The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
Purpose–This study aims to propose a novel identification method to accurately estimate linear and nonlinear dynamics in permanent magnet synchronous linear motor(PMSLM)based on the time-domain analysis of relay feed...Purpose–This study aims to propose a novel identification method to accurately estimate linear and nonlinear dynamics in permanent magnet synchronous linear motor(PMSLM)based on the time-domain analysis of relay feedback.Design/methodology/approach–A mathematical model of the PMSLM-based servo-mechanical system was first established,incorporating the aforementioned nonlinearities.The model’s velocity response was derived by analyzing its behavior as a first-order system under arbitrary input.To induce oscillatory dynamics,an ideal relay with artificially introduced dead-time components was then integrated into the servo-mechanism.Depending on the oscillations and the time-domain analysis,nonlinear formulas were deduced according to the velocity response of the servo-mechanism.Afterwards,the unknown model parameters can be solved on account of the cost function which utilizes the discrepancy between nominal position characteristics and temporary position characteristics,both of which are extracted from the oscillations.The proposed recognition method was validated through a twostage process:(1)numerical simulation and calculation,followed by(2)real-time experimental verification on a direct-drive servo platform.Subsequently,leveraging the identification results,a novel control strategy was developed and its tracking performance was benchmarked against conventional control schemes.Findings–Simulation results demonstrate that the proposed method achieves estimation accuracy within 8%.Building on this,a novel control strategy is developed by incorporating both friction pulsation and force pulsation identification results into the feedforward compensator.Comparative experiments reveal that this strategy significantly enhances tracking and positioning performance over traditional control schemes.In a word,this new identification method can be used in different process control and servo control systems.Moreover,parameter auto-tuning,feed forward compensation or disturbance observer can be investigated based on the obtained information to improve the system stability and control accuracy.Originality/value–It is of great significance for the performance improvement of rail transit motor control equipment,such as electro-mechanical braking systems.By enhancing the efficiency of motor control,the performance of the product will be more outstanding.展开更多
As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent...As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent QKD protocols,and they commonly rely on the deployment of single-protocol trusted relay chains for long reach.Driven by the evolution of QKD protocols,large-scale QKD networking is expected to migrate from a single-protocol to a multi-protocol paradigm,during which some useful evolutionary elements for the later stages of the quantum Internet may be incorporated.In this work,we delve into a pivotal technique for large-scale QKD networking,namely,multi-protocol relay chaining.A multi-protocol relay chain is established by connecting a set of trusted/untrusted relays relying on multiple QKD protocols between a pair of QKD nodes.The structures of diverse multi-protocol relay chains are described,based on which the associated model is formulated and the policies are defined for the deployment of multi-protocol relay chains.Furthermore,we propose three multi-protocol relay chaining heuristics.Numerical simulations indicate that the designed heuristics can effectively reduce the number of trusted relays deployed and enhance the average security level versus the commonly used single-protocol trusted relay chaining methods on backbone network topologies.展开更多
A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a...A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a hybrid network of RIS and Half-Duplex(HD)Amplify-and-Forward(AF)relay.We model the system’s signal propagation and propose a new algorithm to get the system’s Achievable Rate(AR)value.We complete simulations to evaluate the performance of the RIS and HD-AF relay hybrid network system compared to the system assisted by either the RIS or HD-AF relay.The simulations indicate that many factors can considerably influence the system performance.Selecting an optimal placement for the RIS and relay can result in the best performance for the RIS and HD-AF relay hybrid network system in situations where the direct link between the receiver and transmitter is absent.展开更多
Developing high-efficient flame-retardant coatings is crucial for fire safety polymer and battery fields.Traditional intumescent coatings and ceramifiable coatings struggle to provide immediate and prolonged protectio...Developing high-efficient flame-retardant coatings is crucial for fire safety polymer and battery fields.Traditional intumescent coatings and ceramifiable coatings struggle to provide immediate and prolonged protection simultaneously,which limits the applicability.To address this,an innovative bi-layered coating with organic/nano-inorganic additives is inspired by differential response behaviors,enabling relay response effect with both fast-acting and extended protection.Specifically,two layers function continuously in the form of a relay.With a mere 320 microns,the bi-layered coating withstands fire temperatures of up to 1400℃for at least 900 s.Consequently,the coating effective prevented burn through in aluminum plates and glass fabric-reinforced epoxy resin,which otherwise were burned through in 135 and 173 s,respectively.Meanwhile,the bi-layered coating suppressed the formation and decomposition of solid interface layer in lithium soft-package batteries,leading to prolonged electrochemical stability and fire safety.Additionally,the bi-layered coating with a fast response endows polyurethane foam with rapid self-extinguishing,preventing ignition even under exposure to strong fire of 1400℃.Shortly,our work offers new insights into the design and development of thin,high-performance,and multi-application flame-retardant coatings.展开更多
