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3rd EAI International Conference on Artificial Intelligence for communications and Networks, AICON 2021

作者： Zhu, Huijie Liu, Mingqian Li, Ming Gao, Xiuhui Science and Technology on Communication Information Security Control Laboratory The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China State Key Laboratory of Integrated Service Networks Xidian University Shaanxi Xi’an710071 China State 722 Factory Guangxi Guilin541001 China

ISBN: (纸本)9783030901950

This paper proposes a novel passive location parameter estimator using multiple satellites for moving aerial targets. Specifically, we consider target detection in the ground dual receiver system, which is divided into reference channel and monitoring channel. The reference channel receives the direct wave signals from multiple external emitters, and the monitoring channel receives the echo signals reflected by the target. We propose a target detection method based on a generalized likelihood ratio (GLRT). This detection algorithm is robust to the reference channel noise. Extensive simulations are conducted to evaluate the performance of the algorithm under various network settings. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Satellites

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Passive Target Detection Based on Rao Using Multi-satellite Illumination 3rd

Passive Target Detection Based on Rao Using Multi-satellite ...

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3rd EAI International Conference on Artificial Intelligence for communications and Networks, AICON 2021

ISBN: (纸本)9783030901950

In this paper, hypotheses of target detection features is proposed when constructing the signal model. Under this condition, the Rao detection method is extended to weak echo signal detection using multi-satellite illumination. Furthermore, a multi-satellite weak echo signal detection algorithm is proposed based on Rao detection. When the noise variance is unknown, the Rao detector is designed according to the existence of an interfering target. Moreover, the detector’ detection thresholds are obtained given the false alarm probability, respectively. Finally, we evaluate the Rao detection performance in different situations with extensive simulations. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Satellites

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Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios

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China communications 2020年第2期17卷 138-148页

作者： Shilian Zheng Shichuan Chen Peihan Qi Huaji Zhou Xiaoniu Yang Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033China State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of ChinaXidian UniversityXi’an 710071China

Spectrum sensing is a key technology for cognitive *** present spectrum sensing as a classification problem and propose a sensing method based on deep learning *** normalize the received signal power to overcome the effects of noise power *** train the model with as many types of signals as possible as well as noise data to enable the trained network model to adapt to untrained new *** also use transfer learning strategies to improve the performance for real-world *** experiments are conducted to evaluate the performance of this *** simulation results show that the proposed method performs better than two traditional spectrum sensing methods,i.e.,maximum-minimum eigenvalue ratio-based method and frequency domain entropy-based *** addition,the experimental results of the new untrained signal types show that our method can adapt to the detection of these new ***,the real-world signal detection experiment results show that the detection performance can be further improved by transfer ***,experiments under colored noise show that our proposed method has superior detection performance under colored noise,while the traditional methods have a significant performance degradation,which further validate the superiority of our method.

关键词： spectrum sensing deep learning convolutional neural network cognitive radio spectrum management

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Unsupervised Feature Enrichment and Fidelity Preservation Learning Framework for Skeleton-based Action Recognition

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Li, Chuankun Li, Shuai Gao, Yanbo Gao, Xingyu Chen, Ping Li, Jian Li, Wanqing North University of China State Key Laboratory of Dynamic Testing Technology School of Information and Communication Engineering Taiyuan030051 China Shandong University School of Control Science and Engineering School of Software Jinan250100 China Chinese Academy of Sciences Institute of Microelectronics Beijing100029 China University of Wollongong Advanced Multimedia Research Lab WollongongNSW2522 Australia

