Despite the superior advantages of specific emitter identification in extracting emitter features from in-phase and quadrature(I/Q)signals,challenges persist due to signal-type confusion and background noise interfere...Despite the superior advantages of specific emitter identification in extracting emitter features from in-phase and quadrature(I/Q)signals,challenges persist due to signal-type confusion and background noise interference.To address those limitations,this paper proposes a multi-channel contrast prediction coding and complex-valued residuals network(MCPC-MCVResNet)framework.This model employs contrast prediction techniques to directly extract discriminative features from electromagnetic signal sequences,effectively capturing both amplitude and phase information within I/Q data.A core innovation of this approach is the sphere space softmax(SS-softmax)loss,which optimizes intra-class clustering density of while establishing well-defined boundaries between distinct emitters.The SS-softmax mechanism significantly enhances the model's capacity to discern subtle variations among radiation emitters.Experimental results demonstrate superior identification accuracy,rapid convergence,and exceptional robustness in low signal-to-noise ratio environments.展开更多
A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum...A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.展开更多
To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer ro...To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.展开更多
This paper presents a link allocation and rate assignment algorithm for multi-channel wireless networks. The objective is to reduce network con-flicts and guarantee the fairness among links. We first design a new netw...This paper presents a link allocation and rate assignment algorithm for multi-channel wireless networks. The objective is to reduce network con-flicts and guarantee the fairness among links. We first design a new network model. With this net-work model, the multi-channel wireless network is divided into several subnets according to the num-ber of channels. Based on this, we present a link allocation algorithm with time complexity O（l^2）to al-locate all links to subnets. This link allocation algo-rithm adopts conflict matrix to minimize the network contention factor. After all links are allocated to subnets, the rate assignment algorithm to maximize a fairness utility in each subnet is presented. The rate assignment algorithm adopts a near-optirml al-gorithm based on dual decomposition and realizes in a distributed way. Simulation results demonstrate that, compared with IEEE 802.11b and slotted see-ded channel hopping algorithm, our algorithm de-creases network conflicts and improves the net-work throughput significantly.展开更多
Wireless Sensor Networks(WSNs)can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions,such as temperature,sound,vibration,pressure and motion etc.WS...Wireless Sensor Networks(WSNs)can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions,such as temperature,sound,vibration,pressure and motion etc.WSNs may comprise thousands of Internet of Things(IoT)devices to sense and collect data from its surrounding,process the data and take an automated and mechanized decision.On the other side the proliferation of these devices will soon cause radio spectrum shortage.So,to facilitate these networks,we integrate Cognitive Radio(CR)functionality in these networks.CR can sense the unutilized spectrum of licensed users and then use these empty bands when required.In order to keep the IoT nodes functional all time,continuous energy is required.For this reason the energy harvested techniques are preferred in IoT networks.Mainly it is preferred to harvest Radio Frequency(RF)energy in the network.In this paper a region based multi-channel architecture is proposed.In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region.The Secondary User(SU)that are the licensed user is IoT enabled with Cognitive Radio(CR)techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy.To harvest energy efficiently and to reduce the energy consumption during sensing,the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel.From the experimental analysis,it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel.We also show that channel load can be highly reduced and channel utilization is proved to be more proficient.Thus,this proves the proposed architecture cost-effective and energy-efficient.展开更多
