This paper focuses on the research of MPLS VPN technology in the ocean information communication network.Through the analysis of the current situation of the ocean information communication network,the architecture de...This paper focuses on the research of MPLS VPN technology in the ocean information communication network.Through the analysis of the current situation of the ocean information communication network,the architecture design of MPLS VPN technology in the ocean information communication network and the important role of RD value and RT value in the VPN instances,the matching strategies of import RT and export RT of different VPN instances are verified through experiments.展开更多
This paper proposes an efficient scheme for quantum communication between two atoms trapped in distant cavities which are connected by an optical fibre. During the operation, all the atomic system, the cavity modes an...This paper proposes an efficient scheme for quantum communication between two atoms trapped in distant cavities which are connected by an optical fibre. During the operation, all the atomic system, the cavity modes and the fibre are not excited. The quantum state is mediated by the vacuum fields. The idea can be used to realize quantum entanglement between two distant atoms via vacuum.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
In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disaster...In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disasters frequently damage terrestrial communication infrastructures,making the rapid deployment of emergency communication networks in affected areas critical in increasing rescue efficiency[2].展开更多
The emerging deployment of large-scale Low Earth Orbit(LEO)satellite constellations provides seamless global coverage.However,the increasing number of satellites also introduces significant security challenges,such as...The emerging deployment of large-scale Low Earth Orbit(LEO)satellite constellations provides seamless global coverage.However,the increasing number of satellites also introduces significant security challenges,such as eavesdropping and illegal communication behavior detection.This paper investigates covert wireless communication over uplink satellite-terrestrial network,focusing on scenarios with warden satellites.By accounting for shot noise generated by ambient signals from terrestrial interferers,the terrestrial transmitter Alice can effectively hide its signal from warden satellites.Leveraging stochastic geometry,the distributions of distances between transmitter and satellites are analyzed,enabling the assessment of uplink performance and interference within a satellite’s coverage area.Approximate expressions for detection error probability and transmission outage probability are derived.Based on the theoretical analysis,an optimal scheme is proposed to maximize covert throughput under the constraint of the average detection error probability of the most detrimental warden satellite.Extensive Monte Carlo simulations experiments are conducted to validate the accuracy of analytical methods for evaluating covert performance.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
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
Communications system has a signifi-cant impact on both operational safety and logisti-cal efficiency within low-altitude drone logistics net-works.Aiming at providing a systematic investiga-tion of real-world communi...Communications system has a signifi-cant impact on both operational safety and logisti-cal efficiency within low-altitude drone logistics net-works.Aiming at providing a systematic investiga-tion of real-world communication requirements and challenges encountered in Meituan UAV’s daily oper-ations,this article first introduces the operational sce-narios within current drone logistics networks and an-alyzes the related communication requirements.Then,the current communication solution and its inherent bottlenecks are elaborated.Finally,this paper explores emerging technologies and examines their application prospects in drone logistics networks.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 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
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
High-Frequency(HF)communication is widely used for long-distance transmission in remote and disaster areas.However,the dynamic nature of the ionosphere and multipath propagation in the HF channel pose significant chal...High-Frequency(HF)communication is widely used for long-distance transmission in remote and disaster areas.However,the dynamic nature of the ionosphere and multipath propagation in the HF channel pose significant challenges to designing efficient and robust communication systems.In this paper,we propose a Fixed Station(FS)and frequency matching method,as well as a power allocation method,to improve the sum-rate of air-to-ground HF communication networks.We derive optimal power allocation among users that share the same frequency,based on which a modified water-filling algorithm is used to solve the power allocation problem in multi-user scenarios,while a low-complexity algorithm is proposed to solve the integer optimization problem of frequency-FS matching.Simulation results demonstrate that the proposed algorithm outperforms the naive algorithm,indicating its effectiveness.展开更多