This paper is concerned with design-ing symbol labeling for a low-density parity-check(LDPC)-coded delayed bit-interleaved coded modu-lation(DBICM)scheme in a two-way relay channel(TWRC).We first present some properti...This paper is concerned with design-ing symbol labeling for a low-density parity-check(LDPC)-coded delayed bit-interleaved coded modu-lation(DBICM)scheme in a two-way relay channel(TWRC).We first present some properties of symbol labeling within a phase shift keying(PSK)modula-tion.These properties reduce the candidate labeling search space.Based on this search space,we take DBICM capacity as the cost function and propose a general method for optimizing symbol labeling by em-ploying the differential evolution algorithm.Numeri-cal results show that our labeling obtains a signal-to-noise ratio(SNR)gain up to 0.45 dB with respect to Gray labeling.展开更多
An N-heterocyclic carbene(NHC)catalyzed enantioselective cyclisation and trifluoromethylation of olefins with cinnamaldehydes via radical relay cross-coupling in the presence of Togni reagent is reported andδ-lactone...An N-heterocyclic carbene(NHC)catalyzed enantioselective cyclisation and trifluoromethylation of olefins with cinnamaldehydes via radical relay cross-coupling in the presence of Togni reagent is reported andδ-lactones tolerated with stereogenic centers atβ-andγ-positions are obtained in moderate to high yields and with high enantioselectivities.Further computational studies explain that the radical crosscoupling step is the key to determining the enantioselectivity.Energy analysis of key transition states and intermediates also provides a reasonable explanation for the difficulty of diastereoselective control.DFT calculations also reveal that the hydrogen-bonding interaction plays a vital role in the promotion of this chemistry.展开更多
In Power Line Communications(PLC),there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons,which creates coverage issues despite the not too long distances...In Power Line Communications(PLC),there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons,which creates coverage issues despite the not too long distances.Hence,PLC networks often employ repeaters/relays,especially in smart grid neighborhood area networks.Even in broadband indoor PLC systems that offer a notable data rate,relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things paradigm.In this paper,we study Multiple-Input Multiple-Output(MIMO)PLC systems that incorporate inband full-duplex functionality in relaying networks.We present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC systems.To reach this analysis,we get channel realizations from random network layouts for indoor and outdoor scenarios.We adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC standards.The concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput:smart grids with enhanced communications in outdoor scenarios,and“last meter”systems for high-speed connections everywhere in indoor ones.展开更多
Wireless Body Area Network(WBAN)is essential for continuous health monitoring.However,they face energy efficiency challenges due to the low power consumption of sensor nodes.Current WBAN routing protocols face limitat...Wireless Body Area Network(WBAN)is essential for continuous health monitoring.However,they face energy efficiency challenges due to the low power consumption of sensor nodes.Current WBAN routing protocols face limitations in strategically minimizing energy consumption during the retrieval of vital health parameters.Efficient network traffic management remains a challenge,with existing approaches often resulting in increased delay and reduced throughput.Additionally,insufficient attention has been paid to enhancing channel capacity to maintain signal strength and mitigate fading effects under dynamic and robust operating scenarios.Several routing strategies and procedures have been developed to effectively reduce communication-related energy consumption based on the selection of relay nodes.The relay node selection is essential for data transmission in WBAN.This paper introduces an Adaptive Relay-Assisted Protocol(ARAP)for WBAN,a hybrid routing protocol designed to optimize energy use and Quality of Service(QoS)metrics such as network longevity,latency,throughput,and residual energy.ARAP employs neutrosophic relay node selection techniques,including the Analytic Hierarchy Process(AHP)and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)to optimally resolve data and decision-making uncertainties.The protocol was compared with existing protocols such as Low-Energy Adaptive Clustering Hierarchy(LEACH),Modified-Adaptive Threshold Testing and Evaluation Methodology for Performance Testing(M-ATTEMPT),Wireless Adaptive Sampling Protocol(WASP),and Tree-Based Multicast Quality of Service(TMQoS).The comparative results show that the ARAP significantly outperformed these protocols in terms of network longevity and energy efficiency.ARAP has lower communication cost,better throughput,reduced delay,increased network lifetime,and enhanced residual energy.The simulation results indicate that the proposed approach performed better than the conventional methods,with 68%,62%,25%,and 50%improvements in network longevity,residual energy,throughput,and latency,respectively.This significantly improves the functional lifespan of WBAN and makes them promising candidates for sophisticated health monitoring systems.展开更多