Cognitive radio,which is capable of enabling dynamic spectrum access,is a promising technology in future wireless communication.The feasibility of cognitive radio network greatly depends on the energy efciency and rel...Cognitive radio,which is capable of enabling dynamic spectrum access,is a promising technology in future wireless communication.The feasibility of cognitive radio network greatly depends on the energy efciency and reliability of spectrum sensing technology.In this paper,spectrum sensing in cognitive ad-hoc network(CAN)with wide-band dynamic spectrum is considered.A cognitive cluster head(CCH)is set and responsible for dividing the wide-band spectrum into multiple sub-channels;it can either sense sub-channels in a centralized manner,or make use of sensing modules to sense sub-channels in a distributed manner.Then cognitive users(CUs)can get sensing results and access to the available sub-channel.We take the cost of control message into consideration and formulate the energy consumption of CAN in terms of sub-channel sampling rate and whole-band sensing time.We define energy efciency intuitively and solve the energy efciency optimization problem with sensing reliability constraints by constructing a parametric problem and obtain the optimal sampling rate and the wholeband sensing time.Power dissipation model of a practical A/D convertor(ADC)is introduced,and numerical results are given to show the energy efciency performance of two diferent sensing manners.展开更多
In this paper, the capacity of multi-channel, multi-hop ad hoc network is evaluated.In particular, the performance of multi-hop ad hoc network with single channel IEEE 802.11MAC utilizing different topologies is shown...In this paper, the capacity of multi-channel, multi-hop ad hoc network is evaluated.In particular, the performance of multi-hop ad hoc network with single channel IEEE 802.11MAC utilizing different topologies is shown. Also the scaling laws of throughputs for large-scale ad hoc networks and the theoretical guaranteed throughput bounds for multi-channel gridtopology systems are proposed. The results presented in this work will help researchers to choosethe proper parameter settings in evaluation of protocols for multi-hop ad hoc networks.展开更多
Recent advances in wireless sensor technology have enabled simultaneous exploitation of multiple channels in wireless sensor systems. In this paper, a novel time synchronization algorithm is proposed for multi- channe...Recent advances in wireless sensor technology have enabled simultaneous exploitation of multiple channels in wireless sensor systems. In this paper, a novel time synchronization algorithm is proposed for multi- channel Wireless Sensor Networks (WSNs) called Multi-Channel Time Synchronization (MCTS) protocol. Time synchronization is critical for many WSN applications and enables efficient communications between sensor nodes along with intelligent spectrum access. Contrary to many existing protocols that do not exploit multi-channel communications, the protocol takes advantage of potential multiple channels and distributes the synchronization of different nodes to distinct channels and thus, reduces the convergence time of synchronization processes significantly.展开更多
A channel assignment algorithm with awareness of link traffic is proposed in multi-radio multi-channel wireless mesh networks. First, the physical interference model based on the signal-to-interference-plus-noise rati...A channel assignment algorithm with awareness of link traffic is proposed in multi-radio multi-channel wireless mesh networks. First, the physical interference model based on the signal-to-interference-plus-noise ratio and successful transmission condition is described. The model is more suitable for a wireless communication environment than other existing models. Secondly, a pure integer quadratic programming （PIQP） model is used to solve the channel assignment problem and improve the capacity of wireless mesh networks. Consequently, a traffic- aware static channel assignment algorithm（TASC） is designed. The algorithm adopts some network parameters, including the network connectivity, the limitation of the number of radios and the successful transmission conditions in wireless communications. The TASC algorithm can diminish network interference and increase the efficiency of channel assignment while keeping the connectivity of the network. Finally, the feasibility and effectivity of the channel assignment solution are illustrated by the simulation results. Compared witb similar algorithms, the proposed algorithm can increase the capacity of WMNs.展开更多
针对水稻病虫害检测精度低、速度慢、模型复杂度高、部署困难等问题,改进了YOLOv4目标检测算法,结合轻量化GhostNet网络,提出了一种基于改进的YOLOv4-GhostNet水稻病虫害识别方法:1)利用幻象模块代替普通卷积结构,替换主干特征提取网络C...针对水稻病虫害检测精度低、速度慢、模型复杂度高、部署困难等问题,改进了YOLOv4目标检测算法,结合轻量化GhostNet网络,提出了一种基于改进的YOLOv4-GhostNet水稻病虫害识别方法:1)利用幻象模块代替普通卷积结构,替换主干特征提取网络CSPDarkNet53,构建GhostNet模块进行图像的特征提取;2)改进YOLOv4网络的加强特征提取部分PANet结构;3)结合迁移学习与YOLOv4网络训练技巧。通过试验将YOLOv4及其MobileNet系列轻量化网络与Faster-RCNN系列网络和SSD系列网络进行对比,结果表明,改进的YOLOv4-GhostNet模型平均准确率达到79.38%,检测速度可达1 s 34.51帧,模型权重大小缩减为42.45 MB,在保持检测精度达到较高水平的同时模型参数量大幅度降低,适用于部署在计算能力不足的嵌入式设备上。展开更多