Covert unmanned aerial vehicle(UAV)communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy(LAE).This paper investigates the system policy,trajectory des...Covert unmanned aerial vehicle(UAV)communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy(LAE).This paper investigates the system policy,trajectory design,and resource allocation for energy-efficient aerial networked systems with the aid of an integrated sensing and communications(ISAC)framework,in which multiple UAVs are employed to simultaneously conduct cooperative sensing and covert downlink transmissions to multiple ground users(GUs)in the presence of a mobile warden(Willie).Specifically,to improve the communication covertness,UAVs are strategically switched between jamming(JUAV)and information(IUAV)modes.Additionally,to cope with the mobility of Willie,an unscented Kalman filtering(UKF)-based method is employed to track and predict Willie’s location relying on the delay and Doppler measurements extracted from the ISAC echoes.Capitalizing on the predicted Willie’s location,a real-time energy efficiency(EE)maximization problem is formulated by jointly optimizing the JUAV selection strategy,IUAV-GU scheduling,communication/jamming power allocation,and UAV trajectories design.The formulation takes into account the communication covertness requirement and the maximum transmit power budget,leading to a mixed-integer non-convex fractional programming.To tackle this challenge,the alternating optimization(AO)approach is adopted,which decomposes the original problem into a series of sub-problems,allowing us to obtain an efficient sub-optimal solution.Simulation results demonstrate that the proposed scheme is capable of tracking Willie accurately and offering excellent system EE performance compared to various benchmark schemes adopting existing designs.展开更多
The increasing importance of terminal privacy in the Unmanned Aerial Vehicle(UAV)network has led to a growing recognition of the crucial role of authentication technology in UAV network security.However,traditional au...The increasing importance of terminal privacy in the Unmanned Aerial Vehicle(UAV)network has led to a growing recognition of the crucial role of authentication technology in UAV network security.However,traditional authentication approaches are vulnerable due to the transmission of identity information between UAVs and cryptographic paradigm management centers over a public channel.These vulnerabilities include brute-force attacks,single point of failure,and information leakage.Blockchain,as a decentralized distributed ledger with blockchain storage,tamper-proof,secure,and trustworthy features,can solve problems such as single-point-of-failure and trust issues,while the hidden communication in the physical layer can effectively resist information leakage and violent attacks.In this paper,we propose a lightweight UAV network authentication mechanism that leverages blockchain and covert communication,where the identity information is transmitted as covert tags carried by normal modulated signals.In addition,a weight-based Practical Byzantine Fault-Tolerant(wPBFT)consensus protocol is devised,where the weights are determined by the channel states of UAVs and the outcomes of past authentication scenarios.Simulation results demonstrate that the proposed mechanism outperforms traditional benchmarks in terms of security and robustness,particularly under conditions of low Signal-to-Noise Ratio(SNR)and short tag length.展开更多
Non-Orthogonal Multiple Access(NOMA)in Unmanned Aerial Vehicle(UAV)-assisted communications is a promising technique in future wireless networks.However,for UAV-assisted communication systems,secure and covert communi...Non-Orthogonal Multiple Access(NOMA)in Unmanned Aerial Vehicle(UAV)-assisted communications is a promising technique in future wireless networks.However,for UAV-assisted communication systems,secure and covert communication is crucial for maintaining confidentiality in battlefield environments.This study focuses on a novel two-way relaying system assisted by the UAV,leveraging Power Domain NOMA(PD-NOMA),trajectory design,and power allocation strategies to enhance secure communication rates.A PD-NOMA scheme is proposed for the half-duplex two-way UAV relay,utilizing the advantage of Air-to-Ground(A2G)channel.The covert communication scheme is proposed based on the proposed NOMA scheme.A method using permutation matrices is proposed to dynamically adjust the NOMA decoding order based on the UAV trajectory and communication power levels,to reduce complexity while ensuring information causality constraints.A low-interference jamming strategy is proposed for the system for covertness communication.Because of the non-convexity of the problem,the power allocation and trajectory design problem are solved with Difference of Convex(DC)programming and Successive Convex Approximation(SCA).The schemes of jointly designing the NOMA order,allocating the communication power,and designing the trajectory are proposed to maximize the minimum secure communication data rate.Simulation results show that the proposed NOMA-UAV secure communication schemes outperform the benchmarks of the conventional Orthogonal Multiple Access(OMA)method.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
With the rapid development of commercial communications,the research on Radar-Communication Coexistence(RCC)systems is becoming a hot spot.The resource allocation techniques play a crucial role in the RCC systems.A pe...With the rapid development of commercial communications,the research on Radar-Communication Coexistence(RCC)systems is becoming a hot spot.The resource allocation techniques play a crucial role in the RCC systems.A performance-driven Joint Radar-target and Communication-user Assignment,along with Power and Subchannel Allocation(JRCAPSA)strategy,is proposed for an RCC network.The optimization model aims to minimize the sum of weighted Bayesian Cramer-Rao Lower Bounds(BCRLBs)of target state estimates for radar purpose.This is subject to constraints such as the Communication Data Rate(CDR)for communication purpose,the total power budget in each RCC system,assignment relationships,and the number of available subchannels.Considering that such a problem falls into the realm of Mixed Integer Programming(MIP),a Three-stage Iteratively Augment-based Optimization Method(TIAOM)is developed.The Communication-User Assignment(CUA),Communication Subchannel Allocation(SCA),and Radar-Target Assignment(RTA)feasible solution domains are iteratively expanded based on their importance,leading to the efficient acquisition of a suboptimal solution.Simulation results show the outperformance of the proposed JRCAPSA strategy,compared to the other benchmarks and the OPTI toolbox.The results also imply that the Bayesian Cramer-Rao Lower Bound(BCRLB)is a more stringent optimization metric for the achieved Mean Square Error(MSE),compared to Mutual Information(MI)and Signal-to-Interference-Noise Ratio(SINR).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
Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing de...Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing details about the speaker’s goals and desires, as well as their internal condition. Certain vocal characteristics reveal the speaker’s mood, intention, and motivation, while word study assists the speaker’s demand to be understood. Voice emotion recognition has become an essential component of modern HCC networks. Integrating findings from the various disciplines involved in identifying vocal emotions is also challenging. Many sound analysis techniques were developed in the past. Learning about the development of artificial intelligence (AI), and especially Deep Learning (DL) technology, research incorporating real data is becoming increasingly common these days. Thus, this research presents a novel selfish herd optimization-tuned long/short-term memory (SHO-LSTM) strategy to identify vocal emotions in human communication. The RAVDESS public dataset is used to train the suggested SHO-LSTM technique. Mel-frequency cepstral coefficient (MFCC) and wiener filter (WF) techniques are used, respectively, to remove noise and extract features from the data. LSTM and SHO are applied to the extracted data to optimize the LSTM network’s parameters for effective emotion recognition. Python Software was used to execute our proposed framework. In the finding assessment phase, Numerous metrics are used to evaluate the proposed model’s detection capability, Such as F1-score (95%), precision (95%), recall (96%), and accuracy (97%). The suggested approach is tested on a Python platform, and the SHO-LSTM’s outcomes are contrasted with those of other previously conducted research. Based on comparative assessments, our suggested approach outperforms the current approaches in vocal emotion recognition.展开更多
文摘This paper focuses on the research of MPLS VPN technology in the ocean information communication network.Through the analysis of the current situation of the ocean information communication network,the architecture design of MPLS VPN technology in the ocean information communication network and the important role of RD value and RT value in the VPN instances,the matching strategies of import RT and export RT of different VPN instances are verified through experiments.
基金Project supported by the National Natural Science Foundation of China (Grant No.10674025)the Doctoral Foundation of the Ministry of Education of China (Grant No.20070386002)
文摘This paper proposes an efficient scheme for quantum communication between two atoms trapped in distant cavities which are connected by an optical fibre. During the operation, all the atomic system, the cavity modes and the fibre are not excited. The quantum state is mediated by the vacuum fields. The idea can be used to realize quantum entanglement between two distant atoms via vacuum.
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(U2441226).
文摘In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disasters frequently damage terrestrial communication infrastructures,making the rapid deployment of emergency communication networks in affected areas critical in increasing rescue efficiency[2].
基金supported in part by the National Natural Science Foundation of China under Grant No.U22B2006.
文摘The emerging deployment of large-scale Low Earth Orbit(LEO)satellite constellations provides seamless global coverage.However,the increasing number of satellites also introduces significant security challenges,such as eavesdropping and illegal communication behavior detection.This paper investigates covert wireless communication over uplink satellite-terrestrial network,focusing on scenarios with warden satellites.By accounting for shot noise generated by ambient signals from terrestrial interferers,the terrestrial transmitter Alice can effectively hide its signal from warden satellites.Leveraging stochastic geometry,the distributions of distances between transmitter and satellites are analyzed,enabling the assessment of uplink performance and interference within a satellite’s coverage area.Approximate expressions for detection error probability and transmission outage probability are derived.Based on the theoretical analysis,an optimal scheme is proposed to maximize covert throughput under the constraint of the average detection error probability of the most detrimental warden satellite.Extensive Monte Carlo simulations experiments are conducted to validate the accuracy of analytical methods for evaluating covert performance.
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 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.
基金supported by Shenzhen Science and Technology Program(KJZD20230923115210021)。
文摘Communications system has a signifi-cant impact on both operational safety and logisti-cal efficiency within low-altitude drone logistics net-works.Aiming at providing a systematic investiga-tion of real-world communication requirements and challenges encountered in Meituan UAV’s daily oper-ations,this article first introduces the operational sce-narios within current drone logistics networks and an-alyzes the related communication requirements.Then,the current communication solution and its inherent bottlenecks are elaborated.Finally,this paper explores emerging technologies and examines their application prospects in drone logistics networks.
