Deep learning based channel state information(CSI)fingerprint indoor localization schemes need to collect massive labeled data samples for training,and the parameters of the deep neural network are used as the fingerp...Deep learning based channel state information(CSI)fingerprint indoor localization schemes need to collect massive labeled data samples for training,and the parameters of the deep neural network are used as the fingerprints.However,the indoor environment may change,and the previously constructed fingerprint may not be valid for the changed environment.In order to adapt to the changed environment,it requires to recollect massive amount of labeled data samples and perform the training again,which is labor-intensive and time-consuming.In order to overcome this drawback,in this paper,we propose one novel domain adversarial neural network(DANN)based CSI Fingerprint Indoor Localization(D-Fi)scheme,which only needs the unlabeled data samples from the changed environment to update the fingerprint to adapt to the changed environment.Specifically,the previous environment and changed environment are treated as the source domain and the target domain,respectively.The DANN consists of the classification path and the domain-adversarial path,which share the same feature extractor.In the offline phase,the labeled CSI samples are collected as source domain samples to train the neural network of the classification path,while in the online phase,for the changed environment,only the unlabeled CSI samples are collected as target domain samples to train the neural network of the domainadversarial path to update parameters of the feature extractor.In this case,the feature extractor extracts the common features from both the source domain samples corresponding to the previous environment and the target domain samples corresponding to the changed environment.Experiment results show that for the changed localization environment,the proposed D-Fi scheme significantly outperforms the existing convolutional neural network(CNN)based scheme.展开更多
As a computer vision task,object detection algorithms can be applied to various real-world sce-narios.However,efficient algorithms often come with a large number of parameters and high computational complexity.To meet...As a computer vision task,object detection algorithms can be applied to various real-world sce-narios.However,efficient algorithms often come with a large number of parameters and high computational complexity.To meet the demand for high-performance object detection algorithms on mobile devices and embedded devices with limited computational resources,we propose a new lightweight object detection algorithm called DLE-YOLO.Firstly,we design a novel backbone called dual-branch lightweight excitation network(DLEN)for feature extraction,which is mainly constructed by dual-branch lightweight excitation units(DLEU).DLEU is stacked with different numbers of dual-branch lightweight excitation blocks(DLEB),which can extract comprehensive features and integrate information between different channels of features.Secondly,in order to enhance the network to capture key feature information in the regions of interest,the attention model HS-coordinate attention(HS-CA)is introduced into the network.Thirdly,the localization loss utilizes SIoU loss to further optimize the accuracy of the bounding box.Our method achieves a mAP value of 46.0%on the MS-COCO dataset,which is a 2%mAP improvement compared to the baseline YOLOv5-m,while bringing a 19.3%reduction in parameter count and a 12.9%decrease in GFLOPs.Furthermore,our method outperforms some advanced lightweight object detection algorithms,validating the effectiveness of our approach.展开更多
The combination of integrated sensing and communication(ISAC)with mobile edge computing(MEC)enhances the overall safety and efficiency for vehicle to everything(V2X)system.However,existing works have not considered th...The combination of integrated sensing and communication(ISAC)with mobile edge computing(MEC)enhances the overall safety and efficiency for vehicle to everything(V2X)system.However,existing works have not considered the potential impacts on base station(BS)sensing performance when users offload their computational tasks via uplink.This could leave insufficient resources allocated to the sensing tasks,resulting in low sensing performance.To address this issue,we propose a cooperative power,bandwidth and computation resource allocation(RA)scheme in this paper,maximizing the overall utility of Cramer-Rao bound(CRB)for sensing accuracy,computation latency for processing sensing information,and communication and computation latency for computational tasks.To solve the RA problem,a twin delayed deep deterministic policy gradient(TD3)algorithm is adopted to explore and obtain the effective solution of the RA problem.Furthermore,we investigate the performance tradeoff between sensing accuracy and summation of communication latency and computation latency for computational tasks,as well as the relationship between computation latency for processing sensing information and that of computational tasks by numerical simulations.Simulation demonstrates that compared to other benchmark methods,TD3 achieves an average utility improvement of 97.11%and 27.90%in terms of the maximum summation of communication latency and computation latency for computational tasks and improves 3.60 and 1.04 times regarding the maximum computation latency for processing sensing information.展开更多
Enhanced mobile broadband(eMBB)and ultra-reliable low-latency communication(URLLC)are two critical services in 5G mobile networks.While there has been extensive research on their coexistence,few studies have considere...Enhanced mobile broadband(eMBB)and ultra-reliable low-latency communication(URLLC)are two critical services in 5G mobile networks.While there has been extensive research on their coexistence,few studies have considered the impact of bursty URLLC on their coexistence performance.In this paper,we propose a method to allocate computing and radio resources for coexisting eMBB and bursty URLLC services by preempting both computing queues in the base station(BS)and time-frequency resources at the air interface.Specifically,we first divide the computing resources at the BS into a shared part for both URLLC and eMBB users and an exclusive part only for eMBB users,and propose a queuing mechanism with preemptive-resume priority for accessing the shared computing resources.Furthermore,we propose a preemptive puncturing method and a threshold-based queuing mechanism in the air interface to enable the multiplexing of eMBB and URLLC on shared time-frequency resources.We analytically derive the average queuing delay,average computation delay,and average transmission delay of eMBB and URLLC packets.Based on this analysis,we formulate a mixed-integer nonlinear programming problem to minimize the average delay of URLLC packets while satisfying the average delay and throughput requirements of eMBB by jointly optimizing the eMBB subcarrier allocation,the URLLC subcarrier scheduling and the computing resource allocation.We decompose this problem into three subproblems and solve them alternately using a block coordinate descent algorithm.Numerical results show that our proposed method reduces the outage probability and average delay of URLLC compared to the existing works.展开更多
