This paper concerns the exponential attitude-orbit coordinated control problems for gravitational-wave detection formation spacecraft systems.Notably,the large-scale communication delays resulting from oversized inter...This paper concerns the exponential attitude-orbit coordinated control problems for gravitational-wave detection formation spacecraft systems.Notably,the large-scale communication delays resulting from oversized inter-satellite distance of space-based laser interferometers are first modeled.Subject to the delayed communication behaviors,a new delay-dependent attitude-orbit coordinated controller is designed.Moreover,by reconstructing the less conservative Lyapunov-Krasovskii functional and free-weight matrices,sufficient criteria are derived to ensure the exponential stability of the closed-loop relative translation and attitude error system.Finally,a simulation example is employed to illustrate the numerical validity of the proposed controller for in-orbit detection missions.展开更多
Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,th...Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.展开更多
Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commo...Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commonly used in various applications such as environmental monitoring,surveillance,healthcare,agriculture,and industrial automation.Despite the benefits of WSN,energy efficiency remains a challenging problem that needs to be addressed.Clustering and routing can be considered effective solutions to accomplish energy efficiency in WSNs.Recent studies have reported that metaheuristic algorithms can be applied to optimize cluster formation and routing decisions.This study introduces a new Northern Goshawk Optimization with boosted coati optimization algorithm for cluster-based routing(NGOBCO-CBR)method for WSN.The proposed NGOBCO-CBR method resolves the hot spot problem,uneven load balancing,and energy consumption in WSN.The NGOBCO-CBR technique comprises two major processes such as NGO based clustering and BCO-based routing.In the initial phase,the NGObased clustering method is designed for cluster head(CH)selection and cluster construction using five input variables such as residual energy(RE),node proximity,load balancing,network average energy,and distance to BS(DBS).Besides,the NGOBCO-CBR technique applies the BCO algorithm for the optimum selection of routes to BS.The experimental results of the NGOBCOCBR technique are studied under different scenarios,and the obtained results showcased the improved efficiency of the NGOBCO-CBR technique over recent approaches in terms of different measures.展开更多
This paper studies the problem of jamming decision-making for dynamic multiple communication links in wireless communication networks(WCNs).We propose a novel jamming channel allocation and power decision-making(JCAPD...This paper studies the problem of jamming decision-making for dynamic multiple communication links in wireless communication networks(WCNs).We propose a novel jamming channel allocation and power decision-making(JCAPD)approach based on multi-agent deep reinforcement learning(MADRL).In high-dynamic and multi-target aviation communication environments,the rapid changes in channels make it difficult for sensors to accurately capture instantaneous channel state information.This poses a challenge to make centralized jamming decisions with single-agent deep reinforcement learning(DRL)approaches.In response,we design a distributed multi-agent decision architecture(DMADA).We formulate multi-jammer resource allocation as a multiagent Markov decision process(MDP)and propose a fingerprint-based double deep Q-Network(FBDDQN)algorithm for solving it.Each jammer functions as an agent that interacts with the environment in this framework.Through the design of a reasonable reward and training mechanism,our approach enables jammers to achieve distributed cooperation,significantly improving the jamming success rate while considering jamming power cost,and reducing the transmission rate of links.Our experimental results show the FBDDQN algorithm is superior to the baseline methods.展开更多
It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the ...It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.展开更多
The dynamic behaviors of a large-scale ring neural network with a triangular coupling structure are investigated.The characteristic equation of the high-dimensional system using Coate’s flow graph method is calculate...The dynamic behaviors of a large-scale ring neural network with a triangular coupling structure are investigated.The characteristic equation of the high-dimensional system using Coate’s flow graph method is calculated.Time delay is selected as the bifurcation parameter,and sufficient conditions for stability and Hopf bifurcation are derived.It is found that the connection coefficient and time delay play a crucial role in the dynamic behaviors of the model.Furthermore,a phase diagram of multiple equilibrium points with one saddle point and two stable nodes is presented.Finally,the effectiveness of the theory is verified through simulation results.展开更多
