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IEEE Globecom Workshops

作者： Ang Li Jianxin Chen Bin Kang Wenqin Zhuang Xuguang Zhang College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China National Engineering Research Center for Communication and Information Technology (NUPT) Nanjing China Key Laboratory of Broadband Wireless Communications and Sensor Network Technology Ministry of Education (NUPT) Nanjing China

ISBN: (数字)9781728109602

ISBN: (纸本)9781728109619

Fine-grained recognition is still a difficult task in pattern recognition applications due to the challenge of accurate localization of discriminative parts. Recent CNN-based methods generally utilize attention mechanism to produce attention masks without part labels/annotations and extract corresponding image parts from them. However, these methods extract the attention parts by using fixed-size rectangles to crop images regardless of the size of objects to be recognized, which will hinder the feature expression of the following Part-CNNs. In this paper, we propose an adaptive cropping module based on the information of attention masks to adjust size of cropping rectangles. The training process of adaptive cropping module and Part-CNNscan reinforce each other with the proposed rank loss and the classic softmax loss. To further balance and fuse all attention parts, we propose a part weighting module to evaluate part contributions. Under the optimization of sort loss, the part weighting module will produce part weights in the same order as prediction scores learned by attention parts. The backbone of our network is MA-CNN. Different from MA-CNN, the new proposed adaptive cropping module and part weighting module can jointly guide the framework to produce a more discriminative fine-grained feature. Experiments show that the AMA-CNN outperforms MA-CNN by 1.1% on CUB200-2011 bird dataset.

关键词： Feature extraction Agriculture Training Image recognition Shape Fuses Birds

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Deep reinforcement learning for fresh data collection in UAV-assisted IoT networks

arXiv

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arXiv 2020年

作者： Yi, Mengjie Wang, Xijun Liu, Juan Zhang, Yan Bai, Bo State Key Lab of Integrated Service Networks Information Science Institute Xidian University Xi’an Shaanxi710071 China Science and Technology on Communication Network Laboratory Shijiazhuang Hebei050081 China School of Electronics and Communication Engineering Sun Yat-sen University Guangzhou510006 China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai200050 China School of Electrical Engineering and Computer Science Ningbo University Zhejiang315211 China 2012 Labs Huawei Technologies Co. Ltd. Hong Kong Hong Kong

Due to the flexibility and low operational cost, dispatching unmanned aerial vehicles (UAVs) to collect information from distributed sensors is expected to be a promising solution in Internet of Things (IoT), especially for time-critical applications. How to maintain the information freshness is a challenging issue. In this paper, we investigate the fresh data collection problem in UAV-assisted IoT networks. Particularly, the UAV flies towards the sensors to collect status update packets within a given duration while maintaining a non-negative residual energy. We formulate a Markov Decision Process (MDP) to find the optimal flight trajectory of the UAV and transmission scheduling of the sensors that minimizes the weighted sum of the age of information (AoI). A UAV-assisted data collection algorithm based on deep reinforcement learning (DRL) is further proposed to overcome the curse of dimensionality. Extensive simulation results demonstrate that the proposed DRL-based algorithm can significantly reduce the weighted sum of the AoI compared to other baseline algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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GRIDLESS TWO-DIMENSIONAL DOA ESTIMATION WITH L-SHAPED ARRAY BASED ON THE CROSS-COVARIANCE MATRIX

GRIDLESS TWO-DIMENSIONAL DOA ESTIMATION WITH L-SHAPED ARRAY ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Xiaohuan Wu Wei-Ping Zhu Jun Yan Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781538646595

The atomic norm minimization (ANM) has been successfully incorporated into the two-dimensional (2-D) direction-of-arrival (DOA) estimation problem for super-resolution. However, its computational workload might be unaffordable when the number of snapshots is large. In this paper, we propose two gridless methods for 2-D DOA estimation with L-shaped array based on the atomic norm to improve the computational efficiency. Firstly, by exploiting the cross-covariance matrix an ANM-based model has been proposed. We then prove that this model can be efficiently solved as a semi-definite programming (SDP). Secondly, a modified model has been presented to improve the estimation accuracy. It is shown that our proposed methods can be applied to both uniform and sparse L-shaped arrays and do not require any knowledge of the number of sources. Furthermore, since our methods greatly reduce the model size as compared to the conventional ANM method, and thus are much more efficient. Simulations results are provided to demonstrate the advantage of our methods.