The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless cove...The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface(IRS)with a decode-andforward(DF)relay to enhance spectral efficiency in extended-range scenarios.B...This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface(IRS)with a decode-andforward(DF)relay to enhance spectral efficiency in extended-range scenarios.By combining the amplification capability of the active IRS and the signal regeneration function of the DF relay,the proposed system effectively mitigates path loss and fading.We derive closed-form upper bounds on the achievable rate and develop an optimal power allocation strategy under a total power constraint.Numerical results demonstrate that the hybrid scheme significantly outperforms conventional passive IRS-assisted or active IRS-only configurations,particularly under conditions of limited reflecting elements or moderate signal-to-noise ratios.展开更多
With the continuous improvement of current science and technology and residents’electricity demand,the power system relay protection course has become a key component of the curriculum for students majoring in power ...With the continuous improvement of current science and technology and residents’electricity demand,the power system relay protection course has become a key component of the curriculum for students majoring in power engineering.In this context,the teaching model of power system relay protection faces both new challenges and opportunities.By integrating the Outcome-Based Education(OBE)concept,teachers can reconstruct curriculum objectives and teaching frameworks by clearly defining learning outcomes,thereby enhancing students’practical competencies and innovative thinking.Based on the core connotation of the OBE concept,this paper analyzes the significance of incorporating OBE into Power System Relay Protection teaching and explores effective implementation strategies.The findings aim to offer practical insights for teaching reform and to strengthen the alignment between academic training and industry requirements.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective metho...Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
A novel photocatalytic energy transfer-driven radical relay strategy has been introduced for the chemoand regioselective 1,4-difunctionalization of carbon-sulfur double bonds.This represents the first instance of radi...A novel photocatalytic energy transfer-driven radical relay strategy has been introduced for the chemoand regioselective 1,4-difunctionalization of carbon-sulfur double bonds.This represents the first instance of radical-mediated dual-functionalization of X-Y type unsaturated bonds,enabling the synthesis of complex linear molecules with C–O,C–N,and C-S bonds in a single operation.The method surpasses traditional approaches by avoiding the need for thiourea intermediates and the harsh conditions typically associated with them.The developed strategy exemplifies versatility,being applicable to 1,4-oxyamination,1,4-diamination,and 1,4-sulfonamination reactions,and has demonstrated compatibility with over 60 different substrates.The research also elucidates the role of electronic complementarity between radicals and receptors in achieving high selectivity in 1,4-difunctionalization reactions.This study significantly advances the field of bifunctionalization and remote difunctionalization reactions,with profound implications for the development of pharmaceuticals and materials science.展开更多
Physical layer security methods based on joint relay and jammer selection(JRJS)have been widely investigated in the study of secure wireless communications.Different from current works on JRJS schemes,which assumed th...Physical layer security methods based on joint relay and jammer selection(JRJS)have been widely investigated in the study of secure wireless communications.Different from current works on JRJS schemes,which assumed that the global channel state information(CSI)of the eavesdroppers(Eves)was known beforehand,then the optimal relaying and jamming relays were determined.More importantly,the time complexity of selecting optimal jamming relay is O(N^(2)),where N is the maximum number of relays/Eves.In this paper,for the scenario where the source wants to exchange the message with the destination,via relaying scheme due to longer communication distance and limited transmission power,in the presence of multiple Eves,with the assumption of Eves'perfect CSI and average CSI,we propose two kinds of JRJS methods.In particular,the time complexity of finding the optimal jammer can be reduced to O(N).Furthermore,we present a novel JRJS scheme for no CSI of Eves by minimizing the difference between expected signal and interfering signal at the destination.Finally,simulations show that the designed methods are more effective than JRJS and other existing strategies in terms of security performance.展开更多