Meteor Burst Communication(MBC),a niche yet revolutionary wireless communication paradigm,exploits the transient ionized trails generated by meteors ablating in Earth’s atmosphere to enable sporadic yet resilient lon...Meteor Burst Communication(MBC),a niche yet revolutionary wireless communication paradigm,exploits the transient ionized trails generated by meteors ablating in Earth’s atmosphere to enable sporadic yet resilient long-distance radio links.Known for its exceptional resilience,robustness,and sustained connectivity,MBC holds significant promise for applications in emergency communications,remote area connectivity,military/defense systems,and environmental monitoring.However,the scientific exploration and application of MBC have long been highly challenging.In particular,under the combined influence of multiple physical field factors,the channel experiences superimposed multiple random fading effects,exhibiting bursty,highly time-varying,and strongly random characteristics.This persistent technical challenge has resulted in the absence of a practical statistical channel model for MBC to date.展开更多
As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent...As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent QKD protocols,and they commonly rely on the deployment of single-protocol trusted relay chains for long reach.Driven by the evolution of QKD protocols,large-scale QKD networking is expected to migrate from a single-protocol to a multi-protocol paradigm,during which some useful evolutionary elements for the later stages of the quantum Internet may be incorporated.In this work,we delve into a pivotal technique for large-scale QKD networking,namely,multi-protocol relay chaining.A multi-protocol relay chain is established by connecting a set of trusted/untrusted relays relying on multiple QKD protocols between a pair of QKD nodes.The structures of diverse multi-protocol relay chains are described,based on which the associated model is formulated and the policies are defined for the deployment of multi-protocol relay chains.Furthermore,we propose three multi-protocol relay chaining heuristics.Numerical simulations indicate that the designed heuristics can effectively reduce the number of trusted relays deployed and enhance the average security level versus the commonly used single-protocol trusted relay chaining methods on backbone network topologies.展开更多
BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-...BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-injury and SA are poorly understood in depressed adolescents but likely relate to the structural abnormalities in brain regions.AIM To investigate structural network communication within large-scale brain networks in adolescents with depression.METHODS We constructed five distinct network communication models to evaluate structural network efficiency at the whole-brain level in adolescents with depression.Diffusion magnetic resonance imaging data were acquired from 32 healthy controls and 85 depressed adolescents,including 17 depressed adolescents without SA or NSSI(major depressive disorder group),27 depressed adolescents with NSSI but no SA(NSSI group),and 41 depressed adolescents with SA and NSSI(NSSI+SA group).RESULTS Significant differences in structural network communication were observed across the four groups,involving spatially widespread brain regions,particularly encompassing cortico-cortical connections(e.g.,dorsal posterior cingulate gyrus and the right ventral posterior cingulate gyrus;connections based on precentral gyrus)and cortico-subcortical circuits(e.g.,the nucleus accumbens-frontal circuit).In addition,we examined whether compromised communication efficiency was linked to clinical symptoms in the depressed adolescents.We observed significant correlations between network communication efficiencies and clinical scale scores derived from depressed adolescents with NSSI and SA.CONCLUSION This study provides evidence of structural network communication differences in depressed adolescents with NSSI and SA,highlighting impaired neuroanatomical communication efficiency as a potential contributor to their symptoms.These findings offer new insights into the pathophysiological mechanisms underlying the comorbidity of NSSI and SA in adolescent depression.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
With the rapid development of network technologies,a large number of deployed edge devices and information systems generate massive amounts of data which provide good support for the advancement of data-driven intelli...With the rapid development of network technologies,a large number of deployed edge devices and information systems generate massive amounts of data which provide good support for the advancement of data-driven intelligent models.However,these data often contain sensitive information of users.Federated learning(FL),as a privacy preservation machine learning setting,allows users to obtain a well-trained model without sending the privacy-sensitive local data to the central server.Despite the promising prospect of FL,several significant research challenges need to be addressed before widespread deployment,including network resource allocation,model security,model convergence,etc.In this paper,we first provide a brief survey on some of these works that have been done on FL and discuss the motivations of the Communication Networks(CNs)and FL to mutually enable each other.We analyze the support of network technologies for FL,which requires frequent communication and emphasizes security,as well as the studies on the intelligence of many network scenarios and the improvement of network performance and security by the methods based on FL.At last,some challenges and broader perspectives are explored.展开更多
