This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysi...This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.展开更多
It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sens...It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sensor Networks(UWSNs).To this end,this paper investigates the relationship between the Degree of Target Change(DoTC)and the detection period,as well as the impact of individual nodes.A Hierarchical Detection and Tracking Approach(HDTA)is proposed.Firstly,the network detection period is determined according to DoTC,which reflects the variation of target motion.Secondly,during the network detection period,each detection node calculates its own node detection period based on the detection mutual information.Taking DoTC as pheromone,an ant colony algorithm is proposed to adaptively adjust the network detection period.The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25%and the network energy consumption by 10%simultaneously,compared to the traditional adaptive period detection schemes.展开更多
Wireless networks support numerous terminals,manage large data volumes,and provide diverse services,but the vulnerability to environmental changes leads to increased complexity and costs.Situational awareness has been...Wireless networks support numerous terminals,manage large data volumes,and provide diverse services,but the vulnerability to environmental changes leads to increased complexity and costs.Situational awareness has been widely applied in network management,but existing methods fail to find optimal solutions due to the high heterogeneity of base stations,numerous metrics,and complex intercell dependencies.To address this gap,this paper proposes a specialized framework for wireless networks,integrating an evaluation model and control approach.The framework expands the indicator set into four key areas,introduces an evaluation method,and proposes the indicator perturbation greedy(IPG)algorithm and the adjustment scheme selection method based on damping coefficient(DCSS)for effective network optimization.A case study in an urban area demonstrates the framework’s ability to balance and improve network performance,enhancing situational awareness and operational efficiency under dynamic conditions.展开更多
This paper studies the problem of jamming decision-making for dynamic multiple communication links in wireless communication networks(WCNs).We propose a novel jamming channel allocation and power decision-making(JCAPD...This paper studies the problem of jamming decision-making for dynamic multiple communication links in wireless communication networks(WCNs).We propose a novel jamming channel allocation and power decision-making(JCAPD)approach based on multi-agent deep reinforcement learning(MADRL).In high-dynamic and multi-target aviation communication environments,the rapid changes in channels make it difficult for sensors to accurately capture instantaneous channel state information.This poses a challenge to make centralized jamming decisions with single-agent deep reinforcement learning(DRL)approaches.In response,we design a distributed multi-agent decision architecture(DMADA).We formulate multi-jammer resource allocation as a multiagent Markov decision process(MDP)and propose a fingerprint-based double deep Q-Network(FBDDQN)algorithm for solving it.Each jammer functions as an agent that interacts with the environment in this framework.Through the design of a reasonable reward and training mechanism,our approach enables jammers to achieve distributed cooperation,significantly improving the jamming success rate while considering jamming power cost,and reducing the transmission rate of links.Our experimental results show the FBDDQN algorithm is superior to the baseline methods.展开更多
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
As a natural biopolymer material,silk fibroin with unique mechanical properties can be used in the preparation of biocomposite hydrogels for strain sensors.But,the electromechanical properties of bio-composite hydroge...As a natural biopolymer material,silk fibroin with unique mechanical properties can be used in the preparation of biocomposite hydrogels for strain sensors.But,the electromechanical properties of bio-composite hydrogel strain sensors are still insufficient,such as the deterioration of electrical signals and low sensitivity,which need to develop a hydrogel with a stable transmission network for electric con-duction.Herein,a silk fibroin biocomposite hydrogel is prepared by incorporating tannic acid and MXene nanosheets into a polyacrylamide and silk fibroin double network.The electromechanical properties of hydrogels are improved by optimizing the proportion of material components.As a result,the double network structure and supramolecular interaction enhance the stretchability of hydrogels(692% fracture strain).The hydrogel also exhibits good biocompatibility and conductivity(0.85 S/m),which shows the application prospect in wearable sensors.The wireless strain sensor assembled by this biocomposite hy-drogel presents good portability and sensing performance,such as high sensitivity(gauge factor=6.04),wide working range(500% strain),and outstanding stability(1000 cycles at 100%strain).The results in-dicate that the hydrogel strain sensor can be used to monitor human body movement.The biocomposite hydrogel is expected to be applied in the field of wearable strain sensors,and this study can provide a new way for the design of flexible electronic materials.展开更多