Satellite communications and reconfigurable intelligent surface (RIS) are considered as twopromising technologies that can significantly improve the coverage and energy efficiency of futurewireless communication netwo...Satellite communications and reconfigurable intelligent surface (RIS) are considered as twopromising technologies that can significantly improve the coverage and energy efficiency of futurewireless communication networks. The satellite communications security is often threatened dueto its broadcasting nature. To enhance the physical layer security (PLS) of satellite communications with channel similarity, an aerial RIS-aided dual full-duplex (DFD-ARIS) cooperative jamming method is presented in this paper. Specifically, unlike the existing works that relied onchannel difference, DFD-ARIS utilizes the channel similarity against the eavesdroppers with thehelp of ARIS. In addition, the power allocation is further studied in conjunction with the phasedesign of RIS to minimize the total power under the constraints of data rate, satellite powerlimitation and secrecy rate. Then, the closed-form solutions are achieved. Simulation results showthat the performance of the proposed scheme is superior to the traditional method.展开更多
With the increasing popularity of civilian unmanned aerial vehicles(UAVs),safety issues arising from unsafe operations and terrorist activities have received growing attention.To address this problem,an accurate class...With the increasing popularity of civilian unmanned aerial vehicles(UAVs),safety issues arising from unsafe operations and terrorist activities have received growing attention.To address this problem,an accurate classification and positioning system is needed.Considering that UAVs usually use radio frequency(RF)signals for video transmission,in this paper,we design a passive distributed monitoring system that can classify and locate UAVs according to their RF signals.Specifically,three passive receivers are arranged in different locations to receive RF signals.Due to the noncooperation between a UAV and receivers,it is necessary to detect whether there is a UAV signal from the received signals.Hence,convolutional neural network(CNN)is proposed to not only detect the presence of the UAV,but also classify its type.After the UAV signal is detected,the time difference of arrival(TDOA)of the UAV signal arriving at the receiver is estimated by the cross-correlation method to obtain the corresponding distance difference.Finally,the Chan algorithm is used to calculate the location of the UAV.We deploy a distributed system constructed by three software defined radio(SDR)receivers on the campus playground,and conduct extensive experiments in a real wireless environment.The experimental results have successfully validated the proposed system.展开更多
In this paper,we introduce a new concept,namelyε-arithmetics,for real vectors of any fixed dimension.The basic idea is to use vectors of rational values(called rational vectors)to approximate vectors of real values o...In this paper,we introduce a new concept,namelyε-arithmetics,for real vectors of any fixed dimension.The basic idea is to use vectors of rational values(called rational vectors)to approximate vectors of real values of the same dimension withinεrange.For rational vectors of a fixed dimension m,they can form a field that is an mth order extension Q(α)of the rational field Q whereαhas its minimal polynomial of degree m over Q.Then,the arithmetics,such as addition,subtraction,multiplication,and division,of real vectors can be defined by using that of their approximated rational vectors withinεrange.We also define complex conjugate of a real vector and then inner product and convolutions of two real vectors and two real vector sequences(signals)of finite length.With these newly defined concepts for real vectors,linear processing,such as linear filtering,ARMA modeling,and least squares fitting,can be implemented to real vectorvalued signals with real vector-valued coefficients,which will broaden the existing linear processing to scalar-valued signals.展开更多
In modern Wi-Fi systems,channel state information(CSI)serves as a foundational support for various sensing applications.Currently,existing CSI-based techniques exhibit limitations in terms of environmental adaptabilit...In modern Wi-Fi systems,channel state information(CSI)serves as a foundational support for various sensing applications.Currently,existing CSI-based techniques exhibit limitations in terms of environmental adaptability.As such,optimizing the utilization of subcarrier CSI stands as a critical avenue for enhancing sensing performance.Within the OFDM communication framework,this work derives sensing outcomes for both detection and estimation by harnessing the CSI from every individual measured subcarrier,subsequently consolidating these outcomes.When contrasted against results derived from CSI based on specific extraction protocols or those obtained through weighted summation,the methodology introduced in this study offers substantial improvements in CSI-based detection and estimation performance.This approach not only underscores the significance but also serves as a robust exemplar for the comprehensive application of CSI.展开更多
Orthogonal time-frequency space(OTFS)modulation can effectively counter ICI in high-speed mobile scenarios,fully enhance the spectral efficiency of communication systems in high Doppler expansion scenarios,and improve...Orthogonal time-frequency space(OTFS)modulation can effectively counter ICI in high-speed mobile scenarios,fully enhance the spectral efficiency of communication systems in high Doppler expansion scenarios,and improve the quality of communication systems.Channel estimation performance serves as a critical evaluation parameter within the OTFS modulation system.In this paper,we propose a multi-scale attention residual neural structure for improved channel estimation of OTFS waveforms in different satellite-ground scenario.Firstly,a multi-scale channel feature extraction module is designed,which applies multi-dimensional feature extraction to the channel matrix,thereby bolstering the capability to capture features at diverse scales.Subsequently,a selfattention mechanism is incorporated to concentrate on subtle yet significant features.The extracted features are then integrated and exploited through a residual convolutional architecture to derive an estimation of the channel matrix.Simulations are conducted using the satellite-ground mobile channel model outlined in 3GPP TR 38.811,with the NTN-TDL-C and NTN-TDL-B channel models representing line of sight(LoS)and non-line of sight(NLoS)conditions,respectively.Results demonstrate that the attention-based approach presented surpasses alternative neural network methodologies in terms of mean squared error(MSE),bit error rate(BER),and complexity,and meets the demands of OTFS channel estimation in satellite-ground scenario.展开更多
