Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite...Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.展开更多
The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant e...The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant effort and expense.Monitoring is becoming more efficient thanks to technologies such as Unmanned Aerial Vehicles(UAVs),which can access hard-to-reach areas and provide real-time data.However,in disaster-affected areas,these monitoring systems may encounter many obstacles when communicating with servers or transmitting monitored data.This paper proposes an adaptive communication model to overcome the challenges faced in disaster-affected areas.A base station is responsible for collecting data(such as images and videos)captured by UAVs performing surveillance within its communication range.This station is typically a tower providing fixed cellular network service.However,in the absence of such a tower,a selected UAV may serve as the station,depending on the situation.If surveillance needs to be performed outside the coverage area,it can continue to communicate via nearby UAVs through cooperative communication.UAVs with internet support,known as the Internet of Flying Things(IoFT),will also be utilized to enhance communication capacity and efficiency.The proposed communication model is validated through experiments,showing superior data transmission performance and higher throughput.Analysis indicates it outperforms traditional systems,even in rural areas,with or without internet access.展开更多
Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace divers...Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.展开更多
This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee dr...This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.展开更多
Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future...Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.展开更多
The acquisition of position information of legitimate users and jammers plays an important role in the emerging non-geostationary synchronous orbit(NGSO)satellite communications.In this paper,we study the multi-signal...The acquisition of position information of legitimate users and jammers plays an important role in the emerging non-geostationary synchronous orbit(NGSO)satellite communications.In this paper,we study the multi-signal localization problem in an uplink NGSO satellite communication system.We propose an onboard localization scheme based on multiple observations from the satellite,together with the geometric constraints of the satellite postions,the signal positions,the attitude of the satellite,and the angle-of-arrival(AoAs)of the signals.We develop a massage-passing algorithm,termed the Bayesian blind multi-signal localization(BMSL),to jointly estimate the AoAs and the signal positions.The Cramér-Rao lower bound(CRLB)is derived to characterize the fundamental performance limit of the considered localization problem.Simulation results show that the proposed BMSL algorithm can perform close to the derived CRLB and significantly outperforms its counterpart algorithms.展开更多
In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorit...In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system.An output-based event-triggered scheme is first employed to alleviate transmission burden.Accounting for the limited-communication-induced measurement bias,a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation,thereby achieving accurate system state estimates.Subsequently,the Field Programmable Gate Array(FPGA)implementation of the proposed algorithm is also realized with the hope of providing fast bias calibration in practical scenarios.A simulation about a numerical example and a practical example(for gyroscope’s angular velocity bias calibration)on MATLAB is provided to demonstrate the feasibility and effectiveness of the proposed algorithm.展开更多
The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential sc...The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.展开更多
V2X communication enables vehicles to share real-time traffic and road-condition data,but binding messages to persistent identifiers enables location tracking.Furthermore,since forged reports from malicious vehicles c...V2X communication enables vehicles to share real-time traffic and road-condition data,but binding messages to persistent identifiers enables location tracking.Furthermore,since forged reports from malicious vehicles can distort trust decisions and threaten road safety,privacy-preserving trust management is essential.Lu et al.previously presented BARS,an anonymous reputation mechanism founded on blockchain technology to establish a privacy-preserving trust architecture for V2X communication.In this system,reputation certificates without a vehicle identifier ensure anonymity,while two authorities jointly manage certificate issuance and reputation updates.However,the centralized certificate updates introduce scalability limitations,and the authorities can trace vehicle behavioral information,which threatens privacy guarantees.Several subsequent systems derived from BARS still rely on centralized certificate management and are subject to authority-side privacy leakage.As a result,a key challenge in this line