This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying tec...This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying techniques are utilized to enhance secrecy performance. By jointly optimizing the link selection strategy, the UAV position, and the reflection coefficient of the IRS, we aim to maximize the long-term average secrecy rate. Specifically, we propose a novel buffer in/out stabilization scheme based on the Lyapunov framework, which transforms the long-term average secrecy rate maximization problem into two per-slot drift-plus-penalty minimization problems with different link selection factors. The hybrid Particle Swarm Optimization-Artificial Fish Swarm Algorithm (PSO-AFSA) is adopted to optimize the UAV position, and the IRS reflection coefficient optimization problem is solved by iterative optimization in which auxiliary variables and standard convex optimization algorithms are introduced. Finally, the delay constraint is set to ensure the timeliness of information packets. Simulation results demonstrate that our proposed scheme outperforms the comparison schemes in terms of average secrecy rate. Specifically, the addition of BA improves the average secrecy rate by 1.37 bps/Hz, and the continued optimizations of IRS reflection coefficients and UAV positions improve the average secrecy rate by 2.46 bps/Hz and 3.75 bps/Hz, respectively.展开更多
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
文摘Purpose–This study aims to propose a novel identification method to accurately estimate linear and nonlinear dynamics in permanent magnet synchronous linear motor(PMSLM)based on the time-domain analysis of relay feedback.Design/methodology/approach–A mathematical model of the PMSLM-based servo-mechanical system was first established,incorporating the aforementioned nonlinearities.The model’s velocity response was derived by analyzing its behavior as a first-order system under arbitrary input.To induce oscillatory dynamics,an ideal relay with artificially introduced dead-time components was then integrated into the servo-mechanism.Depending on the oscillations and the time-domain analysis,nonlinear formulas were deduced according to the velocity response of the servo-mechanism.Afterwards,the unknown model parameters can be solved on account of the cost function which utilizes the discrepancy between nominal position characteristics and temporary position characteristics,both of which are extracted from the oscillations.The proposed recognition method was validated through a twostage process:(1)numerical simulation and calculation,followed by(2)real-time experimental verification on a direct-drive servo platform.Subsequently,leveraging the identification results,a novel control strategy was developed and its tracking performance was benchmarked against conventional control schemes.Findings–Simulation results demonstrate that the proposed method achieves estimation accuracy within 8%.Building on this,a novel control strategy is developed by incorporating both friction pulsation and force pulsation identification results into the feedforward compensator.Comparative experiments reveal that this strategy significantly enhances tracking and positioning performance over traditional control schemes.In a word,this new identification method can be used in different process control and servo control systems.Moreover,parameter auto-tuning,feed forward compensation or disturbance observer can be investigated based on the obtained information to improve the system stability and control accuracy.Originality/value–It is of great significance for the performance improvement of rail transit motor control equipment,such as electro-mechanical braking systems.By enhancing the efficiency of motor control,the performance of the product will be more outstanding.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62201276,62350001,U22B2026,and 62471248)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300701)+1 种基金the Key R&D Program(Industry Foresight and Key Core Technologies)of Jiangsu Province(Grant No.BE2022071)Natural Science Research of Jiangsu Higher Education Institutions of China(Grant No.22KJB510007)。
文摘As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent QKD protocols,and they commonly rely on the deployment of single-protocol trusted relay chains for long reach.Driven by the evolution of QKD protocols,large-scale QKD networking is expected to migrate from a single-protocol to a multi-protocol paradigm,during which some useful evolutionary elements for the later stages of the quantum Internet may be incorporated.In this work,we delve into a pivotal technique for large-scale QKD networking,namely,multi-protocol relay chaining.A multi-protocol relay chain is established by connecting a set of trusted/untrusted relays relying on multiple QKD protocols between a pair of QKD nodes.The structures of diverse multi-protocol relay chains are described,based on which the associated model is formulated and the policies are defined for the deployment of multi-protocol relay chains.Furthermore,we propose three multi-protocol relay chaining heuristics.Numerical simulations indicate that the designed heuristics can effectively reduce the number of trusted relays deployed and enhance the average security level versus the commonly used single-protocol trusted relay chaining methods on backbone network topologies.
