PHM-based intelligent O&M system has been implemented across the railway network,achieving seamless information flow throughout the entire process of monitoring,decision-making and execution.
基金supported by the CAS Project for Young Scientists in Basic Research under Grant YSBR-035Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2.
文摘In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.