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.
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 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(Nos.U20B2038,62231027,62171462,61931011,62001514 and 62271501)。
文摘High-Frequency(HF)communication is widely used for long-distance transmission in remote and disaster areas.However,the dynamic nature of the ionosphere and multipath propagation in the HF channel pose significant challenges to designing efficient and robust communication systems.In this paper,we propose a Fixed Station(FS)and frequency matching method,as well as a power allocation method,to improve the sum-rate of air-to-ground HF communication networks.We derive optimal power allocation among users that share the same frequency,based on which a modified water-filling algorithm is used to solve the power allocation problem in multi-user scenarios,while a low-complexity algorithm is proposed to solve the integer optimization problem of frequency-FS matching.Simulation results demonstrate that the proposed algorithm outperforms the naive algorithm,indicating its effectiveness.
基金supported in part by the National Natural Science Foundation of China(Nos.62101232 and 62471208)in part by the Guangdong Provincial Natural Science Foundation,China(No.2024A151510098)+4 种基金in part by the Shenzhen Science and Technology Program,China(No.JCYJ20220530114412029)in part by Shenzhen Key Laboratory of Robotics and Computer Vision,China(No.ZDSYS20220330160557001)supported by the National Natural Science Foundation of China(No.62301206)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F010005)the Starting Research Fund from the Hangzhou Normal University,China(No.4115C50222204114).
文摘Covert unmanned aerial vehicle(UAV)communication has garnered considerable attention in wireless systems for realizing the sustainable low-altitude economy(LAE).This paper investigates the system policy,trajectory design,and resource allocation for energy-efficient aerial networked systems with the aid of an integrated sensing and communications(ISAC)framework,in which multiple UAVs are employed to simultaneously conduct cooperative sensing and covert downlink transmissions to multiple ground users(GUs)in the presence of a mobile warden(Willie).Specifically,to improve the communication covertness,UAVs are strategically switched between jamming(JUAV)and information(IUAV)modes.Additionally,to cope with the mobility of Willie,an unscented Kalman filtering(UKF)-based method is employed to track and predict Willie’s location relying on the delay and Doppler measurements extracted from the ISAC echoes.Capitalizing on the predicted Willie’s location,a real-time energy efficiency(EE)maximization problem is formulated by jointly optimizing the JUAV selection strategy,IUAV-GU scheduling,communication/jamming power allocation,and UAV trajectories design.The formulation takes into account the communication covertness requirement and the maximum transmit power budget,leading to a mixed-integer non-convex fractional programming.To tackle this challenge,the alternating optimization(AO)approach is adopted,which decomposes the original problem into a series of sub-problems,allowing us to obtain an efficient sub-optimal solution.Simulation results demonstrate that the proposed scheme is capable of tracking Willie accurately and offering excellent system EE performance compared to various benchmark schemes adopting existing designs.
基金supported by the Hainan Province Science and Technology Special Fund,China(No.ZDYF2024GXJS292).
文摘The increasing importance of terminal privacy in the Unmanned Aerial Vehicle(UAV)network has led to a growing recognition of the crucial role of authentication technology in UAV network security.However,traditional authentication approaches are vulnerable due to the transmission of identity information between UAVs and cryptographic paradigm management centers over a public channel.These vulnerabilities include brute-force attacks,single point of failure,and information leakage.Blockchain,as a decentralized distributed ledger with blockchain storage,tamper-proof,secure,and trustworthy features,can solve problems such as single-point-of-failure and trust issues,while the hidden communication in the physical layer can effectively resist information leakage and violent attacks.In this paper,we propose a lightweight UAV network authentication mechanism that leverages blockchain and covert communication,where the identity information is transmitted as covert tags carried by normal modulated signals.In addition,a weight-based Practical Byzantine Fault-Tolerant(wPBFT)consensus protocol is devised,where the weights are determined by the channel states of UAVs and the outcomes of past authentication scenarios.Simulation results demonstrate that the proposed mechanism outperforms traditional benchmarks in terms of security and robustness,particularly under conditions of low Signal-to-Noise Ratio(SNR)and short tag length.
基金supported in part by the National Natural Science Foundation of China(No.62171154)in part by the Fundamental Research Funds for the Central Universities,China(No.HIT.OCEF.2023030).