Wireless energy transmission technology through the transmitter will be converted into microwave,laser or electromagnetic field and other energy carriers to realize the transmission of space,and the receiver will be c...Wireless energy transmission technology through the transmitter will be converted into microwave,laser or electromagnetic field and other energy carriers to realize the transmission of space,and the receiver will be captured back to the energy conversion of electrical energy,the whole process can be completed without physical contact energy transfer.The core mechanism is to build the energy coupling channel of the transmitter-receiver system,and realize the spatial power transmission through electromagnetic field interaction.In the electromagnetic induction coupled transmission system,the industrial frequency alternating current is converted into direct current by rectification and filtering,and then converted into high-frequency alternating current by high-frequency inverter.This current excites the primary side transmitting winding to generate a time-varying magnetic field,and through magnetic coupling in the secondary side receiving winding inductance electromotive force,and ultimately through the high-frequency rectifier and power regulation circuit to the load power supply.The essence of the process is to establish a transceiver double-ended resonant network,through the magnetic field resonance to achieve efficient energy exchange,and its transmission characteristics follow the laws of electromagnetic induction and the circuit resonance principle of double constraints.展开更多
Wireless Sensor Networks(WSN)have gained significant attention over recent years due to their extensive applications in various domains such as environmentalmonitoring,healthcare systems,industrial automation,and smar...Wireless Sensor Networks(WSN)have gained significant attention over recent years due to their extensive applications in various domains such as environmentalmonitoring,healthcare systems,industrial automation,and smart cities.However,such networks are inherently vulnerable to different types of attacks because they operate in open environments with limited resources and constrained communication capabilities.Thepaper addresses challenges related to modeling and analysis of wireless sensor networks and their susceptibility to attacks.Its objective is to create versatile modeling tools capable of detecting attacks against network devices and identifying anomalies caused either by legitimate user errors or malicious activities.A proposed integrated approach for data collection,preprocessing,and analysis in WSN outlines a series of steps applicable throughout both the design phase and operation stage.This ensures effective detection of attacks and anomalies within WSNs.An introduced attackmodel specifies potential types of unauthorized network layer attacks targeting network nodes,transmitted data,and services offered by the WSN.Furthermore,a graph-based analytical framework was designed to detect attacks by evaluating real-time events from network nodes and determining if an attack is underway.Additionally,a simulation model based on sequences of imperative rules defining behaviors of both regular and compromised nodes is presented.Overall,this technique was experimentally verified using a segment of a WSN embedded in a smart city infrastructure,simulating a wormhole attack.Results demonstrate the viability and practical significance of the technique for enhancing future information security measures.Validation tests confirmed high levels of accuracy and efficiency when applied specifically to detecting wormhole attacks targeting routing protocols in WSNs.Precision and recall rates averaged above the benchmark value of 0.95,thus validating the broad applicability of the proposed models across varied scenarios.展开更多
A Wireless Sensor Network(WSN)comprises a series of spatially distributed autonomous devices,each equipped with sophisticated sensors.These sensors play a crucial role in monitoring diverse environmental conditions su...A Wireless Sensor Network(WSN)comprises a series of spatially distributed autonomous devices,each equipped with sophisticated sensors.These sensors play a crucial role in monitoring diverse environmental conditions such as light intensity,air pressure,temperature,humidity,wind,etc.These sensors are generally deployed in harsh and hostile conditions;hence they suffer from different kinds of faults.However,identifying faults in WSN data remains a complex task,as existing fault detection methods,including centralized,distributed,and hybrid approaches,rely on the spatio⁃temporal correlation among sensor nodes.Moreover,existing techniques predominantly leverage classification⁃based machine learning methods to discern the fault state within WSN.In this paper,we propose a regression⁃based bagging method to detect the faults in the network.The proposed bagging method is consisted of GRU(Gated Recurrent Unit)and Prophet model.Bagging allows weak learners to combine efforts to outperform a strong learner,hence it is appropriate to use in WSN.The proposed bagging method was first trained at the base station,then they were deployed at each SN(Sensor Node).Most of the common faults in WSN,such as transient,intermittent and permanent faults,were considered.The validity of the proposed scheme was tested using a trusted online published dataset.Using experimental studies,compared to the latest state⁃of⁃the⁃art machine learning models,the effectiveness of the proposed model is shown for fault detection.Performance evaluation in terms of false positive rate,accuracy,and false alarm rate shows the efficiency of the proposed algorithm.展开更多
WCE (Wireless Capsule Endoscopy) is a new technology that combines computer vision and medicine, allowing doctors to visualize the conditions inside the intestines, achieving good diagnostic results. However, due to t...WCE (Wireless Capsule Endoscopy) is a new technology that combines computer vision and medicine, allowing doctors to visualize the conditions inside the intestines, achieving good diagnostic results. However, due to the complex intestinal environment and limited pixel resolution of WCE videos, lesions are not easily detectable, and it takes an experienced doctor 1–2 h to analyze a complete WCE video. The use of computer-aided diagnostic methods, assisting or even replacing manual WCE diagnosis, has significant application value. In response to the issue of intestinal lesion detection in WCE videos, this paper proposes a multi-scale feature fusion network model TSD-YOLO based on the YOLO (You Only Look Once) architecture: (I) a Tiny Detection Layer to avoid the loss of shallow feature information for tiny-scale targets;(II) integrating a simple, parameter-free attention module (SimAM) at the neck to better extract local lesion features and fuse features;(III) incorporating a new loss function DIoU (Distance Intersection over Union) to better achieve boundary box regression for target detection. This model was validated using the WCE dataset from Kyushu University Hospital. For the dataset containing 18,000 images, the evaluation metrics of our model for 12 types of lesions, outperformed existing reported results from advanced models on this dataset, and the mAP (mean Average Precision) and precision evaluation metrics improved by 3.7% and 0.9% over the benchmark model.展开更多