关键词： 2-D DOA estimation L-shaped array atomic norm cross-covariance matrix

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Real-time Hand Tracking Using Kinect

Real-time Hand Tracking Using Kinect

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作者： Chenxuan Xi Jianxin Chen Chenxue Zhao Qicheng Pei Lizheng Liu Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of Education

Real-time hand tracking is fundamental to human gesture recognition. However, due to the huge computation, previous studies are either off-line or limited to given poses. In order to satisfy the requirement of real-time hand tracking, in this paper we propose a real time hand tracking method using Kinect. Firstly we extract the hand region from the depth image output from Kinect. Then we achieve the hand parameters. During the procedure of hand region extraction, we propose a cascade structure with recursive connected component algorithm to improve the efficiency and reserve connection relationships in 3D space. To determine the fingertips, we use the former 3D connections and geodesic distance over hand skeleton pixels to guarantee the accuracy and robustness, with acceptable loss. Experimental results show that our proposed solution can significantly improve the quality of real-time hand tracking.

关键词： Hand tracking fingertip tracking Kinect connected component analysis geodesic distance

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Multidimensional reconciliation protocol for continuous-variable quantum key agreement with polar coding

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中国科学（物理学力学天文学） 2018年第9期61卷 99-102页

作者： ShengMei Zhao ZhiGang Shen Hong Xiao Le Wang Institute of Signal Processing Transmission Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China Institute of Signal Processing Transmission Nanjing University of Posts and Telecommunications Nanjing 210003 China

Continuous-variable quantum key distribution (CVQKD) [1-7] allows two remote parties (Alice and Bob) to share a secret key,even in the presence of an eavesdropper (Eve) with unlimited computational power [8-17].While,a highly efficient reconciliation protocol [18-21] is crucial in a CVQKD system,which can not only extract the errorless secret keys,but also provide a promising way to achieve a long distance CVQKD at a low signal-to-noise ratio (SNR).There are some practical reconciliation protocols [18-21] for CVQKD systems,such as,sliced reconciliation protocol (SEC) [18],sign reconciliation protocol [19],and multidimensional reconciliation protocol (MR) [21].Compared with the others,MR utilized the algebraic properties of a multidimensional method,which did not require quantization or any other post-selection technique.

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Certifying quantum teleportation experimentally

Quantum Engineering

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Quantum Engineering 2019年第3期1卷

作者： Sheng, Yu-Bo Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing China School of Science Nanjing University of Posts and Telecommunications Nanjing China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing China

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Channel Estimation and Throughput Evaluation for 5G wireless communication Systems in Various Scenarios on High Speed Railways

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China communications 2018年第4期15卷 86-97页

作者： yanrong zhao xiyu wang gongpu wang ruisi he yulong zou zhuyan zhao school of computer and information technology beijing jiaotong universityBeijing 100044China the state key laboratory of rail traffic control and safety beijing jiaotong universityBeijing 100044China the key laboratory of broadband wireless communication and sensor network technology of ministry of education nanjing university of posts and telecommunicationsNanjing 210003China nokia bell labs beijing Beijing 100044China

The fifth generation （5G） wireless communication is currently a hot research topic and wireless communication systems on high speed railways （HSR） are important applications of 5G technologies. Existing stud- ies about 5G wireless systems on high speed railways （HSR） often utilize ideal channel parameters and are usually based on simple scenarios. In this paper, we evaluate the down- link throughput of 5G HSR communication systems on three typical scenarios including urban, cutting and viaduct with three different channel estimators. The channel parameters of each scenario are generated with tapped delay line （TDL） models through ray-tracing sim- ulations, which can be considered as a good match to practical situations. The channel estimators including least square （LS）, linear minimum mean square error （LMMSE）, and our proposed historical information based ba- sis expansion model （HiBEM）. We analyze the performance of the HiBEM estimator in terms of mean square error （MSE） and evaluate the system throughputs with different channel estimates over each scenario. Simulation results are then provided to corroborate our proposed studies. It is shown that our HiBEM estimator outperforms other estimators and that the sys-tem throughput can reach the highest point in the viaduct scenario.