of research remains unresolved:how to decentralize the certificate-update process while preserving privacy against the authorities in privacy-preservingV2X trustmanagement.In this paper,we propose a distributed anonymous reputation system for V2X communication,based on an anonymous reputation system for crowdsensing.In our proposed system for V2X communication,the server is distributed to a certificate authority(CA)and roadside units(RSUs).Each vehicle shows the reputation level to the nearest RSU at the beginning of each time interval,and registers a short-time public key.In the interval,the messages from the vehicle are authenticated under the public key and are scored.At the end of the interval,the nearest RSU updates the certificate anonymously.Our solution decentralizes the certificate-update process by assigning each update to the nearest RSU.A zero-knowledge-proof-based show protocol removes the need for any central authority to handle vehicle certificates and thus prevents the authorities from tracing vehicle activities.Compared with BARS,where centralized authorities must update the reputation certificates of many vehicles and may incur communication and processing delays,our system performs each update locally at the nearest RSUonce per interval.The required interaction consists only of a fewkilobytes of communication and a zero-knowledge proof that is almost fully precomputed on the vehicle side,while the RSU-side processing is estimated to take about 40 ms based on timingmeasurements of the underlying cryptographic operations.This distributed updatemodel avoids the centralized bottleneck of BARS and simultaneously removes the privacy risk arising from authority collusion.展开更多
This study investigates how to pedagogically integrate ideological education with competency development in the Intercultural Communication course,a challenge arising from China’s dual reform contexts of the New Libe...This study investigates how to pedagogically integrate ideological education with competency development in the Intercultural Communication course,a challenge arising from China’s dual reform contexts of the New Liberal Arts initiative and the national curriculum ideology policy.As global interactions intensify,cultivating foreign language professionals who possess both firm cultural confidence and sophisticated intercultural competence have become a critical educational imperative.This exploratory study investigates how a three-dimensional“Value-Knowledge-Competency”framework can guide the redesign of course content,task design,and assessment to achieve organic fusion.Drawing on qualitative data from a case study,it analyzes specific implementation pathways,synthesizes teacher and student feedback,and discusses the resultant challenges and broader implications for foreign language curriculum reform.The findings suggest that such an integrated approach can effectively synergize value guidance with skill cultivation,though its success hinges on overcoming issues related to pedagogical naturalness,resource allocation,and standardized evaluation.展开更多
To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framewor...To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framework integrating Deep Reinforcement Learning(DRL)and Graph Neural Network(GNN)is proposed.This framework models resource allocation as a Partially Observable Markov Game(POMG),designs a weighted reward function to balance radar and communication efficiencies,adopts the Multi-Agent Proximal Policy Optimization(MAPPO)framework,and integrates Graph Convolutional Networks(GCN)and Graph Sample and Aggregate(Graph-SAGE)to optimize information interaction.Simulations show that,compared with traditional methods and pure DRL methods,the proposed framework achieves improvements in performance metrics such as communication success rate,Average Age of Information(AoI),and policy convergence speed,effectively enabling resource management in complex environments.Moreover,the proposed GNN-DRL-based intelligent optimization framework obtains significantly better performance for resource management in multi-agent JRC systems than traditional methods and pure DRL methods.展开更多
Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for ...Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.展开更多
Managing massive data flows effectively and resolving spectrum shortages are two challenges that smart grid communication networks(SGCN)must overcome.To address these problems,we provide a combined optimization approa...Managing massive data flows effectively and resolving spectrum shortages are two challenges that smart grid communication networks(SGCN)must overcome.To address these problems,we provide a combined optimization approach that makes use of cognitive radio(CR)and non-orthogonal multiple access(NOMA)technologies.Our work focuses on using user pairing(UP)and power allocation(PA)techniques to maximize energy efficiency(EE)in SGCN,particularly within neighbourhood area networks(NANs).We develop a joint optimization problem that takes into account the real-world limitations of a CR-NOMA setting.This problem is NP-hard,nonlinear,and nonconvex by nature.To address the computational complexity of the problem,we use the block coordinate