Unsupervised skeleton-based action recognition has achieved remarkable progress recently. Existing unsupervised learning methods suffer from severe overfitting problem, and thus small networks are used, significantly reducing the representation capability. To address this problem, the overfitting mechanism behind the unsupervised learning for skeleton-based action recognition is first investigated. It is observed that skeleton is already a relatively high-level and low-dimension feature, but not in the same manifold as the features for action recognition. Simply applying the existing unsupervised learning method tends to produce features that discriminate the different samples rather than action classes, resulting in the overfitting problem. To address this problem, this paper proposes an Unsupervised spatial-temporal Feature Enrichment and Fidelity Preservation (U-FEFP) learning framework to generate rich distributed features that contain all the information of a skeleton sample. A spatial-temporal feature transformation subnetwork is developed using channel-wise topology refinement graph convolutional block and graph convolutional gated recurrent unit block as the basic feature extraction network. The unsupervised Bootstrap Your Own Latent-based learning is utilized to generate rich distributed features, and the unsupervised pretext task-based learning is employed to preserve the information contained in the skeleton. The two unsupervised learning ways are collab.rated as U-FEFP to produce robust and discriminative representations. Experimental results on four widely used benchmarks, namely NTU-RGB+D-60, PKU-MMD, NTU-RGB+D-120 and UAV-Human dataset, demonstrate that the proposed U-FEFP obtains the best result compared with the state-of-the-art unsupervised learning methods. © 1991-2012 IEEE.

关键词： Convolution

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Secure Computation Offloading via Cooperative Jamming in Marine IoT Networks

Secure Computation Offloading via Cooperative Jamming in Mar...

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GLOBECOM 2022 - 2022 IEEE Global communications Conference

作者： Li Ping Qian Mingqing Li Xinyu Dong Yuan Wu Xiaoniu Yang College of Information Engineering Zhejiang University of Technology Hangzhou Zhejiang China Department of Computer and Information Science University of Macau Macao SAR China State Key Laboratory of Internet of Things for Smart City University of Macau Macao SAR China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781665435413

Edge computing has been envisioned as a promising approach to enable the computation-intensive yet latencysensitive marine mobile services in the fifth generation and beyond wireless networks. In this paper, we investigate the edge computing in Marine Internet of Things (M-IoT) via the assistance of unmanned surface vehicles (USVs) subject to the eavesdropping attack. In particular, we consider a scenario in which USVs are exploited to provide cooperative jamming for the communication security at the physical layer when the high altitude platform (HAP) is performing task offloading transmission. We jointly optimize the workload offloaded by HAP, the HAP's transmission power as well as each USV's interfering signal power with the objective of minimizing the total energy consumption for completing the total workloads under the latency constraint. The bisection search method is first adopted to obtain the optimal solutions to the offloaded workload and each USV's interfering signal power. Further, by exploiting the monotonicity, the polyblock outer approximation based algorithm (POA-Algorithm) is designed to obtain the HAP's optimal transmission power. Finally, numerical results validate the optimality and effectiveness of our proposed algorithm by comparing it with the results of LINGO and different jamming schemes.

关键词： Energy consumption Wireless networks Search methods Physical layer Approximation algorithms security Jamming

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Design of A Chipless Sensor System for Continuous Intraocular Pressure Monitoring

Design of A Chipless Sensor System for Continuous Intraocula...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Qi Yang Lu-Yang Sun Jun-Lin Zhan Cong Ding Hao Chen Zhen-Guo Liu Wei-Bing Lu Center for Flexible RF Technology State Key Lab of Millimeter Waves School of Information Science and Engineering Southeast University Nanjing China MOE Frontiers Science for Mobile Information Communication and Security Purple Mountain Laboratories Nanjing China

In this paper, a chipless sensor system for continuous intraocular pressure monitoring is designed, which includes a near-field communication circuit for transmitter and receiver of wireless signals and a near-field electromagnetic coupling antenna. In this system, signal processing chip on lab.l is removed, making it possible for the intelligent contact lens system to be fully flexible and transparent.

关键词： Wireless communication Wireless sensor networks Transmitting antennas Receiving antennas Transforms Signal processing Sensor systems

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Dual-band cooperative backscatter communication system

Dual-band cooperative backscatter communication system

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Cong Ding Jun-Lin Zhan Hao Chen Zhen-Guo Liu Wei-Bing Lu Center for Flexible RF Technology State Key Lab of Millimeter Waves School of Information Science and Engineering Southeast University Nanjing China MOE Frontiers Science for Mobile Information Communication and Security Purple Mountain Laboratories Nanjing China