The active Lamb wave and piezoelectric transducer(PZT)-based structural health monitoring(SHM)technology is a kind of efficient approach to estimate the health state of aircraft structure.In practical applications,PZT...The active Lamb wave and piezoelectric transducer(PZT)-based structural health monitoring(SHM)technology is a kind of efficient approach to estimate the health state of aircraft structure.In practical applications,PZT networks are needed to monitor large scale structures.Scanning many of the different PZT actuator-sensor channels within these PZT networks to achieve on-line SHM task is important.Based on a peripheral component interconnect extensions for instrumentation(PXI)platform,an active Lamb wave and PZT network-based integrated multi-channel scanning system(PXI-ISS)is developed for the purpose of practical applications of SHM,which is compact and portable,and can scan large numbers of actuator-sensor channels and perform damage assessing automatically.A PXI-based 4 channels gain-programmable charge amplifier,an external scanning module with 276 actuator-sensor channels and integrated SHM software are proposed and discussed in detail.The experimental research on a carbon fiber composite wing box of an unmanned aerial vehicle(UAV)for verifying the functions of the PXI-ISS is mainly discussed,including the design of PZTs layer,the method of excitation frequency selection,functional test of damage imaging,stability test of the PXI-ISS,and the loading effect on signals.The experimental results have verified the stability and damage functions of this system.展开更多
Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases.This study aims to develop an efficient deep learning based scheme for correctly identifying sleep ...Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases.This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography(EEG),electrocardiogram(ECG),electromyogram(EMG),and electrooculogram(EOG).Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods.Traditional hand-crafted feature extraction methods choose features manually from raw data,which is tedious,and these features are limited in their ability to balance efficiency and accuracy.Moreover,most of the existing works on sleep staging are either single channel(a single-lead EEG may not contain enough information)or only EEG signal based which can not reveal more complicated physical features for reliable classification of various sleep stages.This study proposes an approach to combine Convolutional Neural Networks(CNNs)and Gated Recurrent Units(GRUs)that can discover hidden features from multi-biological signal data to recognize the different sleep stages efficiently.In the proposed scheme,the CNN is designed to extract concealed features from the multi-biological signals,and the GRU is employed to automatically learn the transition rules among different sleep stages.After that,the softmax layers are used to classify various sleep stages.The proposed method was tested on two publicly available databases:Sleep Heart Health Study(SHHS)and St.Vincent’s University Hospital/University College Dublin Sleep Apnoea(UCDDB).The experimental results reveal that the proposed model yields better performance compared to state-of-the-art works.Our proposed scheme will assist in building a new system to deal with multi-channel or multi-modal signal processing tasks in various applications.展开更多
Existing multi-channel Medium Access Control (MAC) protocols have been demonstrated to significantly increase wireless network performance compared to single channel MAC protocols. Traditionally, the channelization st...Existing multi-channel Medium Access Control (MAC) protocols have been demonstrated to significantly increase wireless network performance compared to single channel MAC protocols. Traditionally, the channelization structure in IEEE 802.11 based wireless networks is pre-configured, and the entire available spectrum is divided into subchannels and equal channel widths. In contrast, this paper presents a Traffic-Aware Channelization MAC (TAC-MAC) protocol for wireless ad hoc networks, where each node is equipped with a single half duplex transceiver. TAC-MAC works in a distributed, fine-grai-ned manner, which dynamically divides variable-width subchannels and allocates subchannel width based on the Orthogonal Frequency Division Multiplexing (OFDM) technique according to the traffic demands of nodes. Simulations show that the TAC-MAC can significantly improve network throughput and reduce packet delay compared with both fixed-width multi-channel MAC and single channel 802.11 protocols, which illustrates a new paradigm for high-efficient multi-channel MAC design in wireless ad hoc networks.展开更多