Quantum communication networks,such as quantum key distribution(QKD)networks,typically employ the measurement-resend mechanism between two users using quantum communication devices based on different quantum encoding ...Quantum communication networks,such as quantum key distribution(QKD)networks,typically employ the measurement-resend mechanism between two users using quantum communication devices based on different quantum encoding types.To achieve direct communication between the devices with different quantum encoding types,in this paper,we propose encoding conversion schemes between the polarization bases(rectilinear,diagonal and circular bases)and the time-bin phase bases(two phase bases and time-bin basis)and design the quantum encoding converters.The theoretical analysis of the encoding conversion schemes is given in detail,and the basis correspondence of encoding conversion and the property of bit flip are revealed.The conversion relationship between polarization bases and time-bin phase bases can be easily selected by controlling a phase shifter.Since no optical switches are used in our scheme,the converter can be operated with high speed.The converters can also be modularized,which may be utilized to realize miniaturization in the future.展开更多
Symmetric encryption algorithms learned by the previous proposed end-to-end adversarial network encryption communication systems are deterministic.With the same key and same plaintext,the deterministic algorithm will ...Symmetric encryption algorithms learned by the previous proposed end-to-end adversarial network encryption communication systems are deterministic.With the same key and same plaintext,the deterministic algorithm will lead to the same ciphertext.This means that the key in the deterministic encryption algorithm can only be used once,thus the encryption is not practical.To solve this problem,a nondeterministic symmetric encryption end-to-end communication system based on generative adversarial networks is proposed.We design a nonce-based adversarial neural network model,where a“nonce”standing for“number used only once”is passed to communication participants,and does not need to be secret.Moreover,we optimize the network structure through adding Batch Normalization(BN)to the CNNs(Convolutional Neural Networks),selecting the appropriate activation functions,and setting appropriate CNNs parameters.Results of experiments and analysis show that our system can achieve non-deterministic symmetric encryption,where Alice encrypting the same plaintext with the key twice will generate different ciphertexts,and Bob can decrypt all these different ciphertexts of the same plaintext to the correct plaintext.And our proposed system has fast convergence and the correct rate of decryption when the plaintext length is 256 or even longer.展开更多
With the widespread application of com-munication technology in the non-terrestrial network(NTN),the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized.Consequ...With the widespread application of com-munication technology in the non-terrestrial network(NTN),the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized.Consequently,safeguarding com-munication information in the NTN has emerged as a critical challenge.To address this issue,we pro-pose a beamforming and horizontal trajectory joint op-timization method for unmanned aerial vehicle(UAV)covert communications in the NTN.First,we formu-late an optimization problem that considers constraints such as the transmitting power and the distance.More-over,we employ the integrated communication and jamming(ICAJ)signal as Alice’s transmitting signal,further protecting the content of communication in-formation.Next,we construct two subproblems,and we propose an alternate optimization(AO)algorithm based on quadratic transform and penalty term method to solve the proposed two subproblems.Simulation re-sults demonstrate that the proposed method is effective and has better performance than benchmarks.展开更多
Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so...Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present some sufficient conditions for the exponential stability of a particular category of switched systems.展开更多