文摘A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a hybrid network of RIS and Half-Duplex(HD)Amplify-and-Forward(AF)relay.We model the system’s signal propagation and propose a new algorithm to get the system’s Achievable Rate(AR)value.We complete simulations to evaluate the performance of the RIS and HD-AF relay hybrid network system compared to the system assisted by either the RIS or HD-AF relay.The simulations indicate that many factors can considerably influence the system performance.Selecting an optimal placement for the RIS and relay can result in the best performance for the RIS and HD-AF relay hybrid network system in situations where the direct link between the receiver and transmitter is absent.
基金the support by the National Natural Science Foundation of China(grant numbers 52273048 and 51973006)the Beijing Natural Science Foundation of China(grant number 2222052)the financial support of this work by BIOFIRESAFE(PID2020-117274RB-I00)funded by MINECO,Spain。
文摘Developing high-efficient flame-retardant coatings is crucial for fire safety polymer and battery fields.Traditional intumescent coatings and ceramifiable coatings struggle to provide immediate and prolonged protection simultaneously,which limits the applicability.To address this,an innovative bi-layered coating with organic/nano-inorganic additives is inspired by differential response behaviors,enabling relay response effect with both fast-acting and extended protection.Specifically,two layers function continuously in the form of a relay.With a mere 320 microns,the bi-layered coating withstands fire temperatures of up to 1400℃for at least 900 s.Consequently,the coating effective prevented burn through in aluminum plates and glass fabric-reinforced epoxy resin,which otherwise were burned through in 135 and 173 s,respectively.Meanwhile,the bi-layered coating suppressed the formation and decomposition of solid interface layer in lithium soft-package batteries,leading to prolonged electrochemical stability and fire safety.Additionally,the bi-layered coating with a fast response endows polyurethane foam with rapid self-extinguishing,preventing ignition even under exposure to strong fire of 1400℃.Shortly,our work offers new insights into the design and development of thin,high-performance,and multi-application flame-retardant coatings.
文摘This paper is concerned with design-ing symbol labeling for a low-density parity-check(LDPC)-coded delayed bit-interleaved coded modu-lation(DBICM)scheme in a two-way relay channel(TWRC).We first present some properties of symbol labeling within a phase shift keying(PSK)modula-tion.These properties reduce the candidate labeling search space.Based on this search space,we take DBICM capacity as the cost function and propose a general method for optimizing symbol labeling by em-ploying the differential evolution algorithm.Numeri-cal results show that our labeling obtains a signal-to-noise ratio(SNR)gain up to 0.45 dB with respect to Gray labeling.
基金financial supports for this work are provided by the National Natural Science Foundation of China(Nos.21871160,21672121,22071130)。
文摘An N-heterocyclic carbene(NHC)catalyzed enantioselective cyclisation and trifluoromethylation of olefins with cinnamaldehydes via radical relay cross-coupling in the presence of Togni reagent is reported andδ-lactones tolerated with stereogenic centers atβ-andγ-positions are obtained in moderate to high yields and with high enantioselectivities.Further computational studies explain that the radical crosscoupling step is the key to determining the enantioselectivity.Energy analysis of key transition states and intermediates also provides a reasonable explanation for the difficulty of diastereoselective control.DFT calculations also reveal that the hydrogen-bonding interaction plays a vital role in the promotion of this chemistry.