This paper designs a high-frequency stable wireless amplitude modulation(AM)system based on a Pierce circuit.The system utilizes an oscillator and comparator to generate a 20 kHz square wave with an adjustable duty cy...This paper designs a high-frequency stable wireless amplitude modulation(AM)system based on a Pierce circuit.The system utilizes an oscillator and comparator to generate a 20 kHz square wave with an adjustable duty cycle,combined with a 41 MHz carrier wave produced by a passive crystal oscillator Pierce circuit.A 100% modulation index amplitude modulation is achieved through the AD835 multiplier.The modulated signal is amplified by a power amplifier circuit and transmitted wirelessly via the transmitter antenna.Upon reception,the signal undergoes two-stage highfrequency amplification before passing through a Schottky diode envelope detector.The NE5532 shaping circuit then restores the square wave.Experimental results demonstrate reliable 11-meter transmission with carrier frequency deviation<0.75% and demodulation error<1%.展开更多
The physical layer key generation technique provides an efficient method,which utilizes the natural dynamics of wireless channel.However,there are some extremely challenging security scenarios such as static or quasi-...The physical layer key generation technique provides an efficient method,which utilizes the natural dynamics of wireless channel.However,there are some extremely challenging security scenarios such as static or quasi-static environment,which lead to the low randomness of generated keys.Meanwhile,the coefficients of the static channel may be dropped into the guard space and discarded by the quantization approach,which causes low key generation rate.To tackle these issues,we propose a random coefficient-moving product based wireless key generation scheme(RCMP-WKG),where new random resources with remarkable fluctuations can be obtained by applying random coefficient and by moving product on the legitimate nodes.Furthermore,appropriate quantization approaches are used to increase the key generation rate.Moreover,the security of our proposed scheme is evaluated by analyzing different attacks and the eavesdropper’s mean square error(MSE).The simulation results reveal that the proposed scheme can achieve better performances in key capacity,key inconsistency rate(KIR)and key generation rate(KGR)compared with the prior works in static environment.Besides,the proposed scheme can deteriorate the MSE performance of the eavesdropper and improve the key generation performance of legitimate nodes by controlling the length of the moving product.展开更多
Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a mult...Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a multi-stage progressive technique called Deep learning based Progressive Joint Source-Channel Coding(DP-JSCC).This approach partitions the source into multiple stages and transmits the signals continuously.The receiver gradually enhances the quality of image reconstruction by progressively receiving the signals,offering greater flexibility compared to existing dynamic rate transmission methods.The model adopts a lightweight architectural design,where we introduce an efficient module called the Inverted Shuffle Attention Bottleneck(ISAB)and incorporate self-attention mechanisms in the encoding and decoding process to capture signal correlations and establish long-range dependencies.Additionally,we introduce the Progressive Focus Weight Allocation(PFWA)method to improve the image reconstruction capability in progressive transmission tasks.These design enhance the expressive capacity of the model.Simulation results demonstrate that DP-JSCC can flexibly adjust the transmission rate according to requirements without the need for retraining or deployment,enabling continuous optimization of signals at different rates.Furthermore,compared to stateof-the-art JSCC methods,DP-JSCC exhibits advantages in terms of computational complexity,parameter count,and reconstruction performance.展开更多
The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,partic...The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,particularly in channel estimation due to complex and dynamic propagation environments.This paper explores the concept of channel knowledge maps(CKMs)as a solution to these challenges.CKMs enable environment-aware communications by providing location-specific channel information,reducing reliance on real-time pilot measurements.We categorize CKM construction techniques into measurement-based,model-based,and hybrid methods,and examine their key applications in integrated sensing and communication(ISAC)systems,beamforming,trajectory optimization of unmanned aerial vehicles(UAVs),base station(BS)placement,and resource allocation.Furthermore,we discuss open challenges and propose future research directions to enhance the robustness,accuracy,and scalability of CKM-based systems in the evolving 6G landscape.展开更多