The integration of communications,sensing and computing(I-CSC)has significant applications in vehicular ad hoc networks(VANETs).A roadside unit(RSU)plays an important role in I-CSC by performing functions such as info...The integration of communications,sensing and computing(I-CSC)has significant applications in vehicular ad hoc networks(VANETs).A roadside unit(RSU)plays an important role in I-CSC by performing functions such as information transmission and edge computing in vehicular communication.Due to the constraints of limited resources,RSU cannot achieve full coverage and deploying RSUs at key cluster heads of hierarchical structures of road networks is an effective management method.However,direct extracting the hierarchical structures for the resource allocation in VANETs is an open issue.In this paper,we proposed a network-based renormalization method based on information flow and geographical location to hierarchically deploy the RSU on the road networks.The renormalization method is compared with two deployment schemes:genetic algorithm(GA)and memetic framework-based optimal RSU deployment(MFRD),to verify the improvement of communication performance.Our results show that the renormalization method is superior to other schemes in terms of RSU coverage and information reception rate.展开更多
Reconfigurable intelligent surface(RIS)is emerged as a promising technique to solve the challenges faced by future wireless communication networks.Although the most commonly used electrically-controlled RISs can achie...Reconfigurable intelligent surface(RIS)is emerged as a promising technique to solve the challenges faced by future wireless communication networks.Although the most commonly used electrically-controlled RISs can achieve millisecond-scale speed of dynamic switch,they have a large number of microwave circuit elements(such as PIN diodes or varactors)which will bring non-negligible insertion loss,and the complicity of the bias network to electrically addressing each element will increase with the expansion of the RIS aperture.Aiming at further reducing the fabrication cost and power consumption,herein an electromechanical RIS used for sub-6G wireless communication is proposed.The electromechanical RIS is designed with a passive metasurface and step-motor driver modules,providing simultaneous high-efficiency reflection(over 80%)and continuous reflection phase coverage of 360.Through electromechanical control,the RIS system can realize different reflective wavefront shaping,and has been employed in the indoor sub-6G wireless environment demonstrating a maximum signal improvement of 8.3 dB.The proposed electromechanical RIS is particularly useful for wireless signal enhancement in static blind area,and has the obvious advantage of not requiring continuous power supply after the RIS being regulated.Therefore,it greatly reduces the overall cost and power consumption which may have potentials in indoor application scenarios for improving wireless communication performance.展开更多
Aiming at the consensus of relative position considering obstacle avoidance for fractional-order multi-agent system,a novel distributed control algorithm is proposed in this paper.Firstly,a synthetic error of each age...Aiming at the consensus of relative position considering obstacle avoidance for fractional-order multi-agent system,a novel distributed control algorithm is proposed in this paper.Firstly,a synthetic error of each agent under the influence of obstacles is introduced.The consensus pro-tocols are designed based on this eror according to sliding mode theory for the order increasing and decreasing,respectively.Then,the Lyapunov function is used to prove the stable convergence of the protocols.Finally,the simulation results show that the protocols can not only prevent the agents from colliding with obstacles,but also enable the agents to quickly recover the expected formation and achieve consensus of the relative position.展开更多
S-boxes play a central role in the design of symmetric cipher schemes.For stream cipher appli-cations,an s-box should satisfy several criteria such as high nonlinearity,balanceness,correlation immunity,and so on.In th...S-boxes play a central role in the design of symmetric cipher schemes.For stream cipher appli-cations,an s-box should satisfy several criteria such as high nonlinearity,balanceness,correlation immunity,and so on.In this paper,by using disjoint linear codes,a class of s-boxes possessing high nonlinearity and 1st-order correlation immunity is given.It is shown that the constructed correlation immune S-boxes can possess currently best known nonlinearity,which is confirmed by the example 1st-order correlation immune(12,3)s-box with nonlinearity 2000.In addition,two other frameworks concerning the criteria of balanced and resiliency are obtained respectively.展开更多
Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at runtime.In order to improve the utiliz...Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at runtime.In order to improve the utilization of multi-core processors and ensure the real-time performance of the system,it is necessary to adopt a reasonable real-time task allocation method,but the existing methods are only for single-core processors or the performance is too low to be applicable.Aiming at the task allocation problem when mixed real-time tasks are dynamically added,we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF(Virtual Utilization Worst Fit)in multi-core processor.First,a 4-tuple task model is established to describe the fixedpoint task and the sporadic task in a unified manner.Then,a VDS(Virtual Deferral Server)for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is derived.Finally,combined with the analysis of VDS's capacity,VU-WF is proposed,which selects cores in ascending order of virtual utilization for the schedulability test.Experiments show that the overall performance of VU-WF is better than available algorithms,not only has a good schedulable ratio and load balancing but also has the lowest runtime overhead.In a 4-core processor,compared with available algorithms of the same schedulability ratio,the load balancing is improved by 73.9%,and the runtime overhead is reduced by 38.3%.In addition,we also develop a visual multi-core mixed task scheduling simulator RT-MCSS(open source)to facilitate the design and verification of multi-core scheduling for users.As the high performance,VU-WF can be widely used in resource-constrained and safety-critical real-time systems,such as spacecraft,self-driving cars,industrial robots,etc.展开更多