In this paper,we utilized the deep convolutional neural network D-LinkNet,a model for semantic segmentation,to analyze the Himawari-8 satellite data captured from 16 channels at a spatial resolution of 0.5 km,with a f...In this paper,we utilized the deep convolutional neural network D-LinkNet,a model for semantic segmentation,to analyze the Himawari-8 satellite data captured from 16 channels at a spatial resolution of 0.5 km,with a focus on the area over the Yellow Sea and the Bohai Sea(32°-42°N,117°-127°E).The objective was to develop an algorithm for fusing and segmenting multi-channel images from geostationary meteorological satellites,specifically for monitoring sea fog in this region.Firstly,the extreme gradient boosting algorithm was adopted to evaluate the data from the 16 channels of the Himawari-8 satellite for sea fog detection,and we found that the top three channels in order of importance were channels 3,4,and 14,which were fused into false color daytime images,while channels 7,13,and 15 were fused into false color nighttime images.Secondly,the simple linear iterative super-pixel clustering algorithm was used for the pixel-level segmentation of false color images,and based on super-pixel blocks,manual sea-fog annotation was performed to obtain fine-grained annotation labels.The deep convolutional neural network D-LinkNet was built on the ResNet backbone and the dilated convolutional layers with direct connections were added in the central part to form a string-and-combine structure with five branches having different depths and receptive fields.Results show that the accuracy rate of fog area(proportion of detected real fog to detected fog)was 66.5%,the recognition rate of fog zone(proportion of detected real fog to real fog or cloud cover)was 51.9%,and the detection accuracy rate(proportion of samples detected correctly to total samples)was 93.2%.展开更多
In order to achieve low-latency and high-reliability data gathering in heterogeneous wireless sensor networks(HWSNs),the problem of multi-channel-based data gathering with minimum latency(MCDGML),which associates with...In order to achieve low-latency and high-reliability data gathering in heterogeneous wireless sensor networks(HWSNs),the problem of multi-channel-based data gathering with minimum latency(MCDGML),which associates with construction of data gathering trees,channel allocation,power assignment of nodes and link scheduling,is formulated as an optimization problem in this paper.Then,the optimization problem is proved to be NP-hard.To make the problem tractable,firstly,a multi-channel-based low-latency(MCLL)algorithm that constructs data gathering trees is proposed by optimizing the topology of nodes.Secondly,a maximum links scheduling(MLS)algorithm is proposed to further reduce the latency of data gathering,which ensures that the signal to interference plus noise ratio(SINR)of all scheduled links is not less than a certain threshold to guarantee the reliability of links.In addition,considering the interruption problem of data gathering caused by dead nodes or failed links,a robust mechanism is proposed by selecting certain assistant nodes based on the defined one-hop weight.A number of simulation results show that our algorithms can achieve a lower data gathering latency than some comparable data gathering algorithms while guaranteeing the reliability of links,and a higher packet arrival rate at the sink node can be achieved when the proposed algorithms are performed with the robust mechanism.展开更多
Wireless Mesh Network has drawn much attention due to wide area service coverage with low system cost and being easy to install.However,WMN suffers from high bit error rate,which provides different link capacity among...Wireless Mesh Network has drawn much attention due to wide area service coverage with low system cost and being easy to install.However,WMN suffers from high bit error rate,which provides different link capacity among wireless mesh routers.The conventional routing metrics select the path based on link quality.The link with the best quality is preferred as the data transmission path,and thus all nodes likely select the same link,which leads to network performance degradation.This paper proposes a routing metric that considers the available bandwidth and the number of nodes suffering congestion in the path.It is confirmed that the proposed method provides higher network performance of reduced delay,reduced packet loss and increased throughput than conventional routing metrics.展开更多
基金supported by the National Natural Science Foundation of China(62201602)。
文摘Despite the superior advantages of specific emitter identification in extracting emitter features from in-phase and quadrature(I/Q)signals,challenges persist due to signal-type confusion and background noise interference.To address those limitations,this paper proposes a multi-channel contrast prediction coding and complex-valued residuals network(MCPC-MCVResNet)framework.This model employs contrast prediction techniques to directly extract discriminative features from electromagnetic signal sequences,effectively capturing both amplitude and phase information within I/Q data.A core innovation of this approach is the sphere space softmax(SS-softmax)loss,which optimizes intra-class clustering density of while establishing well-defined boundaries between distinct emitters.The SS-softmax mechanism significantly enhances the model's capacity to discern subtle variations among radiation emitters.Experimental results demonstrate superior identification accuracy,rapid convergence,and exceptional robustness in low signal-to-noise ratio environments.
