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Chinese Control Conference (CCC)

作者： Zewei Zhao Huqing Wang Zhe Sun Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P.R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P. R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P.R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P.R. China

Logistics vehicle and cargo matching problem is a typical combination optimization problem, which has important theoretical and application value in the field of logistics distribution. The proved particle swarm optimization (PSO) algorithm is one of the most extensive optimization methods studied in recent years, with excellent global search ability and convergence speed. Based on the IPSO algorithm, this paper proposes an effective IPSO algorithm model for the matching problem of logistics vehicles and goods, and conducts the corresponding comparative experiment. The final experimental results show that the algorithm has good results in practical application and can provide a feasible optimization method for solving the problem of logistics vehicles and goods.

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Author Correction: An Effective Way for Simulating Oceanic Turbulence Channel on the Beam Carrying Orbital Angular Momentum

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Scientific reports 2020年第1期10卷 1268页

作者： Sunxiang Pan Le Wang Wennai Wang Shengmei Zhao Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications(NUPT) Nanjing 210003 China. Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China. wangwn@***. Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications(NUPT) Nanjing 210003 China. zhaosm@***. Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China. zhaosm@***.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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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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Erratum to: Distributed beamforming designs to improve physical layer security in wireless relay networks

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EURASIP Journal on Advances in Signal Processing 2014年第1期2014卷 1-1页

作者： Mujun Qian Chen Liu Youhua Fu The Key Lab of Broadband Wireless Communication and Sensor Network Technology (Ministry of Education) Nanjing University of Posts and Telecommunications Nanjing Jiangsu China National Mobile Communications Research Laboratory Southeast University Nanjing Jiangsu China

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A Review of the Evolutionary Algorithm Based VRP Problem

A Review of the Evolutionary Algorithm Based VRP Problem

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Chinese Control Conference (CCC)

作者： Lili Pan Bing Hu Zhe Sun Lei Xu Guangfu Gong Xiangpeng Xie Zhixin Sun Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology) Nanjing University of Posts and Telecommunications Nanjing P. R. China Post Big Data Technology and Application Engineering Research Center of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing P. R. China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing P. R. China Anhui Yougu Express Intelligent Technology Co. LTD Nanling Anhui P. R. China

The problem of vehicle routing planning (VRP) has far-reaching influence, and is widely used in vehicle scheduling, industrial production, transportation, logistics and distribution. The study of VRP and its associated derivations has grown significantly in recent years. So, starting with the fundamental VRP, this paper categorizes the VRP based on its traits and real-world applications. It then in-depth analyses the capacity constrained VRP, time window VRP, batched delivery VRP, dynamic VRP, and stochastic demand VRP, and provides an update on each type of VRP's research. Additionally, a summary of the VRP problem-solving methods is provided. The study of evolutionary algorithms is the main topic of this paper, and the fundamental solution method is provided in accordance with the development of the algorithms.

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Deterministic realization of collective measurements via photonic quantum walks

Deterministic realization of collective measurements via pho...

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第十八届全国量子光学学术会议

作者：侯志博 Jun-Feng Tang Yuan Yuan Kang-Da Wu Guo-Yong Xiang Chuan-Feng Li Guang-Can Guo Jiangwei Shang Huangjun Zhu Jian Li 中科大 Key Laboratory of Quantum Information University of Science and Technology of ChinaCAS Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Naturwissenschaftlich-Technische Fakult?t Universit?t Siegen Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems School of PhysicsBeijing Institute of Technology Institute for Theoretical Physics University of Cologne Department of Physics and Center for Field Theory and Particle Physics Fudan University State Key Laboratory of Surface Physics Fudan University Collaborative Innovation Center of Advanced Microstructures Institute of Signal Processing Transmission Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and TelecommunicationsMinistry of Education

Collective measurements on identically prepared quantum systems can extract more information than local measurements, thereby enhancing information-processing efficiency. Although this nonclassical phenomenon has been known for two decades, it has remained a challenging task to demonstrate the advantage of collective measurements in experiments. Here, we introduce a general recipe for performing deterministic collective measurements on two identically prepared qubits based on quantum walks. Using photonic quantum walks, we realize experimentally an optimized collective measurement with fidelity 0.9946 without post selection. As an application, we achieve the highest tomographic efficiency in qubit state tomography to date. Our work offers an effective recipe for beating the precision limit of local measurements in quantum state tomography and metrology. In addition, our study opens an avenue for harvesting the power of collective measurements in quantum information processing and for exploring the intriguing physics behind this power.