Previous efforts to boost the performance of brain-computer interfaces (BCIs) have predominantly focused on optimizing algorithms for decoding brain signals. However, the untapped potential of leveraging brain plastic...Previous efforts to boost the performance of brain-computer interfaces (BCIs) have predominantly focused on optimizing algorithms for decoding brain signals. However, the untapped potential of leveraging brain plasticity for optimization remains underexplored. In this study, we enhanced the temporal resolution of the human brain in discriminating visual stimuli by eliminating the attentional blink (AB) through color-salient cognitive training, and we confirmed that the mechanism was an attention-based improvement. Using the rapid serial visual presentation (RSVP)-based BCI, we evaluated the behavioral and electroencephalogram (EEG) decoding performance of subjects before and after cognitive training in high target percentage (with AB) and low target percentage (without AB) surveillance tasks, respectively. The results consistently demonstrated significant improvements in the trained subjects. Further analysis indicated that this improvement was attributed to the cognitively trained brain producing more discriminative EEG. Our work highlights the feasibility of cognitive training as a means of brain enhancement to boost BCI performance.展开更多
It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed tha...It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor environment.Here,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless link.We designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor environment.Moreover,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver scenario.We faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.展开更多
Palmprint recognition has attracted considerable attention due to its advantages over other biometric modalities such as fingerprints,in that it is larger in area,richer in information and able to work at a distance.H...Palmprint recognition has attracted considerable attention due to its advantages over other biometric modalities such as fingerprints,in that it is larger in area,richer in information and able to work at a distance.However,the issue of palmprint privacy and security(especially palmprint template protection)remains under-studied.Among the very few research works,most of them only use orientational features of the palmprint with transformation processing,yielding unsatisfactory recognition and protection performance.Thus,this research work proposes a palmprint feature extraction method for palmprint template protection that is fixed-length and ordered in nature,by fusing point features and orientational features.Firstly,dual orientations are extracted and encoded with more accuracy based on the modified finite Radon transform(MFRAT).Then,SURF feature points are extracted and converted to be fixed-length and ordered features.Finally,composite fixed-length ordered features that fuse up the dual orientations and SURF points are transformed using the irreversible transformation of index-of-max(IoM)to generate the revocable palmprint templates.Experiments show that the matching accuracy of the proposed method of fixed-length and ordered point features are superior to all other feature extraction methods on the PolyU and CASIA datasets.It is also demonstrated that the EERs before and after IoM transformation are better than all other representative template protection methods.A thorough security and privacy analysis including brute-force attack,false accept attack,birthday attack,attack via record multiplicity,irreversibility,unlinkability and revocability is also given,which proves that our proposed method has both high performance and security.展开更多
The security of cryptographic algorithms based on integer factorization and discrete logarithm will be threatened by quantum computers in future.Since December 2016,the National Institute of Standards and Technology(N...The security of cryptographic algorithms based on integer factorization and discrete logarithm will be threatened by quantum computers in future.Since December 2016,the National Institute of Standards and Technology(NIST)has begun to solicit post-quantum cryptographic(PQC)algorithms worldwide.CRYSTALS-Kyber was selected as the standard of PQC algorithm after 3 rounds of evaluation.Meanwhile considering the large resource consumption of current implementation,this paper presents a lightweight architecture for ASICs and its implementation on FPGAs for prototyping.In this implementation,a novel compact modular multiplication unit(MMU)and compression/decompression module is proposed to save hardware resources.We put forward a specially optimized schoolbook polynomial multiplication(SPM)instead of number theoretic transform(NTT)core for polynomial multiplication,which can reduce about 74%SLICE cost.We also use signed number representation to save memory resources.In addition,we optimize the hardware implementation of the Hash module,which cuts off about 48%of FF consumption by register reuse technology.Our design can be implemented on Kintex-7(XC7K325T-2FFG900I)FPGA for prototyping,which occupations of 4777/4993 LUTs,2661/2765 FFs,1395/1452 SLICEs,2.5/2.5 BRAMs,and 0/0 DSP respective of client/server side.The maximum clock frequency can reach at 244 MHz.As far as we know,our design consumes the least resources compared with other existing designs,which is very friendly to resource-constrained devices.展开更多
Interference range plays a critical role in wireless network performance,significantly impacting both link reliability and resource utilization.This paper studies the interference range associated with the spatial out...Interference range plays a critical role in wireless network performance,significantly impacting both link reliability and resource utilization.This paper studies the interference range associated with the spatial outage capacity(SOC),which is the maximum density of reliable links of bipolar networks.We establish a recursive equation based on the transmitter's active probability,estab-lishing a link between the interference range and the SOC.The analytical results are then verified through numerical and network simulations.The experimental results indicate that the interfer-ence range may improve the SOC of Poisson bipolar networks while deteriorating the SOC of Poisson cellular networks and random distance bipolar networks.展开更多
基金supported in part by the China National Key R&D Program under Grant(YFA1000500)in part by the Key Research and Developement Program of Shaanxi under Grant(2017DCXL-GY-04-02).