基金The National High Technology Research and Development Program of China(863 Program)(No.2013AA013601)Prospective Research Project on Future Netw orks of Jiangsu Future Netw orks Innovation Institute(No.BY2013095-1-18)
文摘A channel allocation algorithm based on the maximum independent set is proposed to decrease network conflict and improve network performance. First, a channel allocation model is formulated and a series of the maximum independent sets （MISs） are obtained from a contention graph by the proposed approximation algorithm with low complexity. Then, a weighted contention graph is obtained using the number of contention vertices between two MISs as a weighted value. Links are allocated to channels by the weighted contention graph to minimize conflicts between independent sets. Finally, after channel allocation, each node allocates network interface cards （NICs） to links that are allocated channels according to the queue lengths of NICs. Simulations are conducted to evaluate the proposed algorithm. The results show that the proposed algorithm significantly improves the network throughput and decreases the end to end delay.
基金supported by the National Natural Science Foundationof China (60873195 61070220)+3 种基金the Natural Science Foundation of Anhui Province (070412049)the Outstanding Young Teacher Foundation of Anhui Higher Education Institutions of China (2009SQRZ167)the Natural Science Foundation of Anhui Higher Education Institutions of China (KJ2009B114)the Open Project Program of Engineering Research Center of Safety Critical Industry Measure and Control Technology (SCIMCT0802)
文摘To study multi-radio multi-channel （MR-MC） Ad Hoc networks based on 802.11, an efficient cross-layer routing protocol with the function of joint channel assignment, called joint channel assignment and cross-layer routing （JCACR）, is presented. Firstly, this paper introduces a new concept called channel utilization percentage （CUP）, which is for measuring the contention level of different channels in a node’s neighborhood, and deduces its optimal value for determining whether a channel is overloaded or not. Then, a metric parameter named channel selection metric （CSM） is designed, which actually reffects not only the channel status but also corresponding node’s capacity to seize it. JCACR evaluates channel assignment by CSM, performs a local optimization by assigning each node a channel with the smaller CSM value, and changes the working channel dynamically when the channel is overloaded. Therefore, the network load balancing can be achieved. In addition, simulation shows that, when compared with the protocol of weighted cumulative expected transfer time （WCETT）, the new protocol can improve the network throughput and reduce the end-to-end average delay with fewer overheads.
基金This work was supported by the National Natural Science Foundation of China under Cxant No. 60902010 the Research Fund of State Key Laboratory of Mobile Communications un-der Crant No. 2012A03.
文摘This paper presents a link allocation and rate assignment algorithm for multi-channel wireless networks. The objective is to reduce network con-flicts and guarantee the fairness among links. We first design a new network model. With this net-work model, the multi-channel wireless network is divided into several subnets according to the num-ber of channels. Based on this, we present a link allocation algorithm with time complexity O（l^2）to al-locate all links to subnets. This link allocation algo-rithm adopts conflict matrix to minimize the network contention factor. After all links are allocated to subnets, the rate assignment algorithm to maximize a fairness utility in each subnet is presented. The rate assignment algorithm adopts a near-optirml al-gorithm based on dual decomposition and realizes in a distributed way. Simulation results demonstrate that, compared with IEEE 802.11b and slotted see-ded channel hopping algorithm, our algorithm de-creases network conflicts and improves the net-work throughput significantly.
文摘Wireless Sensor Networks(WSNs)can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions,such as temperature,sound,vibration,pressure and motion etc.WSNs may comprise thousands of Internet of Things(IoT)devices to sense and collect data from its surrounding,process the data and take an automated and mechanized decision.On the other side the proliferation of these devices will soon cause radio spectrum shortage.So,to facilitate these networks,we integrate Cognitive Radio(CR)functionality in these networks.CR can sense the unutilized spectrum of licensed users and then use these empty bands when required.In order to keep the IoT nodes functional all time,continuous energy is required.For this reason the energy harvested techniques are preferred in IoT networks.Mainly it is preferred to harvest Radio Frequency(RF)energy in the network.In this paper a region based multi-channel architecture is proposed.In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region.The Secondary User(SU)that are the licensed user is IoT enabled with Cognitive Radio(CR)techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy.To harvest energy efficiently and to reduce the energy consumption during sensing,the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel.From the experimental analysis,it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel.We also show that channel load can be highly reduced and channel utilization is proved to be more proficient.Thus,this proves the proposed architecture cost-effective and energy-efficient.