In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clu...In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA)is proposed to optimise the data transmission path.After having obtained the optimal number of cluster head node(CH),its result might be taken as the basis of producing the initial population of FF-PIA algorithm.The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search.Moreover,a Gaussian perturbation strategy is applied to update the optimal solution,ensuring the algorithm can jump out of the local optimal solution.And,in the WSN data gathering,a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN).We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA)dataset.It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance.FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.展开更多
Metasurfaces offer exceptional capabilities for controlling electromagnetic waves,enabling the realization of unique electromagnetic properties.As communication technology continues to evolve,metasurfaces present prom...Metasurfaces offer exceptional capabilities for controlling electromagnetic waves,enabling the realization of unique electromagnetic properties.As communication technology continues to evolve,metasurfaces present promising applications in wireless communications.This paper reviews the latest advancements in metasurface research within the communication sector,explores metasurface-based wireless relay technologies,and summarizes various wireless communication methods employing different types of metasurfaces across diverse modulation schemes.This paper provides a detailed discussion on the design of wireless communication systems based on coding metasurfaces to simplify transmitter architecture,as well as the development of intelligent coding metasurfaces in the communication field.It also elaborates on the application of vector vortex light fields in metasurface communication.Finally,it offers a forward-looking perspective on wireless communication systems that incorporate coded metasurfaces.This review aims to furnish researchers with a thorough understanding of the current state and future directions of coded metasurface applications in communications.展开更多
This study is based on wireless optogenetic technology,utilizing the CRY2/CIB1 photosensitive system to achieve spatiotemporal control of PD-L1 expression.In vitro experiments showed that the surface PD-L1 positivity ...This study is based on wireless optogenetic technology,utilizing the CRY2/CIB1 photosensitive system to achieve spatiotemporal control of PD-L1 expression.In vitro experiments showed that the surface PD-L1 positivity rate of cells increased from 28.6±3.1%to 67.3±5.4%(P<0.001).In animal experiments,the terminal tumor volume in the light exposure group was 450±90 mm3,with a tumor inhibition rate of approximately 49.4%(P<0.001),and the median survival was extended to 32 days(compared to 24 days in the control group,P=0.004).Immunological tests revealed a significant increase in CD8+T cell infiltration(112±18 vs 52±10 cells/HPF,P<0.01),a 30%decrease in the proportion of Tregs(P<0.05),and an increase in the M1/M2 macrophage ratio to 1.8.The results suggest that the wireless optogenetic system can not only precisely regulate PD-L1 but also remodel the tumor immune microenvironment,providing a new approach for precise immunotherapy of GBM.展开更多
Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These...Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.展开更多
Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commo...Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commonly used in various applications such as environmental monitoring,surveillance,healthcare,agriculture,and industrial automation.Despite the benefits of WSN,energy efficiency remains a challenging problem that needs to be addressed.Clustering and routing can be considered effective solutions to accomplish energy efficiency in WSNs.Recent studies have reported that metaheuristic algorithms can be applied to optimize cluster formation and routing decisions.This study introduces a new Northern Goshawk Optimization with boosted coati optimization algorithm for cluster-based routing(NGOBCO-CBR)method for WSN.The proposed NGOBCO-CBR method resolves the hot spot problem,uneven load balancing,and energy consumption in WSN.The NGOBCO-CBR technique comprises two major processes such as NGO based clustering and BCO-based routing.In the initial phase,the NGObased clustering method is designed for cluster head(CH)selection and cluster construction using five input variables such as residual energy(RE),node proximity,load balancing,network average energy,and distance to BS(DBS).Besides,the NGOBCO-CBR technique applies the BCO algorithm for the optimum selection of routes to BS.The experimental results of the NGOBCOCBR technique are studied under different scenarios,and the obtained results showcased the improved efficiency of the NGOBCO-CBR technique over recent approaches in terms of different measures.展开更多
This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different...This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments.The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency.A novel closed-form expression is also derived for a generalized asymptotic error variance steady state.Steady and convergence analyses are then presented for the synchronization,with frequency adaptations done using least mean square(LMS),the Newton search,the gradient descent(GraDes),the normalized LMS(N-LMS),and the Sign-Data LMS algorithms.Results obtained from real-time experiments showed a better performance of our protocols as compared to the Average Proportional-Integral Synchronization Protocol(AvgPISync)regarding the impact of quantization error on synchronization accuracy,precision,and convergence time.This generalized approach to time synchronization allows flexibility in selecting a suitable protocol for different wireless sensor network applications.展开更多
基金Chongqing Engineering University Undergraduate Innovation and Entrepreneurship Training Program Project:Wireless Fire Automatic Alarm System(Project No.:CXCY2024017)Chongqing Municipal Education Commission Science and Technology Research Project:Development and Research of Chongqing Wireless Fire Automatic Alarm System(Project No.:KJQN202401906)。
文摘This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.