descent(BCD)method,which breaks the problem into UP and PA subproblems.Initially,we proposed the zebra-optimization user pairing(ZOUP)algorithm to tackle the UP problem,which outperforms both orthogonal multiple access(OMA)and non-optimized NOMA(UPWO)by 78.8%and13.6%,respectively,at a SNR of 15 dB.Based on the ZOUP pairs,we subsequently proposed the PA approach,i.e.,ZOUPPA,which significantly outperforms UPWO and ZOUP by 53.2%and 25.4%,respectively,at an SNR of 15 dB.A detailed analysis of key parameters,including varying SNRs,power allocation constants,path loss exponents,user density,channel availability,and coverage radius,underscores the superiority of our approach.By facilitating the effective use of communication resources in SGCN,our research opens the door to more intelligent and energy-efficient grid systems.Our work tackles important issues in SGCN and lays the groundwork for future developments in smart grid communication technologies by combining modern optimization approaches with CR-NOMA.展开更多
Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different e...Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).展开更多
This paper investigates the platoon control of heterogeneous vehicular cyber-physical systems(VCPSs) subject to external disturbances by using neural network and uniformly quantized communication data.To reduce the ad...This paper investigates the platoon control of heterogeneous vehicular cyber-physical systems(VCPSs) subject to external disturbances by using neural network and uniformly quantized communication data.To reduce the adverse effects of quantization errors on system performance,a coupling sliding mode surface is established for each following vehicle.The radial basis function(RBF) neural networks are employed to approximate the unknown external disturbances.Then,a novel platoon control law is proposed for cooperative tracking in which each following vehicle only uses the uniformly quantized data of the neighboring vehicles.And the designed controllers in this paper are fully distributed due to the fact that the selection of each vehicle's controller parameters is independent of the entire communication topology.The string stability of VCPSs in the entire control process is ensured rather than only ensuring the string stability after the sliding mode surface converges to zero.Compared with the existing controller design methods and quantization mechanisms,the neural adaptive sliding-mode platoon controller proposed in this paper is superior in performances including tracking errors,driving comfort and fuel economy.Numerical simulations illustrate the effectiveness and superiority of the designed control strategy.展开更多
This paper studies wireless vehicular communication(VehCom)in intelligent transportation systems using an orthogonal frequency division multiplexing with index modulation(OFDM-IM).In the concept of IM,data is transmit...This paper studies wireless vehicular communication(VehCom)in intelligent transportation systems using an orthogonal frequency division multiplexing with index modulation(OFDM-IM).In the concept of IM,data is transmitted not only through the modulated symbols but also via the indices of the active subcarriers.In contrast to the original OFDM,OFDM-IM activates only non-zero subcarriers,increasing energy efficiency.However,the pilotassisted channel estimation(CE)method is a significant challenge in OFDM-IM,where the desired pilot subcarrier interval is related to the OFDM-IM subblock length.This paper proposes a walsh-scattered pilot-assisted CE for OFDM-IM VehCom.The optimum walsh-scattered pilot assignment is proposed to improve the transmission efficiency.Furthermore,a space-time block code with a high transmit diversity gain is employed for OFDM-IM VehCom to enhance VehCom's signal quality.The results show that the proposed method performs higher CE accuracy and better bit-error rate with significant spectral and energy efficiencies than conventional methods.展开更多
In this paper,we analyze the physical layer security(PLS)performance of a free-space optical(FSO)communication system composed of a transmitting satellite and ground users.Specifically,the FSO fading channels follow t...In this paper,we analyze the physical layer security(PLS)performance of a free-space optical(FSO)communication system composed of a transmitting satellite and ground users.Specifically,the FSO fading channels follow the Málaga distribution.Further,we scrutinize the influence of non-zero boresight pointing errors and angle-of-arrival fluctuations on the PLS performance for the first time.We derived the probability density function and cumulative density function of the FSO link,followed by the closed-form expressions of the secrecy outage probability(SOP)and the probability of strictly positive secrecy capacity(SPSC).The asymptotic SOP expression at the high signal-to-noise ratio regime and diversity order are also provided to reveal the physical mechanism of the PLS of the considered system.Finally,Monte Carlo simulation results are presented to verify the correctness of the analytical expressions.The results afford helpful insights for the future design of satellite FSO communication systems.展开更多
Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and env...Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.展开更多
Vehicular communication systems rely on secure vehicle-to-vehicle(V2V)communications for safety-critical information exchange.However,the presence of eavesdropping vehicles poses a significant challenge.This paper inv...Vehicular communication systems rely on secure vehicle-to-vehicle(V2V)communications for safety-critical information exchange.However,the presence of eavesdropping vehicles poses a significant challenge.This paper investigates the security of V2V communications in reconfigurable intelligent surface(RIS)-assisted vehicular communication systems with spectrum sharing.It proposes a three-stage alternating optimization(TSAO)algorithm to address the complex problem of multiple eavesdropped V2V links that reuse the spectrum already occupied by vehicle-toinfrastructure(V2I)links.To solve the mixed-integer and non-convex optimization problem due to coupled variables and complex constraints,the algorithm decomposes the original problem into three easily solvable sub-problems:RIS reflection coefficient optimization,vehicle transmission power optimization,and spectrum sharing optimization.First,the RIS reflection coefficients are optimized by using the penalty convex-concave procedure(CCP)method.Second,the optimal power points are determined in the power optimization sub-problem.Finally,the spectrum sharing optimization sub-problem is constructed as a weighted bipartite graph matching problem and solved by using the optimal matching algorithm.The TSAO algorithm not only maximizes the sum V2V secrecy rate but also ensures the quality-of-service(QoS)requirements of the V2I links.Simulation results validate the superiority of the proposed algorithm and highlight the improvement in the sum V2V secrecy rate achieved by utilizing RIS technology in vehicular communication systems with spectrum sharing.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 62025110,62271093sponsored by Natural Science Foundation of Chongqing,China,under Grant CSTB2023NSCQ-LZX0108.
文摘Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.
文摘The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant effort and expense.Monitoring is becoming more efficient thanks to technologies such as Unmanned Aerial Vehicles(UAVs),which can access hard-to-reach areas and provide real-time data.However,in disaster-affected areas,these monitoring systems may encounter many obstacles when communicating with servers or transmitting monitored data.This paper proposes an adaptive communication model to overcome the challenges faced in disaster-affected areas.A base station is responsible for collecting data(such as images and videos)captured by UAVs performing surveillance within its communication range.This station is typically a tower providing fixed cellular network service.However,in the absence of such a tower,a selected UAV may serve as the station,depending on the situation.If surveillance needs to be performed outside the coverage area,it can continue to communicate via nearby UAVs through cooperative communication.UAVs with internet support,known as the Internet of Flying Things(IoFT),will also be utilized to enhance communication capacity and efficiency.The proposed communication model is validated through experiments,showing superior data transmission performance and higher throughput.Analysis indicates it outperforms traditional systems,even in rural areas,with or without internet access.
文摘Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.
基金National Natural Science Foundation of China under Grants No.62171047,U22B2001,62271065,62001051Beijing Natural Science Foundation under Grant L223027BUPT Excellent Ph.D Students Foundation under Grants CX2021114。
文摘This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.
基金National Natural Science Foundation of China under Grants 62122069,62071431,62072490,62301490Science and Technology Development Fund of Macao,Macao,China under Grant 0158/2022/A+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011287)MYRG2020-00107-IOTSCFDCT SKL-IOTSC(UM)-2021-2023。
文摘Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.
基金National Key R&D Program of China under Grants 2021YFB2900404the National Natural Science Foundation of China under Grants 62371098。
文摘The acquisition of position information of legitimate users and jammers plays an important role in the emerging non-geostationary synchronous orbit(NGSO)satellite communications.In this paper,we study the multi-signal localization problem in an uplink NGSO satellite communication system.We propose an onboard localization scheme based on multiple observations from the satellite,together with the geometric constraints of the satellite postions,the signal positions,the attitude of the satellite,and the angle-of-arrival(AoAs)of the signals.We develop a massage-passing algorithm,termed the Bayesian blind multi-signal localization(BMSL),to jointly estimate the AoAs and the signal positions.The Cramér-Rao lower bound(CRLB)is derived to characterize the fundamental performance limit of the considered localization problem.Simulation results show that the proposed BMSL algorithm can perform close to the derived CRLB and significantly outperforms its counterpart algorithms.