基金the National Natural Science Foundation of China(Nos.61102052 and 60972050)the National Basic Research Program(973)of China(No.2010CB731803)+1 种基金the China Ministry of Education Fok Ying Tung Fund(No.122002)the National Science and Technology Major Project of China(Nos.2010ZX03002-007-01 and 2010ZX03003-001-01)
文摘Cognitive radio,which is capable of enabling dynamic spectrum access,is a promising technology in future wireless communication.The feasibility of cognitive radio network greatly depends on the energy efciency and reliability of spectrum sensing technology.In this paper,spectrum sensing in cognitive ad-hoc network(CAN)with wide-band dynamic spectrum is considered.A cognitive cluster head(CCH)is set and responsible for dividing the wide-band spectrum into multiple sub-channels;it can either sense sub-channels in a centralized manner,or make use of sensing modules to sense sub-channels in a distributed manner.Then cognitive users(CUs)can get sensing results and access to the available sub-channel.We take the cost of control message into consideration and formulate the energy consumption of CAN in terms of sub-channel sampling rate and whole-band sensing time.We define energy efciency intuitively and solve the energy efciency optimization problem with sensing reliability constraints by constructing a parametric problem and obtain the optimal sampling rate and the wholeband sensing time.Power dissipation model of a practical A/D convertor(ADC)is introduced,and numerical results are given to show the energy efciency performance of two diferent sensing manners.
文摘In this paper, the capacity of multi-channel, multi-hop ad hoc network is evaluated.In particular, the performance of multi-hop ad hoc network with single channel IEEE 802.11MAC utilizing different topologies is shown. Also the scaling laws of throughputs for large-scale ad hoc networks and the theoretical guaranteed throughput bounds for multi-channel gridtopology systems are proposed. The results presented in this work will help researchers to choosethe proper parameter settings in evaluation of protocols for multi-hop ad hoc networks.
基金supported in part by TEKES(Finnish Funding Agency for Technology and Innovation)as part of the Wireless Sensor and Actuator Networks for Measurement and Control(WiSA-II)programby the U.S.Army Research Office under Cooperative Agreement W911NF-04-2-0054.
文摘Recent advances in wireless sensor technology have enabled simultaneous exploitation of multiple channels in wireless sensor systems. In this paper, a novel time synchronization algorithm is proposed for multi- channel Wireless Sensor Networks (WSNs) called Multi-Channel Time Synchronization (MCTS) protocol. Time synchronization is critical for many WSN applications and enables efficient communications between sensor nodes along with intelligent spectrum access. Contrary to many existing protocols that do not exploit multi-channel communications, the protocol takes advantage of potential multiple channels and distributes the synchronization of different nodes to distinct channels and thus, reduces the convergence time of synchronization processes significantly.
基金The National Basic Research Program of China(973Program)(No.2009CB320501)the Natural Science Foundation of Jiangsu Province(No.BK2010414)+1 种基金China Postdoctoral Science Foundation(No.20100480071)Specialized Research Fund for the Doctoral Program of Higher Education(No.20090092120029)
文摘A channel assignment algorithm with awareness of link traffic is proposed in multi-radio multi-channel wireless mesh networks. First, the physical interference model based on the signal-to-interference-plus-noise ratio and successful transmission condition is described. The model is more suitable for a wireless communication environment than other existing models. Secondly, a pure integer quadratic programming （PIQP） model is used to solve the channel assignment problem and improve the capacity of wireless mesh networks. Consequently, a traffic- aware static channel assignment algorithm（TASC） is designed. The algorithm adopts some network parameters, including the network connectivity, the limitation of the number of radios and the successful transmission conditions in wireless communications. The TASC algorithm can diminish network interference and increase the efficiency of channel assignment while keeping the connectivity of the network. Finally, the feasibility and effectivity of the channel assignment solution are illustrated by the simulation results. Compared witb similar algorithms, the proposed algorithm can increase the capacity of WMNs.