文摘Deep learning based channel state information(CSI)fingerprint indoor localization schemes need to collect massive labeled data samples for training,and the parameters of the deep neural network are used as the fingerprints.However,the indoor environment may change,and the previously constructed fingerprint may not be valid for the changed environment.In order to adapt to the changed environment,it requires to recollect massive amount of labeled data samples and perform the training again,which is labor-intensive and time-consuming.In order to overcome this drawback,in this paper,we propose one novel domain adversarial neural network(DANN)based CSI Fingerprint Indoor Localization(D-Fi)scheme,which only needs the unlabeled data samples from the changed environment to update the fingerprint to adapt to the changed environment.Specifically,the previous environment and changed environment are treated as the source domain and the target domain,respectively.The DANN consists of the classification path and the domain-adversarial path,which share the same feature extractor.In the offline phase,the labeled CSI samples are collected as source domain samples to train the neural network of the classification path,while in the online phase,for the changed environment,only the unlabeled CSI samples are collected as target domain samples to train the neural network of the domainadversarial path to update parameters of the feature extractor.In this case,the feature extractor extracts the common features from both the source domain samples corresponding to the previous environment and the target domain samples corresponding to the changed environment.Experiment results show that for the changed localization environment,the proposed D-Fi scheme significantly outperforms the existing convolutional neural network(CNN)based scheme.
基金funded in part by the National Natural Science Foundation of China(62372355,61972305,61871308)in part by the Natural Science Basic Research Program of Shaanxi(2023-JC-zD-39,2024JC-YBMS-520)in part by the Key Research and Development Program of Shaanxi(2021ZDLGY02-03).
文摘As a computer vision task,object detection algorithms can be applied to various real-world sce-narios.However,efficient algorithms often come with a large number of parameters and high computational complexity.To meet the demand for high-performance object detection algorithms on mobile devices and embedded devices with limited computational resources,we propose a new lightweight object detection algorithm called DLE-YOLO.Firstly,we design a novel backbone called dual-branch lightweight excitation network(DLEN)for feature extraction,which is mainly constructed by dual-branch lightweight excitation units(DLEU).DLEU is stacked with different numbers of dual-branch lightweight excitation blocks(DLEB),which can extract comprehensive features and integrate information between different channels of features.Secondly,in order to enhance the network to capture key feature information in the regions of interest,the attention model HS-coordinate attention(HS-CA)is introduced into the network.Thirdly,the localization loss utilizes SIoU loss to further optimize the accuracy of the bounding box.Our method achieves a mAP value of 46.0%on the MS-COCO dataset,which is a 2%mAP improvement compared to the baseline YOLOv5-m,while bringing a 19.3%reduction in parameter count and a 12.9%decrease in GFLOPs.Furthermore,our method outperforms some advanced lightweight object detection algorithms,validating the effectiveness of our approach.
基金supported by the National Natural Science Foundation of China(62231020)Innovation Capability Support Program of Shaanxi(2024RS-CXTD-01).
文摘The combination of integrated sensing and communication(ISAC)with mobile edge computing(MEC)enhances the overall safety and efficiency for vehicle to everything(V2X)system.However,existing works have not considered the potential impacts on base station(BS)sensing performance when users offload their computational tasks via uplink.This could leave insufficient resources allocated to the sensing tasks,resulting in low sensing performance.To address this issue,we propose a cooperative power,bandwidth and computation resource allocation(RA)scheme in this paper,maximizing the overall utility of Cramer-Rao bound(CRB)for sensing accuracy,computation latency for processing sensing information,and communication and computation latency for computational tasks.To solve the RA problem,a twin delayed deep deterministic policy gradient(TD3)algorithm is adopted to explore and obtain the effective solution of the RA problem.Furthermore,we investigate the performance tradeoff between sensing accuracy and summation of communication latency and computation latency for computational tasks,as well as the relationship between computation latency for processing sensing information and that of computational tasks by numerical simulations.Simulation demonstrates that compared to other benchmark methods,TD3 achieves an average utility improvement of 97.11%and 27.90%in terms of the maximum summation of communication latency and computation latency for computational tasks and improves 3.60 and 1.04 times regarding the maximum computation latency for processing sensing information.
基金supported in part by the Key Research and Development Program of Shaanxi(2024GX-YBXM-019)in part by Open Fund of Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation(CSSAE-2023-007)in part by the UKRI EPSRC(EP/X038971/1).
文摘Enhanced mobile broadband(eMBB)and ultra-reliable low-latency communication(URLLC)are two critical services in 5G mobile networks.While there has been extensive research on their coexistence,few studies have considered the impact of bursty URLLC on their coexistence performance.In this paper,we propose a method to allocate computing and radio resources for coexisting eMBB and bursty URLLC services by preempting both computing queues in the base station(BS)and time-frequency resources at the air interface.Specifically,we first divide the computing resources at the BS into a shared part for both URLLC and eMBB users and an exclusive part only for eMBB users,and propose a queuing mechanism with preemptive-resume priority for accessing the shared computing resources.Furthermore,we propose a preemptive puncturing method and a threshold-based queuing mechanism in the air interface to enable the multiplexing of eMBB and URLLC on shared time-frequency resources.We analytically derive the average queuing delay,average computation delay,and average transmission delay of eMBB and URLLC packets.Based on this analysis,we formulate a mixed-integer nonlinear programming problem to minimize the average delay of URLLC packets while satisfying the average delay and throughput requirements of eMBB by jointly optimizing the eMBB subcarrier allocation,the URLLC subcarrier scheduling and the computing resource allocation.We decompose this problem into three subproblems and solve them alternately using a block coordinate descent algorithm.Numerical results show that our proposed method reduces the outage probability and average delay of URLLC compared to the existing works.