基金support from the National Natural Science Foundation of China(Grant Nos.U2330206,U2230206,62173068)Sichuan Science and Technology Program(Grants Nos.2024NSFSC1483,2024ZYD0156,2023NSFC1962,DQ202412).
文摘In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system.An output-based event-triggered scheme is first employed to alleviate transmission burden.Accounting for the limited-communication-induced measurement bias,a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation,thereby achieving accurate system state estimates.Subsequently,the Field Programmable Gate Array(FPGA)implementation of the proposed algorithm is also realized with the hope of providing fast bias calibration in practical scenarios.A simulation about a numerical example and a practical example(for gyroscope’s angular velocity bias calibration)on MATLAB is provided to demonstrate the feasibility and effectiveness of the proposed algorithm.
基金supported by the Natural Science Foundation of Shandong Province under Grant ZR2024MF062the open research fund of National Mobile Communications Research Laboratory,Southeast University under Grants 2025D03+1 种基金the Future Plan Program for Young Scholars of Shandong University,and the Innovation and Technology Support Program for Young Scholars of Colleges and Universities in Shandong Province under Grant 2022KJ009The B6G R&D Group in Shandong University is greatly thanked for channel measurements.
文摘The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.
文摘V2X communication enables vehicles to share real-time traffic and road-condition data,but binding messages to persistent identifiers enables location tracking.Furthermore,since forged reports from malicious vehicles can distort trust decisions and threaten road safety,privacy-preserving trust management is essential.Lu et al.previously presented BARS,an anonymous reputation mechanism founded on blockchain technology to establish a privacy-preserving trust architecture for V2X communication.In this system,reputation certificates without a vehicle identifier ensure anonymity,while two authorities jointly manage certificate issuance and reputation updates.However,the centralized certificate updates introduce scalability limitations,and the authorities can trace vehicle behavioral information,which threatens privacy guarantees.Several subsequent systems derived from BARS still rely on centralized certificate management and are subject to authority-side privacy leakage.As a result,a key challenge in this line of research remains unresolved:how to decentralize the certificate-update process while preserving privacy against the authorities in privacy-preservingV2X trustmanagement.In this paper,we propose a distributed anonymous reputation system for V2X communication,based on an anonymous reputation system for crowdsensing.In our proposed system for V2X communication,the server is distributed to a certificate authority(CA)and roadside units(RSUs).Each vehicle shows the reputation level to the nearest RSU at the beginning of each time interval,and registers a short-time public key.In the interval,the messages from the vehicle are authenticated under the public key and are scored.At the end of the interval,the nearest RSU updates the certificate anonymously.Our solution decentralizes the certificate-update process by assigning each update to the nearest RSU.A zero-knowledge-proof-based show protocol removes the need for any central authority to handle vehicle certificates and thus prevents the authorities from tracing vehicle activities.Compared with BARS,where centralized authorities must update the reputation certificates of many vehicles and may incur communication and processing delays,our system performs each update locally at the nearest RSUonce per interval.The required interaction consists only of a fewkilobytes of communication and a zero-knowledge proof that is almost fully precomputed on the vehicle side,while the RSU-side processing is estimated to take about 40 ms based on timingmeasurements of the underlying cryptographic operations.This distributed updatemodel avoids the centralized bottleneck of BARS and simultaneously removes the privacy risk arising from authority collusion.
基金Funding Source:2024 Heilongjiang Province Higher Education Teaching Reform Key Research Project.Project Name:Practice and Exploration of Curriculum-Based Political Education in the Intercultural Communication Course Under the New Liberal Arts Framework(Grant No.SJGZB2024063).
文摘This study investigates how to pedagogically integrate ideological education with competency development in the Intercultural Communication course,a challenge arising from China’s dual reform contexts of the New Liberal Arts initiative and the national curriculum ideology policy.As global interactions intensify,cultivating foreign language professionals who possess both firm cultural confidence and sophisticated intercultural competence have become a critical educational imperative.This exploratory study investigates how a three-dimensional“Value-Knowledge-Competency”framework can guide the redesign of course content,task design,and assessment to achieve organic fusion.Drawing on qualitative data from a case study,it analyzes specific implementation pathways,synthesizes teacher and student feedback,and discusses the resultant challenges and broader implications for foreign language curriculum reform.The findings suggest that such an integrated approach can effectively synergize value guidance with skill cultivation,though its success hinges on overcoming issues related to pedagogical naturalness,resource allocation,and standardized evaluation.