When tracking a unmanned aerial vehicle(UAV)in complex backgrounds,environmen-tal noise and clutter often obscure it.Traditional radar target tracking algorithms face multiple lim-itations when tracking a UAV,includin...When tracking a unmanned aerial vehicle(UAV)in complex backgrounds,environmen-tal noise and clutter often obscure it.Traditional radar target tracking algorithms face multiple lim-itations when tracking a UAV,including high vulnerability to target occlusion and shape variations,as well as pronounced false alarms and missed detections in low signal-to-noise ratio(SNR)envi-ronments.To address these issues,this paper proposes a UAV detection and tracking algorithm based on a low-frequency communication network.The accuracy and effectiveness of the algorithm are validated through simulation experiments using field-measured point cloud data.Additionally,the key parameters of the algorithm are optimized through a process of selection and comparison,thereby improving the algorithm's precision.The experimental results show that the improved algo-rithm can significantly enhance the detection and tracking performance of the UAV under high clutter density conditions,effectively reduce the false alarm rate and markedly improve overall tracking performance metrics.展开更多
As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerou...As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.展开更多
Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effect...Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.展开更多
A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Ea...A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Earth’s population leads to an uneven service volume distribution of access service.Moreover,the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas.To enhance the forwarding capability of satellite networks,we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall.Then,we propose a multi-region cooperative traffic scheduling algorithm.The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding,significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding.This algorithm can utilize all the global satellite resources and improve the utilization of network resources.We model the cooperative multi-region scheduling of large-scale LEO satellites.Based on the model,we build a system testbed using OMNET++to compare the proposed method with existing techniques.The simulations show that our proposed method can reduce the packet loss probability by 30%and improve the resource utilization ratio by 3.69%.展开更多
Generative artificial intelligence(AI),as an emerging paradigm in content generation,has demonstrated its great potentials in creating high-fidelity data including images,texts,and videos.Nowadays wireless networks an...Generative artificial intelligence(AI),as an emerging paradigm in content generation,has demonstrated its great potentials in creating high-fidelity data including images,texts,and videos.Nowadays wireless networks and applications have been rapidly evolving from achieving“connected things”to embracing“connected intelligence”.展开更多
基金supported by the Na⁃tional Key R&D Program of China(No.2022YFC2204800)the Graduate Student Independent Exploration and Innovation Program of Central South University(No.2024ZZTS 0767).
文摘This paper concerns the exponential attitude-orbit coordinated control problems for gravitational-wave detection formation spacecraft systems.Notably,the large-scale communication delays resulting from oversized inter-satellite distance of space-based laser interferometers are first modeled.Subject to the delayed communication behaviors,a new delay-dependent attitude-orbit coordinated controller is designed.Moreover,by reconstructing the less conservative Lyapunov-Krasovskii functional and free-weight matrices,sufficient criteria are derived to ensure the exponential stability of the closed-loop relative translation and attitude error system.Finally,a simulation example is employed to illustrate the numerical validity of the proposed controller for in-orbit detection missions.
基金supported by the Science and Technology Project of the State Grid Corporation of China(5400-202255158A-1-1-ZN).
文摘Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.
文摘Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commonly used in various applications such as environmental monitoring,surveillance,healthcare,agriculture,and industrial automation.Despite the benefits of WSN,energy efficiency remains a challenging problem that needs to be addressed.Clustering and routing can be considered effective solutions to accomplish energy efficiency in WSNs.Recent studies have reported that metaheuristic algorithms can be applied to optimize cluster formation and routing decisions.This study introduces a new Northern Goshawk Optimization with boosted coati optimization algorithm for cluster-based routing(NGOBCO-CBR)method for WSN.The proposed NGOBCO-CBR method resolves the hot spot problem,uneven load balancing,and energy consumption in WSN.The NGOBCO-CBR technique comprises two major processes such as NGO based clustering and BCO-based routing.In the initial phase,the NGObased clustering method is designed for cluster head(CH)selection and cluster construction using five input variables such as residual energy(RE),node proximity,load balancing,network average energy,and distance to BS(DBS).Besides,the NGOBCO-CBR technique applies the BCO algorithm for the optimum selection of routes to BS.The experimental results of the NGOBCOCBR technique are studied under different scenarios,and the obtained results showcased the improved efficiency of the NGOBCO-CBR technique over recent approaches in terms of different measures.
基金supported in part by the National Natural Science Foundation of China(No.61906156).