关键词： Deterministic realization of collective measurements via photonic quantum walks

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Beamforming Design and Power Allocation for secure transmission with NOMA

arXiv

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arXiv 2018年

作者： Feng, Youhong Yan, Shihao Yang, Zhen Yang, Nan Yuan, Jinhong Key Lab. of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 College of Physics and Electronic Information Engineering Anhui Normal University Wuhu241000 China Research School of Engineering Australian National University CanberraACT Australia School of Engineering Macquarie University NSW2109 Australia Research School of Engineering Australian National University CanberraACT2600 Australia School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia

In this work, we propose a novel beamforming design to enhance physical layer security of a non-orthogonal multiple access (NOMA) system with the aid of artificial noise (AN). The proposed design uses two scalars to balance the useful signal strength and interference at the strong and weak users, which is a generalized version of the existing beamforming designs in the context of physical layer security for NOMA. We determine the optimal power allocation among useful signals and AN together with the two optimal beamforming scalars in order to maximize the secrecy sum rate (SSR). Our asymptotic analysis in the high signal-to-noise ratio regime provides an efficient and near-optimal solution to optimizing the beamforming scalars and power allocation coefficients. Our analysis indicates that it is not optimal to form a beam towards either the strong user or the weak user in NOMA systems for security enhancement. In addition, the asymptotically optimal power allocation informs that, as the transmit power increases, more power should be allocated to the weak user or AN signals, while the power allocated to the strong user keeps constant. Our examination shows that the proposed novel beamforming design can significantly outperform two benchmark schemes. Copyright © 2018, The Authors. All rights reserved.

关键词： Beamforming

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Deep Reinforcement Learning for User Association in Heterogeneous networks with Dual Connectivity

Deep Reinforcement Learning for User Association in Heteroge...

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IEEE Conference on wireless communications and networking

作者： Mengjie Yi Yan Zhang Xijun Wang Chao Xu Xiao Ma State Key Lab of Integrated Service Networks Information Science Institue Xidian University Xi’an Shaanxi China School of Electronics and Information Technology Sun Yat-sen University Guangzhou China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai China School of Information Engineering Northwest A&F University Yangling Shaanxi China Shaanxi Normal University Xi’an P. R. China

The dual connectivity is emerging as a promising solution to boost capacity in heterogeneous networks. However, it is challenging to obtain an optimal user association in heterogeneous networks with dual connectivity, due to its non-convex and combinatorial nature. In this paper, we propose a user association scheme based on deep reinforcement learning to maximize the overall network utility, which takes both throughput and user fairness into account, in the downlink of a heterogeneous network. Particularly, each user associates with the macro base station (BS) and a micro BS. We apply a deep Q-network (DQN) to obtain the nearly optimal policy to associate the users and micro BSs. Simulation results demonstrate that DQN-based user association performs better compared to the conventional user association schemes in heterogeneous networks with dual connectivity, and it behaves good scalability when the environment changes.

关键词： Base stations Simulation Scalability Conferences Reinforcement learning Markov processes Throughput

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Voiceprint recognition based on BP Neural network and CNN

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Journal of Physics: Conference Series 2019年第3期1237卷

作者： Dong Zhipeng Wei Jingcheng Xu Yumin Meng Qingmin Wang Xiaoming Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications) Ministry of Education College of Telecommunications & Information Engineering Nanjing 210003 China National Mobile Communications Research Lab Southeast University Nanjing 210096 China

At present, speech recognition has become a key technology of human-computer interaction, which can be used in semantic recognition and speaker identification and other related applications. This paper focuses on a speaker identification scene and the technical design. Because artificial neural network has the ability to distinguish complex classification boundaries, plenty of work on speech recognition had studied multi-layer perceptual networks to improve the accuracy of classification where back propagation method (BP algorithm) has been used. In the studied scheme, when the test objects (speakers) speak the same isolated word, the identification system can judge who the speaker is by identifying the voice voiceprint of different people. Our design not only considers the recognition based on BP as well as its variant, but also explores the voiceprint recognition based on convolution neural network (CNN). Secondly, the network structure and performance are also compared in detail.

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Measurement-Device-Independent Quantum Secure Direct communication

arXiv

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arXiv 2018年

作者： Zhou, Zeng-Rong Sheng, Yu-Bo Niu, Peng-Hao Yin, Liu-Guo Long, Gui-Lu State Key Laboratory of Low-dimensional Quantum Physics Beijing100084 China Department of Physics Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China School of Information and Technology Tsinghua University Beijing100084 China Collaborative Innovation Center of Quantum Matter Beijing100084 China Beijing Academy of Quantum Information Beijing100084 China Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing210003 China College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing210003 China

Quantum secure direct communication (QSDC) is the technology to transmit secret information directly through a quantum channel without neither key nor ciphertext. It provides us with a secure communication structure that is fundamentally different from the one that we use today. In this Letter, we report the first measurement-device-independent(MDI) QSDC protocol with sequences of entangled photon pairs and single photons. It eliminates security loopholes associated with the measurement device. In addition, the MDI technique doubles the communication distance compared to those without using the technique. We also give a protocol with linear optical Bell-basis measurement, where only two of the four Bell-basis states could be measured. When the number of qubit in a sequence reduces to 1, the MDI-QSDC protocol reduces to a deterministic MDI quantum key distribution protocol, which is also presented in the Letter. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum communication

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