文摘It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sensor Networks(UWSNs).To this end,this paper investigates the relationship between the Degree of Target Change(DoTC)and the detection period,as well as the impact of individual nodes.A Hierarchical Detection and Tracking Approach(HDTA)is proposed.Firstly,the network detection period is determined according to DoTC,which reflects the variation of target motion.Secondly,during the network detection period,each detection node calculates its own node detection period based on the detection mutual information.Taking DoTC as pheromone,an ant colony algorithm is proposed to adaptively adjust the network detection period.The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25%and the network energy consumption by 10%simultaneously,compared to the traditional adaptive period detection schemes.
文摘Wireless networks support numerous terminals,manage large data volumes,and provide diverse services,but the vulnerability to environmental changes leads to increased complexity and costs.Situational awareness has been widely applied in network management,but existing methods fail to find optimal solutions due to the high heterogeneity of base stations,numerous metrics,and complex intercell dependencies.To address this gap,this paper proposes a specialized framework for wireless networks,integrating an evaluation model and control approach.The framework expands the indicator set into four key areas,introduces an evaluation method,and proposes the indicator perturbation greedy(IPG)algorithm and the adjustment scheme selection method based on damping coefficient(DCSS)for effective network optimization.A case study in an urban area demonstrates the framework’s ability to balance and improve network performance,enhancing situational awareness and operational efficiency under dynamic conditions.
基金supported in part by the National Natural Science Foundation of China(No.61906156).
文摘This paper studies the problem of jamming decision-making for dynamic multiple communication links in wireless communication networks(WCNs).We propose a novel jamming channel allocation and power decision-making(JCAPD)approach based on multi-agent deep reinforcement learning(MADRL).In high-dynamic and multi-target aviation communication environments,the rapid changes in channels make it difficult for sensors to accurately capture instantaneous channel state information.This poses a challenge to make centralized jamming decisions with single-agent deep reinforcement learning(DRL)approaches.In response,we design a distributed multi-agent decision architecture(DMADA).We formulate multi-jammer resource allocation as a multiagent Markov decision process(MDP)and propose a fingerprint-based double deep Q-Network(FBDDQN)algorithm for solving it.Each jammer functions as an agent that interacts with the environment in this framework.Through the design of a reasonable reward and training mechanism,our approach enables jammers to achieve distributed cooperation,significantly improving the jamming success rate while considering jamming power cost,and reducing the transmission rate of links.Our experimental results show the FBDDQN algorithm is superior to the baseline methods.
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
基金supported by the National Key Re-search and Development Program of China(No.2021YFA0715700)the National Natural Science Foundation of China(No.52003212).
文摘As a natural biopolymer material,silk fibroin with unique mechanical properties can be used in the preparation of biocomposite hydrogels for strain sensors.But,the electromechanical properties of bio-composite hydrogel strain sensors are still insufficient,such as the deterioration of electrical signals and low sensitivity,which need to develop a hydrogel with a stable transmission network for electric con-duction.Herein,a silk fibroin biocomposite hydrogel is prepared by incorporating tannic acid and MXene nanosheets into a polyacrylamide and silk fibroin double network.The electromechanical properties of hydrogels are improved by optimizing the proportion of material components.As a result,the double network structure and supramolecular interaction enhance the stretchability of hydrogels(692% fracture strain).The hydrogel also exhibits good biocompatibility and conductivity(0.85 S/m),which shows the application prospect in wearable sensors.The wireless strain sensor assembled by this biocomposite hy-drogel presents good portability and sensing performance,such as high sensitivity(gauge factor=6.04),wide working range(500% strain),and outstanding stability(1000 cycles at 100%strain).The results in-dicate that the hydrogel strain sensor can be used to monitor human body movement.The biocomposite hydrogel is expected to be applied in the field of wearable strain sensors,and this study can provide a new way for the design of flexible electronic materials.
文摘Wireless energy transmission technology through the transmitter will be converted into microwave,laser or electromagnetic field and other energy carriers to realize the transmission of space,and the receiver will be captured back to the energy conversion of electrical energy,the whole process can be completed without physical contact energy transfer.The core mechanism is to build the energy coupling channel of the transmitter-receiver system,and realize the spatial power transmission through electromagnetic field interaction.In the electromagnetic induction coupled transmission system,the industrial frequency alternating current is converted into direct current by rectification and filtering,and then converted into high-frequency alternating current by high-frequency inverter.This current excites the primary side transmitting winding to generate a time-varying magnetic field,and through magnetic coupling in the secondary side receiving winding inductance electromotive force,and ultimately through the high-frequency rectifier and power regulation circuit to the load power supply.The essence of the process is to establish a transceiver double-ended resonant network,through the magnetic field resonance to achieve efficient energy exchange,and its transmission characteristics follow the laws of electromagnetic induction and the circuit resonance principle of double constraints.
基金the International Scientific Complex“Astana”was funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan(Grant No.AP19680345).