基金funded by Shandong Provincial Natural Science Foundation,grant number ZR2023MF111.
文摘To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framework integrating Deep Reinforcement Learning(DRL)and Graph Neural Network(GNN)is proposed.This framework models resource allocation as a Partially Observable Markov Game(POMG),designs a weighted reward function to balance radar and communication efficiencies,adopts the Multi-Agent Proximal Policy Optimization(MAPPO)framework,and integrates Graph Convolutional Networks(GCN)and Graph Sample and Aggregate(Graph-SAGE)to optimize information interaction.Simulations show that,compared with traditional methods and pure DRL methods,the proposed framework achieves improvements in performance metrics such as communication success rate,Average Age of Information(AoI),and policy convergence speed,effectively enabling resource management in complex environments.Moreover,the proposed GNN-DRL-based intelligent optimization framework obtains significantly better performance for resource management in multi-agent JRC systems than traditional methods and pure DRL methods.
基金National Natural Science Foundation of China under Grant 62571248 and Grant 62201266Key Laboratory of Intelligent Space TTC&O(Space Engineering University),Ministry of Education under Grant CYK2025-01-12。
文摘Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.
文摘Managing massive data flows effectively and resolving spectrum shortages are two challenges that smart grid communication networks(SGCN)must overcome.To address these problems,we provide a combined optimization approach that makes use of cognitive radio(CR)and non-orthogonal multiple access(NOMA)technologies.Our work focuses on using user pairing(UP)and power allocation(PA)techniques to maximize energy efficiency(EE)in SGCN,particularly within neighbourhood area networks(NANs).We develop a joint optimization problem that takes into account the real-world limitations of a CR-NOMA setting.This problem is NP-hard,nonlinear,and nonconvex by nature.To address the computational complexity of the problem,we use the block coordinate descent(BCD)method,which breaks the problem into UP and PA subproblems.Initially,we proposed the zebra-optimization user pairing(ZOUP)algorithm to tackle the UP problem,which outperforms both orthogonal multiple access(OMA)and non-optimized NOMA(UPWO)by 78.8%and13.6%,respectively,at a SNR of 15 dB.Based on the ZOUP pairs,we subsequently proposed the PA approach,i.e.,ZOUPPA,which significantly outperforms UPWO and ZOUP by 53.2%and 25.4%,respectively,at an SNR of 15 dB.A detailed analysis of key parameters,including varying SNRs,power allocation constants,path loss exponents,user density,channel availability,and coverage radius,underscores the superiority of our approach.By facilitating the effective use of communication resources in SGCN,our research opens the door to more intelligent and energy-efficient grid systems.Our work tackles important issues in SGCN and lays the groundwork for future developments in smart grid communication technologies by combining modern optimization approaches with CR-NOMA.
基金supported by the National Natural Science Foundation of China(62462040)the Yunnan Fundamental Research Projects(202501AT070345)the Major Science and Technology Projects in Yunnan Province(202202AD080013).
文摘Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).
基金supported by the National Natural Science Foundation of China(62173079,62473203)Liaoning Provincial Science and Technology Plan Joint Program(2024-MSLH-019)+1 种基金the Education Department of Liaoning Province(LJKMZ20221840)Interdisciplinary project of Dalian University(DLUXK-2024-YB-004)。
文摘This paper investigates the platoon control of heterogeneous vehicular cyber-physical systems(VCPSs) subject to external disturbances by using neural network and uniformly quantized communication data.To reduce the adverse effects of quantization errors on system performance,a coupling sliding mode surface is established for each following vehicle.The radial basis function(RBF) neural networks are employed to approximate the unknown external disturbances.Then,a novel platoon control law is proposed for cooperative tracking in which each following vehicle only uses the uniformly quantized data of the neighboring vehicles.And the designed controllers in this paper are fully distributed due to the fact that the selection of each vehicle's controller parameters is independent of the entire communication topology.The string stability of VCPSs in the entire control process is ensured rather than only ensuring the string stability after the sliding mode surface converges to zero.Compared with the existing controller design methods and quantization mechanisms,the neural adaptive sliding-mode platoon controller proposed in this paper is superior in performances including tracking errors,driving comfort and fuel economy.Numerical simulations illustrate the effectiveness and superiority of the designed control strategy.