文摘This paper studies the problem of jamming decision-making for dynamic multiple communication links in wireless communication networks(WCNs).We propose a novel jamming channel allocation and power decision-making(JCAPD)approach based on multi-agent deep reinforcement learning(MADRL).In high-dynamic and multi-target aviation communication environments,the rapid changes in channels make it difficult for sensors to accurately capture instantaneous channel state information.This poses a challenge to make centralized jamming decisions with single-agent deep reinforcement learning(DRL)approaches.In response,we design a distributed multi-agent decision architecture(DMADA).We formulate multi-jammer resource allocation as a multiagent Markov decision process(MDP)and propose a fingerprint-based double deep Q-Network(FBDDQN)algorithm for solving it.Each jammer functions as an agent that interacts with the environment in this framework.Through the design of a reasonable reward and training mechanism,our approach enables jammers to achieve distributed cooperation,significantly improving the jamming success rate while considering jamming power cost,and reducing the transmission rate of links.Our experimental results show the FBDDQN algorithm is superior to the baseline methods.
基金supported by the Fundamental Research Funds for the Central Universities(Grant Nos.lzujbky-2021-62 and lzujbky-2024-jdzx06)the National Natural Science Foundation of China(Grant No.12247101)+1 种基金the Natural Science Foundation of Gansu Province,China(Grant Nos.22JR5RA389 and 23JRRA1740)the‘111 Center’Fund(Grant No.B20063).
文摘It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.
基金Supported by Natural Science Foundation of Shandong Province of China(Grant Nos.ZR2020MF080 and ZR2020MF065).
文摘The dynamic behaviors of a large-scale ring neural network with a triangular coupling structure are investigated.The characteristic equation of the high-dimensional system using Coate’s flow graph method is calculated.Time delay is selected as the bifurcation parameter,and sufficient conditions for stability and Hopf bifurcation are derived.It is found that the connection coefficient and time delay play a crucial role in the dynamic behaviors of the model.Furthermore,a phase diagram of multiple equilibrium points with one saddle point and two stable nodes is presented.Finally,the effectiveness of the theory is verified through simulation results.
文摘Meteor Burst Communication(MBC),a niche yet revolutionary wireless communication paradigm,exploits the transient ionized trails generated by meteors ablating in Earth’s atmosphere to enable sporadic yet resilient long-distance radio links.Known for its exceptional resilience,robustness,and sustained connectivity,MBC holds significant promise for applications in emergency communications,remote area connectivity,military/defense systems,and environmental monitoring.However,the scientific exploration and application of MBC have long been highly challenging.In particular,under the combined influence of multiple physical field factors,the channel experiences superimposed multiple random fading effects,exhibiting bursty,highly time-varying,and strongly random characteristics.This persistent technical challenge has resulted in the absence of a practical statistical channel model for MBC to date.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62201276,62350001,U22B2026,and 62471248)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300701)+1 种基金the Key R&D Program(Industry Foresight and Key Core Technologies)of Jiangsu Province(Grant No.BE2022071)Natural Science Research of Jiangsu Higher Education Institutions of China(Grant No.22KJB510007)。
文摘As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent QKD protocols,and they commonly rely on the deployment of single-protocol trusted relay chains for long reach.Driven by the evolution of QKD protocols,large-scale QKD networking is expected to migrate from a single-protocol to a multi-protocol paradigm,during which some useful evolutionary elements for the later stages of the quantum Internet may be incorporated.In this work,we delve into a pivotal technique for large-scale QKD networking,namely,multi-protocol relay chaining.A multi-protocol relay chain is established by connecting a set of trusted/untrusted relays relying on multiple QKD protocols between a pair of QKD nodes.The structures of diverse multi-protocol relay chains are described,based on which the associated model is formulated and the policies are defined for the deployment of multi-protocol relay chains.Furthermore,we propose three multi-protocol relay chaining heuristics.Numerical simulations indicate that the designed heuristics can effectively reduce the number of trusted relays deployed and enhance the average security level versus the commonly used single-protocol trusted relay chaining methods on backbone network topologies.
基金Supported by the National Natural Science Foundation of China,No.81871081 and No.62201265the Fundamental Research Funds for the Central Universities,No.NJ2024029-14the Talent Support Programs of Wuxi Health Commission,No.BJ2023085,No.FZXK2021012,and No.M202358.