文摘Wireless Sensor Networks(WSN)have gained significant attention over recent years due to their extensive applications in various domains such as environmentalmonitoring,healthcare systems,industrial automation,and smart cities.However,such networks are inherently vulnerable to different types of attacks because they operate in open environments with limited resources and constrained communication capabilities.Thepaper addresses challenges related to modeling and analysis of wireless sensor networks and their susceptibility to attacks.Its objective is to create versatile modeling tools capable of detecting attacks against network devices and identifying anomalies caused either by legitimate user errors or malicious activities.A proposed integrated approach for data collection,preprocessing,and analysis in WSN outlines a series of steps applicable throughout both the design phase and operation stage.This ensures effective detection of attacks and anomalies within WSNs.An introduced attackmodel specifies potential types of unauthorized network layer attacks targeting network nodes,transmitted data,and services offered by the WSN.Furthermore,a graph-based analytical framework was designed to detect attacks by evaluating real-time events from network nodes and determining if an attack is underway.Additionally,a simulation model based on sequences of imperative rules defining behaviors of both regular and compromised nodes is presented.Overall,this technique was experimentally verified using a segment of a WSN embedded in a smart city infrastructure,simulating a wormhole attack.Results demonstrate the viability and practical significance of the technique for enhancing future information security measures.Validation tests confirmed high levels of accuracy and efficiency when applied specifically to detecting wormhole attacks targeting routing protocols in WSNs.Precision and recall rates averaged above the benchmark value of 0.95,thus validating the broad applicability of the proposed models across varied scenarios.
文摘A Wireless Sensor Network(WSN)comprises a series of spatially distributed autonomous devices,each equipped with sophisticated sensors.These sensors play a crucial role in monitoring diverse environmental conditions such as light intensity,air pressure,temperature,humidity,wind,etc.These sensors are generally deployed in harsh and hostile conditions;hence they suffer from different kinds of faults.However,identifying faults in WSN data remains a complex task,as existing fault detection methods,including centralized,distributed,and hybrid approaches,rely on the spatio⁃temporal correlation among sensor nodes.Moreover,existing techniques predominantly leverage classification⁃based machine learning methods to discern the fault state within WSN.In this paper,we propose a regression⁃based bagging method to detect the faults in the network.The proposed bagging method is consisted of GRU(Gated Recurrent Unit)and Prophet model.Bagging allows weak learners to combine efforts to outperform a strong learner,hence it is appropriate to use in WSN.The proposed bagging method was first trained at the base station,then they were deployed at each SN(Sensor Node).Most of the common faults in WSN,such as transient,intermittent and permanent faults,were considered.The validity of the proposed scheme was tested using a trusted online published dataset.Using experimental studies,compared to the latest state⁃of⁃the⁃art machine learning models,the effectiveness of the proposed model is shown for fault detection.Performance evaluation in terms of false positive rate,accuracy,and false alarm rate shows the efficiency of the proposed algorithm.
文摘WCE (Wireless Capsule Endoscopy) is a new technology that combines computer vision and medicine, allowing doctors to visualize the conditions inside the intestines, achieving good diagnostic results. However, due to the complex intestinal environment and limited pixel resolution of WCE videos, lesions are not easily detectable, and it takes an experienced doctor 1–2 h to analyze a complete WCE video. The use of computer-aided diagnostic methods, assisting or even replacing manual WCE diagnosis, has significant application value. In response to the issue of intestinal lesion detection in WCE videos, this paper proposes a multi-scale feature fusion network model TSD-YOLO based on the YOLO (You Only Look Once) architecture: (I) a Tiny Detection Layer to avoid the loss of shallow feature information for tiny-scale targets;(II) integrating a simple, parameter-free attention module (SimAM) at the neck to better extract local lesion features and fuse features;(III) incorporating a new loss function DIoU (Distance Intersection over Union) to better achieve boundary box regression for target detection. This model was validated using the WCE dataset from Kyushu University Hospital. For the dataset containing 18,000 images, the evaluation metrics of our model for 12 types of lesions, outperformed existing reported results from advanced models on this dataset, and the mAP (mean Average Precision) and precision evaluation metrics improved by 3.7% and 0.9% over the benchmark model.
文摘This paper designs a high-frequency stable wireless amplitude modulation(AM)system based on a Pierce circuit.The system utilizes an oscillator and comparator to generate a 20 kHz square wave with an adjustable duty cycle,combined with a 41 MHz carrier wave produced by a passive crystal oscillator Pierce circuit.A 100% modulation index amplitude modulation is achieved through the AD835 multiplier.The modulated signal is amplified by a power amplifier circuit and transmitted wirelessly via the transmitter antenna.Upon reception,the signal undergoes two-stage highfrequency amplification before passing through a Schottky diode envelope detector.The NE5532 shaping circuit then restores the square wave.Experimental results demonstrate reliable 11-meter transmission with carrier frequency deviation<0.75% and demodulation error<1%.