基金supported in part by the National Natural Science Foundation of China(62171354)the key R&D plan of Shaanxi Province(2019ZDLGY07-02)+1 种基金the Fundamental Research Funds for the Central Universities,the National Natural Science Foundation of China(61501347)the“111”project(B08038).
文摘Satellite communications and reconfigurable intelligent surface (RIS) are considered as twopromising technologies that can significantly improve the coverage and energy efficiency of futurewireless communication networks. The satellite communications security is often threatened dueto its broadcasting nature. To enhance the physical layer security (PLS) of satellite communications with channel similarity, an aerial RIS-aided dual full-duplex (DFD-ARIS) cooperative jamming method is presented in this paper. Specifically, unlike the existing works that relied onchannel difference, DFD-ARIS utilizes the channel similarity against the eavesdroppers with thehelp of ARIS. In addition, the power allocation is further studied in conjunction with the phasedesign of RIS to minimize the total power under the constraints of data rate, satellite powerlimitation and secrecy rate. Then, the closed-form solutions are achieved. Simulation results showthat the performance of the proposed scheme is superior to the traditional method.
基金supported in part by the Shaanxi Provincial Key Research and Development Program(2023-ZDLGY-33,2022ZDLGY05-03,2022ZDLGY05-04)in part by the Guangzhou Basic and Applied Basic Research Foundation(2023A04J1740)+1 种基金in part by the Innovation Fund of Xidian University(YJSJ23012)in part by the Fundamental Research Funds for the Central Universities(XJS220116).
文摘With the increasing popularity of civilian unmanned aerial vehicles(UAVs),safety issues arising from unsafe operations and terrorist activities have received growing attention.To address this problem,an accurate classification and positioning system is needed.Considering that UAVs usually use radio frequency(RF)signals for video transmission,in this paper,we design a passive distributed monitoring system that can classify and locate UAVs according to their RF signals.Specifically,three passive receivers are arranged in different locations to receive RF signals.Due to the noncooperation between a UAV and receivers,it is necessary to detect whether there is a UAV signal from the received signals.Hence,convolutional neural network(CNN)is proposed to not only detect the presence of the UAV,but also classify its type.After the UAV signal is detected,the time difference of arrival(TDOA)of the UAV signal arriving at the receiver is estimated by the cross-correlation method to obtain the corresponding distance difference.Finally,the Chan algorithm is used to calculate the location of the UAV.We deploy a distributed system constructed by three software defined radio(SDR)receivers on the campus playground,and conduct extensive experiments in a real wireless environment.The experimental results have successfully validated the proposed system.
文摘In this paper,we introduce a new concept,namelyε-arithmetics,for real vectors of any fixed dimension.The basic idea is to use vectors of rational values(called rational vectors)to approximate vectors of real values of the same dimension withinεrange.For rational vectors of a fixed dimension m,they can form a field that is an mth order extension Q(α)of the rational field Q whereαhas its minimal polynomial of degree m over Q.Then,the arithmetics,such as addition,subtraction,multiplication,and division,of real vectors can be defined by using that of their approximated rational vectors withinεrange.We also define complex conjugate of a real vector and then inner product and convolutions of two real vectors and two real vector sequences(signals)of finite length.With these newly defined concepts for real vectors,linear processing,such as linear filtering,ARMA modeling,and least squares fitting,can be implemented to real vectorvalued signals with real vector-valued coefficients,which will broaden the existing linear processing to scalar-valued signals.
基金supported by Technological Innovation(“Climbing Program”Special Funds,pdjh2024c11603).
文摘In modern Wi-Fi systems,channel state information(CSI)serves as a foundational support for various sensing applications.Currently,existing CSI-based techniques exhibit limitations in terms of environmental adaptability.As such,optimizing the utilization of subcarrier CSI stands as a critical avenue for enhancing sensing performance.Within the OFDM communication framework,this work derives sensing outcomes for both detection and estimation by harnessing the CSI from every individual measured subcarrier,subsequently consolidating these outcomes.When contrasted against results derived from CSI based on specific extraction protocols or those obtained through weighted summation,the methodology introduced in this study offers substantial improvements in CSI-based detection and estimation performance.This approach not only underscores the significance but also serves as a robust exemplar for the comprehensive application of CSI.
基金supported by National Natural Science Foundation of China(U21A20446)Shaanxi Provincial Key R&D Programme,Qinchuangyuan General Window‘Four Chain’Integration Project(2024PT-ZCK-07)Xi'an Municipal Bureau of Science and Technology,Qinchuangyuan General Window Scientific and Technological Achievement Transformation and Incubation Project(23ZCKCGZH0004).
文摘Orthogonal time-frequency space(OTFS)modulation can effectively counter ICI in high-speed mobile scenarios,fully enhance the spectral efficiency of communication systems in high Doppler expansion scenarios,and improve the quality of communication systems.Channel estimation performance serves as a critical evaluation parameter within the OTFS modulation system.In this paper,we propose a multi-scale attention residual neural structure for improved channel estimation of OTFS waveforms in different satellite-ground scenario.Firstly,a multi-scale channel feature extraction module is designed,which applies multi-dimensional feature extraction to the channel matrix,thereby bolstering the capability to capture features at diverse scales.Subsequently,a selfattention mechanism is incorporated to concentrate on subtle yet significant features.The extracted features are then integrated and exploited through a residual convolutional architecture to derive an estimation of the channel matrix.Simulations are conducted using the satellite-ground mobile channel model outlined in 3GPP TR 38.811,with the NTN-TDL-C and NTN-TDL-B channel models representing line of sight(LoS)and non-line of sight(NLoS)conditions,respectively.Results demonstrate that the attention-based approach presented surpasses alternative neural network methodologies in terms of mean squared error(MSE),bit error rate(BER),and complexity,and meets the demands of OTFS channel estimation in satellite-ground scenario.