基金supported by the Spanish Government and EU,under project PID2019-109842RB-I00/AEI/10.13039/501100011033。
文摘In Power Line Communications(PLC),there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons,which creates coverage issues despite the not too long distances.Hence,PLC networks often employ repeaters/relays,especially in smart grid neighborhood area networks.Even in broadband indoor PLC systems that offer a notable data rate,relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things paradigm.In this paper,we study Multiple-Input Multiple-Output(MIMO)PLC systems that incorporate inband full-duplex functionality in relaying networks.We present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC systems.To reach this analysis,we get channel realizations from random network layouts for indoor and outdoor scenarios.We adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC standards.The concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput:smart grids with enhanced communications in outdoor scenarios,and“last meter”systems for high-speed connections everywhere in indoor ones.
文摘Wireless Body Area Network(WBAN)is essential for continuous health monitoring.However,they face energy efficiency challenges due to the low power consumption of sensor nodes.Current WBAN routing protocols face limitations in strategically minimizing energy consumption during the retrieval of vital health parameters.Efficient network traffic management remains a challenge,with existing approaches often resulting in increased delay and reduced throughput.Additionally,insufficient attention has been paid to enhancing channel capacity to maintain signal strength and mitigate fading effects under dynamic and robust operating scenarios.Several routing strategies and procedures have been developed to effectively reduce communication-related energy consumption based on the selection of relay nodes.The relay node selection is essential for data transmission in WBAN.This paper introduces an Adaptive Relay-Assisted Protocol(ARAP)for WBAN,a hybrid routing protocol designed to optimize energy use and Quality of Service(QoS)metrics such as network longevity,latency,throughput,and residual energy.ARAP employs neutrosophic relay node selection techniques,including the Analytic Hierarchy Process(AHP)and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)to optimally resolve data and decision-making uncertainties.The protocol was compared with existing protocols such as Low-Energy Adaptive Clustering Hierarchy(LEACH),Modified-Adaptive Threshold Testing and Evaluation Methodology for Performance Testing(M-ATTEMPT),Wireless Adaptive Sampling Protocol(WASP),and Tree-Based Multicast Quality of Service(TMQoS).The comparative results show that the ARAP significantly outperformed these protocols in terms of network longevity and energy efficiency.ARAP has lower communication cost,better throughput,reduced delay,increased network lifetime,and enhanced residual energy.The simulation results indicate that the proposed approach performed better than the conventional methods,with 68%,62%,25%,and 50%improvements in network longevity,residual energy,throughput,and latency,respectively.This significantly improves the functional lifespan of WBAN and makes them promising candidates for sophisticated health monitoring systems.
文摘The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金supported in part by National Key R&D Program of China(2022YFB2903500)NSFC Grant 62331022,Grant 62371289+4 种基金Grant 624B2094in part by the Shanghai Jiao Tong University 2030 Initiative,and the Guangdong Science and Technology program under grant 2022A0505050011in part by the Outstanding Doctoral Graduates Development Scholarship of Shanghai Jiao Tong Universityin part by Shanghai Kewei under Grant 22JC1404000Grant 24DP1500500.
文摘This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface(IRS)with a decode-andforward(DF)relay to enhance spectral efficiency in extended-range scenarios.By combining the amplification capability of the active IRS and the signal regeneration function of the DF relay,the proposed system effectively mitigates path loss and fading.We derive closed-form upper bounds on the achievable rate and develop an optimal power allocation strategy under a total power constraint.Numerical results demonstrate that the hybrid scheme significantly outperforms conventional passive IRS-assisted or active IRS-only configurations,particularly under conditions of limited reflecting elements or moderate signal-to-noise ratios.