基金supported in part by the National Natural Science Foundation of China(Numbers 62171445,62471477 and 62201592).
文摘The physical layer key generation technique provides an efficient method,which utilizes the natural dynamics of wireless channel.However,there are some extremely challenging security scenarios such as static or quasi-static environment,which lead to the low randomness of generated keys.Meanwhile,the coefficients of the static channel may be dropped into the guard space and discarded by the quantization approach,which causes low key generation rate.To tackle these issues,we propose a random coefficient-moving product based wireless key generation scheme(RCMP-WKG),where new random resources with remarkable fluctuations can be obtained by applying random coefficient and by moving product on the legitimate nodes.Furthermore,appropriate quantization approaches are used to increase the key generation rate.Moreover,the security of our proposed scheme is evaluated by analyzing different attacks and the eavesdropper’s mean square error(MSE).The simulation results reveal that the proposed scheme can achieve better performances in key capacity,key inconsistency rate(KIR)and key generation rate(KGR)compared with the prior works in static environment.Besides,the proposed scheme can deteriorate the MSE performance of the eavesdropper and improve the key generation performance of legitimate nodes by controlling the length of the moving product.
文摘Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a multi-stage progressive technique called Deep learning based Progressive Joint Source-Channel Coding(DP-JSCC).This approach partitions the source into multiple stages and transmits the signals continuously.The receiver gradually enhances the quality of image reconstruction by progressively receiving the signals,offering greater flexibility compared to existing dynamic rate transmission methods.The model adopts a lightweight architectural design,where we introduce an efficient module called the Inverted Shuffle Attention Bottleneck(ISAB)and incorporate self-attention mechanisms in the encoding and decoding process to capture signal correlations and establish long-range dependencies.Additionally,we introduce the Progressive Focus Weight Allocation(PFWA)method to improve the image reconstruction capability in progressive transmission tasks.These design enhance the expressive capacity of the model.Simulation results demonstrate that DP-JSCC can flexibly adjust the transmission rate according to requirements without the need for retraining or deployment,enabling continuous optimization of signals at different rates.Furthermore,compared to stateof-the-art JSCC methods,DP-JSCC exhibits advantages in terms of computational complexity,parameter count,and reconstruction performance.
基金supported by the National Natural Science Foundation of China under Grants Nos.62431014 and 62271310the Fundamental Research Funds for the Central Universities of China。
文摘The advent of 6G wireless networks promises unprecedented connectivity,supporting ultra-high data rates,low latency,and massive device connectivity.However,these ambitious goals introduce significant challenges,particularly in channel estimation due to complex and dynamic propagation environments.This paper explores the concept of channel knowledge maps(CKMs)as a solution to these challenges.CKMs enable environment-aware communications by providing location-specific channel information,reducing reliance on real-time pilot measurements.We categorize CKM construction techniques into measurement-based,model-based,and hybrid methods,and examine their key applications in integrated sensing and communication(ISAC)systems,beamforming,trajectory optimization of unmanned aerial vehicles(UAVs),base station(BS)placement,and resource allocation.Furthermore,we discuss open challenges and propose future research directions to enhance the robustness,accuracy,and scalability of CKM-based systems in the evolving 6G landscape.
基金partially supported by the National Natural Science Foundation of China(62161016)the Key Research and Development Project of Lanzhou Jiaotong University(ZDYF2304)+1 种基金the Beijing Engineering Research Center of Highvelocity Railway Broadband Mobile Communications(BHRC-2022-1)Beijing Jiaotong University。
文摘In order to solve the problems of short network lifetime and high data transmission delay in data gathering for wireless sensor network(WSN)caused by uneven energy consumption among nodes,a hybrid energy efficient clustering routing base on firefly and pigeon-inspired algorithm(FF-PIA)is proposed to optimise the data transmission path.After having obtained the optimal number of cluster head node(CH),its result might be taken as the basis of producing the initial population of FF-PIA algorithm.The L′evy flight mechanism and adaptive inertia weighting are employed in the algorithm iteration to balance the contradiction between the global search and the local search.Moreover,a Gaussian perturbation strategy is applied to update the optimal solution,ensuring the algorithm can jump out of the local optimal solution.And,in the WSN data gathering,a onedimensional signal reconstruction algorithm model is developed by dilated convolution and residual neural networks(DCRNN).We conducted experiments on the National Oceanic and Atmospheric Administration(NOAA)dataset.It shows that the DCRNN modeldriven data reconstruction algorithm improves the reconstruction accuracy as well as the reconstruction time performance.FF-PIA and DCRNN clustering routing co-simulation reveals that the proposed algorithm can effectively improve the performance in extending the network lifetime and reducing data transmission delay.