文摘The integration of communications,sensing and computing(I-CSC)has significant applications in vehicular ad hoc networks(VANETs).A roadside unit(RSU)plays an important role in I-CSC by performing functions such as information transmission and edge computing in vehicular communication.Due to the constraints of limited resources,RSU cannot achieve full coverage and deploying RSUs at key cluster heads of hierarchical structures of road networks is an effective management method.However,direct extracting the hierarchical structures for the resource allocation in VANETs is an open issue.In this paper,we proposed a network-based renormalization method based on information flow and geographical location to hierarchically deploy the RSU on the road networks.The renormalization method is compared with two deployment schemes:genetic algorithm(GA)and memetic framework-based optimal RSU deployment(MFRD),to verify the improvement of communication performance.Our results show that the renormalization method is superior to other schemes in terms of RSU coverage and information reception rate.
基金supported by National Natural Science Foundation of China(62071215,62271243,91963128)National Key Research and Development Program of China(2017YFA0700201)the Joint Fund of Ministry of Education for Equipment Pre-research(8091B032112),Priority Academic Program Development of Jiangsu Higher Education Institutions,Fundamental Research Funds for the Central Universities and Jiangsu Provincial Key Laboratory of Advanced Manipulating Technique of Electromagnetic Wave.
文摘Reconfigurable intelligent surface(RIS)is emerged as a promising technique to solve the challenges faced by future wireless communication networks.Although the most commonly used electrically-controlled RISs can achieve millisecond-scale speed of dynamic switch,they have a large number of microwave circuit elements(such as PIN diodes or varactors)which will bring non-negligible insertion loss,and the complicity of the bias network to electrically addressing each element will increase with the expansion of the RIS aperture.Aiming at further reducing the fabrication cost and power consumption,herein an electromechanical RIS used for sub-6G wireless communication is proposed.The electromechanical RIS is designed with a passive metasurface and step-motor driver modules,providing simultaneous high-efficiency reflection(over 80%)and continuous reflection phase coverage of 360.Through electromechanical control,the RIS system can realize different reflective wavefront shaping,and has been employed in the indoor sub-6G wireless environment demonstrating a maximum signal improvement of 8.3 dB.The proposed electromechanical RIS is particularly useful for wireless signal enhancement in static blind area,and has the obvious advantage of not requiring continuous power supply after the RIS being regulated.Therefore,it greatly reduces the overall cost and power consumption which may have potentials in indoor application scenarios for improving wireless communication performance.
基金supported in part by the Natural Science Foundation of Shaanxi Province(2024JC-YBMS-451,2024JC-YBQN-0398).
文摘Aiming at the consensus of relative position considering obstacle avoidance for fractional-order multi-agent system,a novel distributed control algorithm is proposed in this paper.Firstly,a synthetic error of each agent under the influence of obstacles is introduced.The consensus pro-tocols are designed based on this eror according to sliding mode theory for the order increasing and decreasing,respectively.Then,the Lyapunov function is used to prove the stable convergence of the protocols.Finally,the simulation results show that the protocols can not only prevent the agents from colliding with obstacles,but also enable the agents to quickly recover the expected formation and achieve consensus of the relative position.
基金supported by the National Natural Science Foundation of China(62272360,61972303)Natural Science Basic Research Plan in Shaanxi Province of China(2023-JC-YB-570)the Key Research and Development Program of Shaanxi Province(2021GY-040).
文摘S-boxes play a central role in the design of symmetric cipher schemes.For stream cipher appli-cations,an s-box should satisfy several criteria such as high nonlinearity,balanceness,correlation immunity,and so on.In this paper,by using disjoint linear codes,a class of s-boxes possessing high nonlinearity and 1st-order correlation immunity is given.It is shown that the constructed correlation immune S-boxes can possess currently best known nonlinearity,which is confirmed by the example 1st-order correlation immune(12,3)s-box with nonlinearity 2000.In addition,two other frameworks concerning the criteria of balanced and resiliency are obtained respectively.
文摘Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at runtime.In order to improve the utilization of multi-core processors and ensure the real-time performance of the system,it is necessary to adopt a reasonable real-time task allocation method,but the existing methods are only for single-core processors or the performance is too low to be applicable.Aiming at the task allocation problem when mixed real-time tasks are dynamically added,we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF(Virtual Utilization Worst Fit)in multi-core processor.First,a 4-tuple task model is established to describe the fixedpoint task and the sporadic task in a unified manner.Then,a VDS(Virtual Deferral Server)for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is derived.Finally,combined with the analysis of VDS's capacity,VU-WF is proposed,which selects cores in ascending order of virtual utilization for the schedulability test.Experiments show that the overall performance of VU-WF is better than available algorithms,not only has a good schedulable ratio and load balancing but also has the lowest runtime overhead.In a 4-core processor,compared with available algorithms of the same schedulability ratio,the load balancing is improved by 73.9%,and the runtime overhead is reduced by 38.3%.In addition,we also develop a visual multi-core mixed task scheduling simulator RT-MCSS(open source)to facilitate the design and verification of multi-core scheduling for users.As the high performance,VU-WF can be widely used in resource-constrained and safety-critical real-time systems,such as spacecraft,self-driving cars,industrial robots,etc.