文摘This paper studies wireless vehicular communication(VehCom)in intelligent transportation systems using an orthogonal frequency division multiplexing with index modulation(OFDM-IM).In the concept of IM,data is transmitted not only through the modulated symbols but also via the indices of the active subcarriers.In contrast to the original OFDM,OFDM-IM activates only non-zero subcarriers,increasing energy efficiency.However,the pilotassisted channel estimation(CE)method is a significant challenge in OFDM-IM,where the desired pilot subcarrier interval is related to the OFDM-IM subblock length.This paper proposes a walsh-scattered pilot-assisted CE for OFDM-IM VehCom.The optimum walsh-scattered pilot assignment is proposed to improve the transmission efficiency.Furthermore,a space-time block code with a high transmit diversity gain is employed for OFDM-IM VehCom to enhance VehCom's signal quality.The results show that the proposed method performs higher CE accuracy and better bit-error rate with significant spectral and energy efficiencies than conventional methods.
基金National Natural Science Foundation of China(Grant No.62271202,62027802)Zhejiang Provincial Natural Science Foundation of China(Grant No.LZ25F010004)。
文摘In this paper,we analyze the physical layer security(PLS)performance of a free-space optical(FSO)communication system composed of a transmitting satellite and ground users.Specifically,the FSO fading channels follow the Málaga distribution.Further,we scrutinize the influence of non-zero boresight pointing errors and angle-of-arrival fluctuations on the PLS performance for the first time.We derived the probability density function and cumulative density function of the FSO link,followed by the closed-form expressions of the secrecy outage probability(SOP)and the probability of strictly positive secrecy capacity(SPSC).The asymptotic SOP expression at the high signal-to-noise ratio regime and diversity order are also provided to reveal the physical mechanism of the PLS of the considered system.Finally,Monte Carlo simulation results are presented to verify the correctness of the analytical expressions.The results afford helpful insights for the future design of satellite FSO communication systems.
基金supported in part by the National Natural Science Foundation of China(Key Program)under Grant No.62031021。
文摘Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.
基金National Natural Science Foundation of China(Nos.61772130,71171045 and 61901104)Innovation Program of Shanghai Municipal Education Commission,China(No.14YZ130)。
文摘Vehicular communication systems rely on secure vehicle-to-vehicle(V2V)communications for safety-critical information exchange.However,the presence of eavesdropping vehicles poses a significant challenge.This paper investigates the security of V2V communications in reconfigurable intelligent surface(RIS)-assisted vehicular communication systems with spectrum sharing.It proposes a three-stage alternating optimization(TSAO)algorithm to address the complex problem of multiple eavesdropped V2V links that reuse the spectrum already occupied by vehicle-toinfrastructure(V2I)links.To solve the mixed-integer and non-convex optimization problem due to coupled variables and complex constraints,the algorithm decomposes the original problem into three easily solvable sub-problems:RIS reflection coefficient optimization,vehicle transmission power optimization,and spectrum sharing optimization.First,the RIS reflection coefficients are optimized by using the penalty convex-concave procedure(CCP)method.Second,the optimal power points are determined in the power optimization sub-problem.Finally,the spectrum sharing optimization sub-problem is constructed as a weighted bipartite graph matching problem and solved by using the optimal matching algorithm.The TSAO algorithm not only maximizes the sum V2V secrecy rate but also ensures the quality-of-service(QoS)requirements of the V2I links.Simulation results validate the superiority of the proposed algorithm and highlight the improvement in the sum V2V secrecy rate achieved by utilizing RIS technology in vehicular communication systems with spectrum sharing.