文摘With the continuous improvement of current science and technology and residents’electricity demand,the power system relay protection course has become a key component of the curriculum for students majoring in power engineering.In this context,the teaching model of power system relay protection faces both new challenges and opportunities.By integrating the Outcome-Based Education(OBE)concept,teachers can reconstruct curriculum objectives and teaching frameworks by clearly defining learning outcomes,thereby enhancing students’practical competencies and innovative thinking.Based on the core connotation of the OBE concept,this paper analyzes the significance of incorporating OBE into Power System Relay Protection teaching and explores effective implementation strategies.The findings aim to offer practical insights for teaching reform and to strengthen the alignment between academic training and industry requirements.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
基金supported by the Fund of Key Laboratory of Biomedical Engineering of Hainan Province(No.BME20240001)the STI2030-Major Projects(No.2021ZD0200104)the National Natural Science Foundations of China under Grant 61771437.
文摘Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金the National Natural Science Foundation of China(No.22101059)the financial support from Guangxi Science and Technology Program of China(No.2023GXNSFBA026275)Guangxi Normal University。
文摘A novel photocatalytic energy transfer-driven radical relay strategy has been introduced for the chemoand regioselective 1,4-difunctionalization of carbon-sulfur double bonds.This represents the first instance of radical-mediated dual-functionalization of X-Y type unsaturated bonds,enabling the synthesis of complex linear molecules with C–O,C–N,and C-S bonds in a single operation.The method surpasses traditional approaches by avoiding the need for thiourea intermediates and the harsh conditions typically associated with them.The developed strategy exemplifies versatility,being applicable to 1,4-oxyamination,1,4-diamination,and 1,4-sulfonamination reactions,and has demonstrated compatibility with over 60 different substrates.The research also elucidates the role of electronic complementarity between radicals and receptors in achieving high selectivity in 1,4-difunctionalization reactions.This study significantly advances the field of bifunctionalization and remote difunctionalization reactions,with profound implications for the development of pharmaceuticals and materials science.
基金supported by the National Natural Science Foundation of China with Grants 62301076 and 62321001。
文摘Physical layer security methods based on joint relay and jammer selection(JRJS)have been widely investigated in the study of secure wireless communications.Different from current works on JRJS schemes,which assumed that the global channel state information(CSI)of the eavesdroppers(Eves)was known beforehand,then the optimal relaying and jamming relays were determined.More importantly,the time complexity of selecting optimal jamming relay is O(N^(2)),where N is the maximum number of relays/Eves.In this paper,for the scenario where the source wants to exchange the message with the destination,via relaying scheme due to longer communication distance and limited transmission power,in the presence of multiple Eves,with the assumption of Eves'perfect CSI and average CSI,we propose two kinds of JRJS methods.In particular,the time complexity of finding the optimal jammer can be reduced to O(N).Furthermore,we present a novel JRJS scheme for no CSI of Eves by minimizing the difference between expected signal and interfering signal at the destination.Finally,simulations show that the designed methods are more effective than JRJS and other existing strategies in terms of security performance.
基金co-supported by the National Natural Science Foundation of China(Nos.62271399,61901015,GNA22001 and GAA20024)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F010003).
文摘This paper investigates the secure communication between legitimate users in the presence of eavesdroppers, where the Intelligent Reflective Surface-Unmanned Aerial Vehicle (IRS-UAV) and Buffer-Aided (BA) relaying techniques are utilized to enhance secrecy performance. By jointly optimizing the link selection strategy, the UAV position, and the reflection coefficient of the IRS, we aim to maximize the long-term average secrecy rate. Specifically, we propose a novel buffer in/out stabilization scheme based on the Lyapunov framework, which transforms the long-term average secrecy rate maximization problem into two per-slot drift-plus-penalty minimization problems with different link selection factors. The hybrid Particle Swarm Optimization-Artificial Fish Swarm Algorithm (PSO-AFSA) is adopted to optimize the UAV position, and the IRS reflection coefficient optimization problem is solved by iterative optimization in which auxiliary variables and standard convex optimization algorithms are introduced. Finally, the delay constraint is set to ensure the timeliness of information packets. Simulation results demonstrate that our proposed scheme outperforms the comparison schemes in terms of average secrecy rate. Specifically, the addition of BA improves the average secrecy rate by 1.37 bps/Hz, and the continued optimizations of IRS reflection coefficients and UAV positions improve the average secrecy rate by 2.46 bps/Hz and 3.75 bps/Hz, respectively.