基金supported by the National Natural Science Foundation of China (U19B2030, 61976167, 62301405, 62101416)the Natural Science Basic Research Program of Shaanxi, China (2022JQ-708)Fundamental Research Funds for the Central Universities, China.
文摘Previous efforts to boost the performance of brain-computer interfaces (BCIs) have predominantly focused on optimizing algorithms for decoding brain signals. However, the untapped potential of leveraging brain plasticity for optimization remains underexplored. In this study, we enhanced the temporal resolution of the human brain in discriminating visual stimuli by eliminating the attentional blink (AB) through color-salient cognitive training, and we confirmed that the mechanism was an attention-based improvement. Using the rapid serial visual presentation (RSVP)-based BCI, we evaluated the behavioral and electroencephalogram (EEG) decoding performance of subjects before and after cognitive training in high target percentage (with AB) and low target percentage (without AB) surveillance tasks, respectively. The results consistently demonstrated significant improvements in the trained subjects. Further analysis indicated that this improvement was attributed to the cognitively trained brain producing more discriminative EEG. Our work highlights the feasibility of cognitive training as a means of brain enhancement to boost BCI performance.
基金supported by the National Key Research and Development Program of China(2021YFA1401002,2017YFA0700201,2017YFA0700202 and 2017YFA0700203).
文摘It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor environment.Here,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless link.We designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor environment.Moreover,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver scenario.We faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.
基金funded by the National Natural Science Foundation of China(61906149)the Key Research and Development Program of Shaanxi(2024GX-YBXM-543)+2 种基金the Natural Science Basic Research Program of Shaanxi(2024JC-YBMS-471)the Chunhui Project of the Ministry of Education of China(202200927)the Fundamental Research Funds for the Central Universities(ZYTS24150).
文摘Palmprint recognition has attracted considerable attention due to its advantages over other biometric modalities such as fingerprints,in that it is larger in area,richer in information and able to work at a distance.However,the issue of palmprint privacy and security(especially palmprint template protection)remains under-studied.Among the very few research works,most of them only use orientational features of the palmprint with transformation processing,yielding unsatisfactory recognition and protection performance.Thus,this research work proposes a palmprint feature extraction method for palmprint template protection that is fixed-length and ordered in nature,by fusing point features and orientational features.Firstly,dual orientations are extracted and encoded with more accuracy based on the modified finite Radon transform(MFRAT).Then,SURF feature points are extracted and converted to be fixed-length and ordered features.Finally,composite fixed-length ordered features that fuse up the dual orientations and SURF points are transformed using the irreversible transformation of index-of-max(IoM)to generate the revocable palmprint templates.Experiments show that the matching accuracy of the proposed method of fixed-length and ordered point features are superior to all other feature extraction methods on the PolyU and CASIA datasets.It is also demonstrated that the EERs before and after IoM transformation are better than all other representative template protection methods.A thorough security and privacy analysis including brute-force attack,false accept attack,birthday attack,attack via record multiplicity,irreversibility,unlinkability and revocability is also given,which proves that our proposed method has both high performance and security.
基金supported in part by the Shaanxi Province Key R&D Program(2019ZDLGY12-09)in part by the Higher Education Discipline Innovation 111 project(B16037)+1 种基金in part by the Shaanxi innovation team project(2018TD-007)in part by the China National Natural Science Foundation(62102298).
文摘The security of cryptographic algorithms based on integer factorization and discrete logarithm will be threatened by quantum computers in future.Since December 2016,the National Institute of Standards and Technology(NIST)has begun to solicit post-quantum cryptographic(PQC)algorithms worldwide.CRYSTALS-Kyber was selected as the standard of PQC algorithm after 3 rounds of evaluation.Meanwhile considering the large resource consumption of current implementation,this paper presents a lightweight architecture for ASICs and its implementation on FPGAs for prototyping.In this implementation,a novel compact modular multiplication unit(MMU)and compression/decompression module is proposed to save hardware resources.We put forward a specially optimized schoolbook polynomial multiplication(SPM)instead of number theoretic transform(NTT)core for polynomial multiplication,which can reduce about 74%SLICE cost.We also use signed number representation to save memory resources.In addition,we optimize the hardware implementation of the Hash module,which cuts off about 48%of FF consumption by register reuse technology.Our design can be implemented on Kintex-7(XC7K325T-2FFG900I)FPGA for prototyping,which occupations of 4777/4993 LUTs,2661/2765 FFs,1395/1452 SLICEs,2.5/2.5 BRAMs,and 0/0 DSP respective of client/server side.The maximum clock frequency can reach at 244 MHz.As far as we know,our design consumes the least resources compared with other existing designs,which is very friendly to resource-constrained devices.
基金supported by National Natural Science Foundation of China(62372131)。
文摘Interference range plays a critical role in wireless network performance,significantly impacting both link reliability and resource utilization.This paper studies the interference range associated with the spatial outage capacity(SOC),which is the maximum density of reliable links of bipolar networks.We establish a recursive equation based on the transmitter's active probability,estab-lishing a link between the interference range and the SOC.The analytical results are then verified through numerical and network simulations.The experimental results indicate that the interfer-ence range may improve the SOC of Poisson bipolar networks while deteriorating the SOC of Poisson cellular networks and random distance bipolar networks.