文摘针对水稻病虫害检测精度低、速度慢、模型复杂度高、部署困难等问题,改进了YOLOv4目标检测算法,结合轻量化GhostNet网络,提出了一种基于改进的YOLOv4-GhostNet水稻病虫害识别方法:1)利用幻象模块代替普通卷积结构,替换主干特征提取网络CSPDarkNet53,构建GhostNet模块进行图像的特征提取;2)改进YOLOv4网络的加强特征提取部分PANet结构;3)结合迁移学习与YOLOv4网络训练技巧。通过试验将YOLOv4及其MobileNet系列轻量化网络与Faster-RCNN系列网络和SSD系列网络进行对比,结果表明,改进的YOLOv4-GhostNet模型平均准确率达到79.38%,检测速度可达1 s 34.51帧,模型权重大小缩减为42.45 MB,在保持检测精度达到较高水平的同时模型参数量大幅度降低,适用于部署在计算能力不足的嵌入式设备上。
基金National High-tech Research and Development Program of China(2007AA03Z117)National Natural Science Foundation of China(50830201)Graduate Education Innovation Project of Nanjing University of Aeronautics and Astronautics of China(BCXJ09-01).
文摘The active Lamb wave and piezoelectric transducer(PZT)-based structural health monitoring(SHM)technology is a kind of efficient approach to estimate the health state of aircraft structure.In practical applications,PZT networks are needed to monitor large scale structures.Scanning many of the different PZT actuator-sensor channels within these PZT networks to achieve on-line SHM task is important.Based on a peripheral component interconnect extensions for instrumentation(PXI)platform,an active Lamb wave and PZT network-based integrated multi-channel scanning system(PXI-ISS)is developed for the purpose of practical applications of SHM,which is compact and portable,and can scan large numbers of actuator-sensor channels and perform damage assessing automatically.A PXI-based 4 channels gain-programmable charge amplifier,an external scanning module with 276 actuator-sensor channels and integrated SHM software are proposed and discussed in detail.The experimental research on a carbon fiber composite wing box of an unmanned aerial vehicle(UAV)for verifying the functions of the PXI-ISS is mainly discussed,including the design of PZTs layer,the method of excitation frequency selection,functional test of damage imaging,stability test of the PXI-ISS,and the loading effect on signals.The experimental results have verified the stability and damage functions of this system.
文摘Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases.This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography(EEG),electrocardiogram(ECG),electromyogram(EMG),and electrooculogram(EOG).Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods.Traditional hand-crafted feature extraction methods choose features manually from raw data,which is tedious,and these features are limited in their ability to balance efficiency and accuracy.Moreover,most of the existing works on sleep staging are either single channel(a single-lead EEG may not contain enough information)or only EEG signal based which can not reveal more complicated physical features for reliable classification of various sleep stages.This study proposes an approach to combine Convolutional Neural Networks(CNNs)and Gated Recurrent Units(GRUs)that can discover hidden features from multi-biological signal data to recognize the different sleep stages efficiently.In the proposed scheme,the CNN is designed to extract concealed features from the multi-biological signals,and the GRU is employed to automatically learn the transition rules among different sleep stages.After that,the softmax layers are used to classify various sleep stages.The proposed method was tested on two publicly available databases:Sleep Heart Health Study(SHHS)and St.Vincent’s University Hospital/University College Dublin Sleep Apnoea(UCDDB).The experimental results reveal that the proposed model yields better performance compared to state-of-the-art works.Our proposed scheme will assist in building a new system to deal with multi-channel or multi-modal signal processing tasks in various applications.
基金supported by the National Natural Science Foundation of China under Grant No. 61002032the Doctoral Fund of Ministry of Education of China under Grant No. 20094307110004
文摘Existing multi-channel Medium Access Control (MAC) protocols have been demonstrated to significantly increase wireless network performance compared to single channel MAC protocols. Traditionally, the channelization structure in IEEE 802.11 based wireless networks is pre-configured, and the entire available spectrum is divided into subchannels and equal channel widths. In contrast, this paper presents a Traffic-Aware Channelization MAC (TAC-MAC) protocol for wireless ad hoc networks, where each node is equipped with a single half duplex transceiver. TAC-MAC works in a distributed, fine-grai-ned manner, which dynamically divides variable-width subchannels and allocates subchannel width based on the Orthogonal Frequency Division Multiplexing (OFDM) technique according to the traffic demands of nodes. Simulations show that the TAC-MAC can significantly improve network throughput and reduce packet delay compared with both fixed-width multi-channel MAC and single channel 802.11 protocols, which illustrates a new paradigm for high-efficient multi-channel MAC design in wireless ad hoc networks.