文摘BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-injury and SA are poorly understood in depressed adolescents but likely relate to the structural abnormalities in brain regions.AIM To investigate structural network communication within large-scale brain networks in adolescents with depression.METHODS We constructed five distinct network communication models to evaluate structural network efficiency at the whole-brain level in adolescents with depression.Diffusion magnetic resonance imaging data were acquired from 32 healthy controls and 85 depressed adolescents,including 17 depressed adolescents without SA or NSSI(major depressive disorder group),27 depressed adolescents with NSSI but no SA(NSSI group),and 41 depressed adolescents with SA and NSSI(NSSI+SA group).RESULTS Significant differences in structural network communication were observed across the four groups,involving spatially widespread brain regions,particularly encompassing cortico-cortical connections(e.g.,dorsal posterior cingulate gyrus and the right ventral posterior cingulate gyrus;connections based on precentral gyrus)and cortico-subcortical circuits(e.g.,the nucleus accumbens-frontal circuit).In addition,we examined whether compromised communication efficiency was linked to clinical symptoms in the depressed adolescents.We observed significant correlations between network communication efficiencies and clinical scale scores derived from depressed adolescents with NSSI and SA.CONCLUSION This study provides evidence of structural network communication differences in depressed adolescents with NSSI and SA,highlighting impaired neuroanatomical communication efficiency as a potential contributor to their symptoms.These findings offer new insights into the pathophysiological mechanisms underlying the comorbidity of NSSI and SA in adolescent depression.
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 National Key Research and Development Program of China(No.2023YFB2704200)Beijing Natural Science Foundation(No.4254064).
文摘With the rapid development of network technologies,a large number of deployed edge devices and information systems generate massive amounts of data which provide good support for the advancement of data-driven intelligent models.However,these data often contain sensitive information of users.Federated learning(FL),as a privacy preservation machine learning setting,allows users to obtain a well-trained model without sending the privacy-sensitive local data to the central server.Despite the promising prospect of FL,several significant research challenges need to be addressed before widespread deployment,including network resource allocation,model security,model convergence,etc.In this paper,we first provide a brief survey on some of these works that have been done on FL and discuss the motivations of the Communication Networks(CNs)and FL to mutually enable each other.We analyze the support of network technologies for FL,which requires frequent communication and emphasizes security,as well as the studies on the intelligence of many network scenarios and the improvement of network performance and security by the methods based on FL.At last,some challenges and broader perspectives are explored.
基金supported by the National Natural Science Foundation of China(Grant No.62001440).
文摘Quantum communication networks,such as quantum key distribution(QKD)networks,typically employ the measurement-resend mechanism between two users using quantum communication devices based on different quantum encoding types.To achieve direct communication between the devices with different quantum encoding types,in this paper,we propose encoding conversion schemes between the polarization bases(rectilinear,diagonal and circular bases)and the time-bin phase bases(two phase bases and time-bin basis)and design the quantum encoding converters.The theoretical analysis of the encoding conversion schemes is given in detail,and the basis correspondence of encoding conversion and the property of bit flip are revealed.The conversion relationship between polarization bases and time-bin phase bases can be easily selected by controlling a phase shifter.Since no optical switches are used in our scheme,the converter can be operated with high speed.The converters can also be modularized,which may be utilized to realize miniaturization in the future.
基金supported by The National Defense Innovation Project(No.ZZKY20222411)Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-546).
文摘Symmetric encryption algorithms learned by the previous proposed end-to-end adversarial network encryption communication systems are deterministic.With the same key and same plaintext,the deterministic algorithm will lead to the same ciphertext.This means that the key in the deterministic encryption algorithm can only be used once,thus the encryption is not practical.To solve this problem,a nondeterministic symmetric encryption end-to-end communication system based on generative adversarial networks is proposed.We design a nonce-based adversarial neural network model,where a“nonce”standing for“number used only once”is passed to communication participants,and does not need to be secret.Moreover,we optimize the network structure through adding Batch Normalization(BN)to the CNNs(Convolutional Neural Networks),selecting the appropriate activation functions,and setting appropriate CNNs parameters.Results of experiments and analysis show that our system can achieve non-deterministic symmetric encryption,where Alice encrypting the same plaintext with the key twice will generate different ciphertexts,and Bob can decrypt all these different ciphertexts of the same plaintext to the correct plaintext.And our proposed system has fast convergence and the correct rate of decryption when the plaintext length is 256 or even longer.