文摘Non-Orthogonal Multiple Access(NOMA)in Unmanned Aerial Vehicle(UAV)-assisted communications is a promising technique in future wireless networks.However,for UAV-assisted communication systems,secure and covert communication is crucial for maintaining confidentiality in battlefield environments.This study focuses on a novel two-way relaying system assisted by the UAV,leveraging Power Domain NOMA(PD-NOMA),trajectory design,and power allocation strategies to enhance secure communication rates.A PD-NOMA scheme is proposed for the half-duplex two-way UAV relay,utilizing the advantage of Air-to-Ground(A2G)channel.The covert communication scheme is proposed based on the proposed NOMA scheme.A method using permutation matrices is proposed to dynamically adjust the NOMA decoding order based on the UAV trajectory and communication power levels,to reduce complexity while ensuring information causality constraints.A low-interference jamming strategy is proposed for the system for covertness communication.Because of the non-convexity of the problem,the power allocation and trajectory design problem are solved with Difference of Convex(DC)programming and Successive Convex Approximation(SCA).The schemes of jointly designing the NOMA order,allocating the communication power,and designing the trajectory are proposed to maximize the minimum secure communication data rate.Simulation results show that the proposed NOMA-UAV secure communication schemes outperform the benchmarks of the conventional Orthogonal Multiple Access(OMA)method.
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 Natural Science Foundation of China(Nos.62071482,62471485,62471348)Shaanxi Association of Science and Technology Youth Talent Support Program Project,China(No.20230137)+1 种基金Innovative Talents Cultivate Program for Technology Innovation Team of ShaanXi Province,China(No.2024RS-CXTD-08)Youth Talent Lifting Project of the China Association for Science and Technology(No.2021-JCJQ-QT-018)。
文摘With the rapid development of commercial communications,the research on Radar-Communication Coexistence(RCC)systems is becoming a hot spot.The resource allocation techniques play a crucial role in the RCC systems.A performance-driven Joint Radar-target and Communication-user Assignment,along with Power and Subchannel Allocation(JRCAPSA)strategy,is proposed for an RCC network.The optimization model aims to minimize the sum of weighted Bayesian Cramer-Rao Lower Bounds(BCRLBs)of target state estimates for radar purpose.This is subject to constraints such as the Communication Data Rate(CDR)for communication purpose,the total power budget in each RCC system,assignment relationships,and the number of available subchannels.Considering that such a problem falls into the realm of Mixed Integer Programming(MIP),a Three-stage Iteratively Augment-based Optimization Method(TIAOM)is developed.The Communication-User Assignment(CUA),Communication Subchannel Allocation(SCA),and Radar-Target Assignment(RTA)feasible solution domains are iteratively expanded based on their importance,leading to the efficient acquisition of a suboptimal solution.Simulation results show the outperformance of the proposed JRCAPSA strategy,compared to the other benchmarks and the OPTI toolbox.The results also imply that the Bayesian Cramer-Rao Lower Bound(BCRLB)is a more stringent optimization metric for the achieved Mean Square Error(MSE),compared to Mutual Information(MI)and Signal-to-Interference-Noise Ratio(SINR).
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The author Dr.Arshiya S.Ansari extends the appreciation to the Deanship of Postgraduate Studies and Scientific Research at Majmaah University for funding this research work through the project number(R-2025-1538).
文摘Voice, motion, and mimicry are naturalistic control modalities that have replaced text or display-driven control in human-computer communication (HCC). Specifically, the vocals contain a lot of knowledge, revealing details about the speaker’s goals and desires, as well as their internal condition. Certain vocal characteristics reveal the speaker’s mood, intention, and motivation, while word study assists the speaker’s demand to be understood. Voice emotion recognition has become an essential component of modern HCC networks. Integrating findings from the various disciplines involved in identifying vocal emotions is also challenging. Many sound analysis techniques were developed in the past. Learning about the development of artificial intelligence (AI), and especially Deep Learning (DL) technology, research incorporating real data is becoming increasingly common these days. Thus, this research presents a novel selfish herd optimization-tuned long/short-term memory (SHO-LSTM) strategy to identify vocal emotions in human communication. The RAVDESS public dataset is used to train the suggested SHO-LSTM technique. Mel-frequency cepstral coefficient (MFCC) and wiener filter (WF) techniques are used, respectively, to remove noise and extract features from the data. LSTM and SHO are applied to the extracted data to optimize the LSTM network’s parameters for effective emotion recognition. Python Software was used to execute our proposed framework. In the finding assessment phase, Numerous metrics are used to evaluate the proposed model’s detection capability, Such as F1-score (95%), precision (95%), recall (96%), and accuracy (97%). The suggested approach is tested on a Python platform, and the SHO-LSTM’s outcomes are contrasted with those of other previously conducted research. Based on comparative assessments, our suggested approach outperforms the current approaches in vocal emotion recognition.