基金supported in part by National Natural Science Foundation of China(U24A20307 and 62175224)in part by the science and technology innovation leading talent project of special support plan for high-level talents in Zhejiang Province(2021R52032)+2 种基金in part by the China Jiliang University Basic Research ExpensesZhejiang University Students Science and Technology Innovation Activity Plan-New Talent Plan(2024R409C054)in part by the Natural Science Foundation of Zhejiang Province under Grant(ZCLZ25F0502).
文摘Metasurfaces offer exceptional capabilities for controlling electromagnetic waves,enabling the realization of unique electromagnetic properties.As communication technology continues to evolve,metasurfaces present promising applications in wireless communications.This paper reviews the latest advancements in metasurface research within the communication sector,explores metasurface-based wireless relay technologies,and summarizes various wireless communication methods employing different types of metasurfaces across diverse modulation schemes.This paper provides a detailed discussion on the design of wireless communication systems based on coding metasurfaces to simplify transmitter architecture,as well as the development of intelligent coding metasurfaces in the communication field.It also elaborates on the application of vector vortex light fields in metasurface communication.Finally,it offers a forward-looking perspective on wireless communication systems that incorporate coded metasurfaces.This review aims to furnish researchers with a thorough understanding of the current state and future directions of coded metasurface applications in communications.
文摘This study is based on wireless optogenetic technology,utilizing the CRY2/CIB1 photosensitive system to achieve spatiotemporal control of PD-L1 expression.In vitro experiments showed that the surface PD-L1 positivity rate of cells increased from 28.6±3.1%to 67.3±5.4%(P<0.001).In animal experiments,the terminal tumor volume in the light exposure group was 450±90 mm3,with a tumor inhibition rate of approximately 49.4%(P<0.001),and the median survival was extended to 32 days(compared to 24 days in the control group,P=0.004).Immunological tests revealed a significant increase in CD8+T cell infiltration(112±18 vs 52±10 cells/HPF,P<0.01),a 30%decrease in the proportion of Tregs(P<0.05),and an increase in the M1/M2 macrophage ratio to 1.8.The results suggest that the wireless optogenetic system can not only precisely regulate PD-L1 but also remodel the tumor immune microenvironment,providing a new approach for precise immunotherapy of GBM.
基金partially supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2018R1A6A1A03025242)by the Korea government(MIST)(RS-2023-00302751,RS-2024-00343686)the Research Grant of Kwangwoon University in 2024。
文摘Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.
文摘Wireless Sensor Network(WSN)comprises a set of interconnected,compact,autonomous,and resource-constrained sensor nodes that are wirelessly linked to monitor and gather data from the physical environment.WSNs are commonly used in various applications such as environmental monitoring,surveillance,healthcare,agriculture,and industrial automation.Despite the benefits of WSN,energy efficiency remains a challenging problem that needs to be addressed.Clustering and routing can be considered effective solutions to accomplish energy efficiency in WSNs.Recent studies have reported that metaheuristic algorithms can be applied to optimize cluster formation and routing decisions.This study introduces a new Northern Goshawk Optimization with boosted coati optimization algorithm for cluster-based routing(NGOBCO-CBR)method for WSN.The proposed NGOBCO-CBR method resolves the hot spot problem,uneven load balancing,and energy consumption in WSN.The NGOBCO-CBR technique comprises two major processes such as NGO based clustering and BCO-based routing.In the initial phase,the NGObased clustering method is designed for cluster head(CH)selection and cluster construction using five input variables such as residual energy(RE),node proximity,load balancing,network average energy,and distance to BS(DBS).Besides,the NGOBCO-CBR technique applies the BCO algorithm for the optimum selection of routes to BS.The experimental results of the NGOBCOCBR technique are studied under different scenarios,and the obtained results showcased the improved efficiency of the NGOBCO-CBR technique over recent approaches in terms of different measures.
基金funded by Universiti Putra Malaysia under a Geran Putra Inisiatif(GPI)research grant with reference to GP-GPI/2023/9762100.
文摘This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments.The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency.A novel closed-form expression is also derived for a generalized asymptotic error variance steady state.Steady and convergence analyses are then presented for the synchronization,with frequency adaptations done using least mean square(LMS),the Newton search,the gradient descent(GraDes),the normalized LMS(N-LMS),and the Sign-Data LMS algorithms.Results obtained from real-time experiments showed a better performance of our protocols as compared to the Average Proportional-Integral Synchronization Protocol(AvgPISync)regarding the impact of quantization error on synchronization accuracy,precision,and convergence time.This generalized approach to time synchronization allows flexibility in selecting a suitable protocol for different wireless sensor network applications.