关键词： 5G channel estimation HSR tapped delay line throughput pertbrmanceanalysis wireless communication.

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Robust and Passive Motion Detection with COTS WiFi Devices

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Tsinghua Science and technology 2017年第4期22卷 345-359页

作者： Hai Zhu Fu Xiao Lijuan Sun Xiaohui Xie Panlong Yang Ruchuan Wang the College of Computer Nanjing University of Posts and Telecommunications the Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education and College of Computer Nanjing University of Posts and Telecommunications the College of Computer Science and Technology University of Science and Technology of China

Device-free Passive（DfP） detection has received increasing attention for its ability to support various pervasive applications. Instead of relying on variable Received Signal Strength（RSS）, most recent studies rely on finer-grained Channel State Information（CSI）. However, existing methods have some limitations, in that they are effective only in the Line-Of-Sight（LOS） or for more than one moving individual. In this paper, we analyze the human motion effect on CSI and propose a novel scheme for Robust Passive Motion Detection（R-PMD）. Since traditional low-pass filtering has a number of limitations with respect to data denoising, we adopt a novel Principal Component Analysis（PCA）-based filtering technique to capture the representative signals of human motion and extract the variance profile as the sensitive metric for human detection. In addition, existing schemes simply aggregate CSI values over all the antennas in MIMO systems. Instead, we investigate the sensing quality of each antenna and aggregate the best combination of antennas to achieve more accurate and robust detection. The R-PMD prototype uses off-the-shelf WiFi devices and the experimental results demonstrate that R-PMD achieves an average detection rate of 96.33% with a false alarm rate of 3.67%.

关键词： device-free passive detection Received Signal Strength（RSS） channel state information MIMO

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A Node Localization Algorithm in WSNs Based on Iterative Estimation

A Node Localization Algorithm in WSNs Based on Iterative Est...

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IEEE Information technology and Mechatronics Engineering Conference (ITOEC)

作者： Rui Jiang Qian Wu Youyun Xu Broadband Wireless Communication and Sensor Network Technology Key Lab of Ministry of Education Nanjing University of Posts and Telecommunications Jiangsu China

ISBN: (纸本)9781538653746

According to the application of range-free measurement for wireless sensor networks (WSNs), a novel localization algorithm of nodes in based on iterative centroid estimation is proposed in the paper. First, we derive the centroid of the plane enclosed by the current connected beacon nodes as well as the received signal strength (RSSI) between target and beacon nodes. Then, we replace the farthest beacon node from the target node with the centroid node we derive in order to narrow the area of the plane enclosed by the connected beacon nodes and improve the location accuracy through multiple iterations. Judging from the simulation results, the proposed algorithm presents decent results of all indications and is thus eligible for localization in WSNs.

关键词： wireless sensor networks Measurement errors Signal to noise ratio Mathematical model Classification algorithms Estimation Approximation algorithms

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On the secrecy performance of Random VLC networks with imperfect CSI and protected zone

arXiv

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arXiv 2019年

作者： Wang, Jin-Yuan Qiu, Yu Lin, Sheng-Hong Wang, Jun-Bo Lin, Min Liu, Cheng Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Vertical Industry Development Department Baidu China Co. Ltd. Shanghai201210 China

This paper investigates the physical-layer security for a random indoor visible light communication (VLC) network with imperfect channel state information (CSI) and a protected zone. The VLC network consists of three nodes, i.e., a transmitter (Alice), a legitimate receiver (Bob), and an eavesdropper (Eve). Alice is fixed in the center of the ceiling, and the emitted signal at Alice satisfies the non-negativity and the dimmable average optical intensity constraint. Bob and Eve are randomly deployed on the receiver plane. By employing the protected zone and considering the imperfect CSI, the stochastic characteristics of the channel gains for both the main and the eavesdropping channels is first analyzed. After that, the closed-form expressions of the average secrecy capacity and the lower bound of secrecy outage probability are derived, respectively. Finally, Monte-Carlo simulations are provided to verify the accuracy of the derived theoretical expressions. Moreover, the impacts of the nominal optical intensity, the dimming target, the protected zone and the imperfect CSI on secrecy performance are discussed, respectively. Copyright © 2019, The Authors. All rights reserved.

关键词： Visible light communication

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