基金supported in part by the National Natural Science Foundation of China under Grant U2441250 and 62231027in part by Natural Science Basic Research Programof Shaanxi under Grant 2024JC-JCQN-63+2 种基金in part by InnovationCapability Support Program of Shaanxi under Grant2024RS-CXTD-01in part by New Technology Research University Cooperation Project under Grant SKX242010031in part by the FundamentalResearch Funds for the Central Universities and theInnovation Fund of Xidian University under GrantYJSJ25007.
文摘With the widespread application of com-munication technology in the non-terrestrial network(NTN),the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized.Consequently,safeguarding com-munication information in the NTN has emerged as a critical challenge.To address this issue,we pro-pose a beamforming and horizontal trajectory joint op-timization method for unmanned aerial vehicle(UAV)covert communications in the NTN.First,we formu-late an optimization problem that considers constraints such as the transmitting power and the distance.More-over,we employ the integrated communication and jamming(ICAJ)signal as Alice’s transmitting signal,further protecting the content of communication in-formation.Next,we construct two subproblems,and we propose an alternate optimization(AO)algorithm based on quadratic transform and penalty term method to solve the proposed two subproblems.Simulation re-sults demonstrate that the proposed method is effective and has better performance than benchmarks.
基金supported in part by the National Natural Science Foundation of China(62273255,62350003,62088101)the Shanghai Science and Technology Cooperation Project(22510712000,21550760900)+1 种基金the Shanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Fundamental Research Funds for the Central Universities
文摘Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present some sufficient conditions for the exponential stability of a particular category of switched systems.
基金supported in part by National Natural Science Founda-tion of China(No.62372284)in part by Shanghai Nat-ural Science Foundation(No.24ZR1421800).
文摘When tracking a unmanned aerial vehicle(UAV)in complex backgrounds,environmen-tal noise and clutter often obscure it.Traditional radar target tracking algorithms face multiple lim-itations when tracking a UAV,including high vulnerability to target occlusion and shape variations,as well as pronounced false alarms and missed detections in low signal-to-noise ratio(SNR)envi-ronments.To address these issues,this paper proposes a UAV detection and tracking algorithm based on a low-frequency communication network.The accuracy and effectiveness of the algorithm are validated through simulation experiments using field-measured point cloud data.Additionally,the key parameters of the algorithm are optimized through a process of selection and comparison,thereby improving the algorithm's precision.The experimental results show that the improved algo-rithm can significantly enhance the detection and tracking performance of the UAV under high clutter density conditions,effectively reduce the false alarm rate and markedly improve overall tracking performance metrics.
基金This work was supported by National Key R&D Program of China under Grant 2018YFB1800802in part by the National Natural Science Foundation of China under Grant No.61771488,No.61631020 and No.61827801+1 种基金in part by State Key Laboratory of Air Traffic Management System and Technology under Grant No.SKLATM201808in part by Postgraduate Research and Practice Innovation Program of Jiangsu Province under No.KYCX190188.
文摘As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.
文摘Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.
基金This work was supported by the National Key R&D Program of China(2021YFB2900604).
文摘A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Earth’s population leads to an uneven service volume distribution of access service.Moreover,the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas.To enhance the forwarding capability of satellite networks,we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall.Then,we propose a multi-region cooperative traffic scheduling algorithm.The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding,significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding.This algorithm can utilize all the global satellite resources and improve the utilization of network resources.We model the cooperative multi-region scheduling of large-scale LEO satellites.Based on the model,we build a system testbed using OMNET++to compare the proposed method with existing techniques.The simulations show that our proposed method can reduce the packet loss probability by 30%and improve the resource utilization ratio by 3.69%.
文摘Generative artificial intelligence(AI),as an emerging paradigm in content generation,has demonstrated its great potentials in creating high-fidelity data including images,texts,and videos.Nowadays wireless networks and applications have been rapidly evolving from achieving“connected things”to embracing“connected intelligence”.