基金National Key R&D Program of China(2021YFC3000905)Open Research Program of the State Key Laboratory of Severe Weather(2022LASW-B09)National Natural Science Foundation of China(42375010)。
文摘In this paper,we utilized the deep convolutional neural network D-LinkNet,a model for semantic segmentation,to analyze the Himawari-8 satellite data captured from 16 channels at a spatial resolution of 0.5 km,with a focus on the area over the Yellow Sea and the Bohai Sea(32°-42°N,117°-127°E).The objective was to develop an algorithm for fusing and segmenting multi-channel images from geostationary meteorological satellites,specifically for monitoring sea fog in this region.Firstly,the extreme gradient boosting algorithm was adopted to evaluate the data from the 16 channels of the Himawari-8 satellite for sea fog detection,and we found that the top three channels in order of importance were channels 3,4,and 14,which were fused into false color daytime images,while channels 7,13,and 15 were fused into false color nighttime images.Secondly,the simple linear iterative super-pixel clustering algorithm was used for the pixel-level segmentation of false color images,and based on super-pixel blocks,manual sea-fog annotation was performed to obtain fine-grained annotation labels.The deep convolutional neural network D-LinkNet was built on the ResNet backbone and the dilated convolutional layers with direct connections were added in the central part to form a string-and-combine structure with five branches having different depths and receptive fields.Results show that the accuracy rate of fog area(proportion of detected real fog to detected fog)was 66.5%,the recognition rate of fog zone(proportion of detected real fog to real fog or cloud cover)was 51.9%,and the detection accuracy rate(proportion of samples detected correctly to total samples)was 93.2%.
基金This work was supported by the Natural Science Foun-dation of China(Nos.U1334210 and 61374059).
文摘In order to achieve low-latency and high-reliability data gathering in heterogeneous wireless sensor networks(HWSNs),the problem of multi-channel-based data gathering with minimum latency(MCDGML),which associates with construction of data gathering trees,channel allocation,power assignment of nodes and link scheduling,is formulated as an optimization problem in this paper.Then,the optimization problem is proved to be NP-hard.To make the problem tractable,firstly,a multi-channel-based low-latency(MCLL)algorithm that constructs data gathering trees is proposed by optimizing the topology of nodes.Secondly,a maximum links scheduling(MLS)algorithm is proposed to further reduce the latency of data gathering,which ensures that the signal to interference plus noise ratio(SINR)of all scheduled links is not less than a certain threshold to guarantee the reliability of links.In addition,considering the interruption problem of data gathering caused by dead nodes or failed links,a robust mechanism is proposed by selecting certain assistant nodes based on the defined one-hop weight.A number of simulation results show that our algorithms can achieve a lower data gathering latency than some comparable data gathering algorithms while guaranteeing the reliability of links,and a higher packet arrival rate at the sink node can be achieved when the proposed algorithms are performed with the robust mechanism.
基金supported by the ubiquitous Computing and Network(UCN)Projectthe Ministry of Knowledge and Econ-omy(MKE)Knowledge and Economy Frontier R&DProgramin Korea as a result of UCN′s subproject10C2-C1-20Ssupported by the MKE(The Ministry of Knowledge Economy),Korea,under the Convergence-ITRC(Convergence Infor mation Technology Research Center)support program(NIPA-2011-C6150-1101-0004)
文摘Wireless Mesh Network has drawn much attention due to wide area service coverage with low system cost and being easy to install.However,WMN suffers from high bit error rate,which provides different link capacity among wireless mesh routers.The conventional routing metrics select the path based on link quality.The link with the best quality is preferred as the data transmission path,and thus all nodes likely select the same link,which leads to network performance degradation.This paper proposes a routing metric that considers the available bandwidth and the number of nodes suffering congestion in the path.It is confirmed that the proposed method provides higher network performance of reduced delay,reduced packet loss and increased throughput than conventional routing metrics.