ISBN: (纸本)9781665482271

In this paper, we build a cooperative backscatter communication system in 2.4GHz and 3.5 GHz. A test platform including backscattering modulator, Microcontroller Unit (MCU) and receiver system based on Software Defined Radio (SDR) technology is described. In order to realize the communication in the above bands, an omnidirectional dual-band antenna is designed first. Then a backscattering modulation circuit is designed, and a diplexer with two PIN diodes are used to control the two frequency bands. The carrier transmitting and receiving demodulation system is designed at the receiving end. This paper explains the design strategy of realizing frequency- shift keying (FSK) and phase-shift keying (PSK) in the bands simultaneously, and receiving the two signals separately. It can not only meet the communication requirements for different nodes, but also realize rate superposition to improve transmission efficiency.

关键词： Microwave antennas Time-frequency analysis Protocols Modulation Dual band Frequency shift keying Binary phase shift keying

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Yihan Zhao Xuting Duan Jianshan Zhou Long Zhang State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory School of Transportation Science and Engineering Beihang University Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time.

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Mixed Attention Densely Residual Network for Single Image Super-Resolution

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Computer Systems Science & Engineering 2021年第10期39卷 133-146页

作者： Jingjun Zhou Jing Liu Jingbing Li Mengxing Huang Jieren Cheng Yen-Wei Chen Yingying Xu Saqib Ali Nawaz School of Information and Communication Engineering Hainan UniversityHaikou570228China State Key Laboratory of Marine Resource Utilization in the South China Sea Hainan UniversityHaikou570228China Research Center for Healthcare Data Science Zhejiang LabHangzhou311121China School of Computer Science and Cyberspace Security Hainan UniversityHaikou570228China Graduate School of Information Science and Engineering Ritsumeikan University5258577Japan College of Computer Science and Technology Zhejiang UniversityHangzhou311100China

Recent applications of convolutional neural networks(CNNs)in single image super-resolution(SISR)have achieved unprecedented ***,existing CNN-based SISR network structure design consider mostly only channel or spatial information,and cannot make full use of both channel and spatial information to improve SISR performance *** present work addresses this problem by proposing a mixed attention densely residual network architecture that can make full and simultaneous use of both channel and spatial ***,we propose a residual in dense network structure composed of dense connections between multiple dense residual groups to form a very deep *** structure allows each dense residual group to apply a local residual skip connection and enables the cascading of multiple residual blocks to reuse previous features.A mixed attention module is inserted into each dense residual group,to enable the algorithm to fuse channel attention with laplacian spatial attention effectively,and thereby more adaptively focus on valuable feature *** qualitative and quantitative results of extensive experiments have demonstrate that the proposed method has a comparable performance with other stateof-the-art methods.

关键词： Channel attention Laplacian spatial attention residual in dense mixed attention

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Efficient Verification of Stabilizer Code Subspaces with Local Measurements

arXiv

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arXiv 2024年

作者： Zheng, Congcong Yu, Xutao Zhang, Zaichen Xu, Ping Wang, Kun State Key Lab of Millimeter Waves Southeast University Nanjing211189 China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Hefei National Laboratory Hefei230088 China

We address the task of verifying whether a quantum computer, designed to be protected by a specific stabilizer code, correctly encodes the corresponding logical qubits. To achieve this, we develop a general framework for subspace verification and explore several stabilizer code subspaces of practical significance. First, we present two efficient verification strategies for general stabilizer code subspaces, utilizing measurements of their stabilizer generators and stabilizer groups, respectively. Then, building on the observation that certain tests can be conducted in parallel when the subspace exhibits specific structural properties, we propose a coloring strategy tailored to graph code subspaces and an XZ strategy tailored to Calderbank-Shor-Steane (CSS) code subspaces. Compared to stabilizer-based strategies, these new strategies require significantly fewer measurement settings and consume fewer state copies, approaching near-global optimality. Notably, all the strategies employ a limited number of Pauli measurements, are non-adaptive, and work on mixed states, enabling efficient experimental certification of both logical qubits and logical operations in noisy quantum computers. This work contributes to the first systematic study of efficient verification of stabilizer code subspaces with local measurements. © 2024, CC BY.

关键词： Qubits

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