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Blind quantum computation with a noise channel

Physical Review A 2018年第5期98卷 052343-052343页

作者： Yu-Bo Sheng Lan Zhou Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing 210003 China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing 210003 China School of Science Nanjing University of Posts and Telecommunications Nanjing 210003 China

Blind quantum computation (BQC) is a type of quantum computation model. For a client (Alice) who does not have enough sophisticated technology and knowledge to perform universal quantum computation, BQC allows her to resort to a remote quantum computation server (Bob) to delegate universal quantum computation. During the computation, Bob cannot know Alice's inputs, algorithm, and outputs. A single-server BQC protocol requires Alice to prepare and distribute single-photon states to Bob. Unfortunately, the distributed single photons will suffer from noise. The noise not only leads to the decoherence of the single-photon state, but also leads to photon loss. In this protocol, we describe an antinoise single-server BQC protocol. This protocol has three advantages. First, Alice does not require any auxiliary resources, which reduces the client's economic cost. Second, this protocol not only can protect the state from the collective noise, but also can distill the single photon from photon loss. Third, the noise processer in Bob is based on the linear optics so that it is feasible in experiment. This protocol may show that it is possible to perform a single-server BQC protocol in a noise channel.

关键词： Quantum computation

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An -norm Based Method for Off-grid DOA Estimation

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Circuits, Systems, and Signal Processing 2018年第2期38卷 904-917页

作者： Zhang, Zeyun Wu, Xiaohuan Li, Chunguo Zhu, Wei-Ping The Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing People’s Republic of China School of Information Science and Engineering Southeast University Nanjing People’s Republic of China Department of Electrical and Computer Engineering Concordia University Montreal Canada

The sparse signal recovery-based direction of arrival (DOA) estimation has received a great deal of attention over the past decade. From the sparse representation point of view, $$\ell _0$$ -norm is the best choice to evaluate the sparsity of a vector. However, solving an $$\ell _0$$ -norm minimization problem is non-deterministic polynomial hard (NP-hard). Thus, The common idea for many sparse DOA estimation methods is to use the $$\ell _1$$ -norm as the sparsity metric. However, its sparse solution may not coincide with the solution resulting from the $$\ell _0$$ -norm thus deteriorating the DOA estimation performance. In this paper, we propose a new sparse method based on $$\ell _p$$ ( $$0<1$$ ) regularization for DOA estimation to achieve a sparser solution than $$\ell _1$$ regularization. In particular, we use the Taylor expansion to convert the $$\ell _p$$ -norm minimization problem to a weighted $$\ell _1$$ -norm problem. Then, a two-step iterative method is employed to achieve the DOA estimate. The $$\ell _p$$ ( $$0<1$$ ) regularization is able to improve the angle resolution, leading to an improved performance in low SNR and correlated signal scenarios. Numerical results show that our proposed method has better estimation performance than many other methods do.

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A noval data collection approach for Wirelsee sensor networks

A noval data collection approach for Wirelsee Sensor Network...

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International Conference on Electrical and Control Engineering (ICECE)

作者： Haiyong Wang Geng Yang Jian Xu Zhengyu Chen Lei Chen Zhen Yang College of Internet of Things Nanjing University of Posts and Telecommunications Nanjing Jiangsu China Key Laboratory of Broadband Wireless Communication & Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

The unmanned nature of wireless sensor networks make them very vulnerable to the malicious attacks. Therefore, how to complete secure data collection under different conditions is the crucial issue to wireless sensor networks. There have been a few on-going research efforts about multipath routing for secure data collection. In this paper, we make full use of the broadcast message when wireless sensor network initializes to construct secure multipath routing for secure data collection which will cause little overhead to the sensor nodes in the network. In accordance with the simulation results, the algorithm in this paper compares with other recent researches is better.

关键词： Routing wireless sensor networks Algorithm design and analysis Neodymium sensors Cryptography Reliability

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Study on Object Transaction Based on networked RFID Systems

Study on Object Transaction Based on Networked RFID Systems

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2014 IEEE 5th International Conference on Software Engineering and Service Science

作者： Xuan Shen Chenqi Bao Jianmin Bao Huan Wang Department of Computer and Software Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationCollege of IOT Nanjing University of Posts and Telecommunications Department of IOT Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781479932801

Radio Frequency IDentification(RFID) is a novel technology of automated *** use of RFID,however,raises great concerns due to the serious security *** this paper,we at first propose a Secure Transaction Frame(STF) and a flow of object transaction based on networked RFID ***,it is worth mentioning that the authentication technology in Secure Transaction Frame(STF) is able to verify the ownership of electric tags in order to deal with common attacks in the networked RFID ***,this paper presents an encryption scheme to protect the information stored in electric tags from being illegally *** collecting relevant statistics and analyzing cases based on networked RFID systems,this paper also researches the mass requests for the information stored in the electric tags by the reader and eventually,gives a cache mechanism to solve that problem.

关键词： RFID object transaction secure transaction flow(STF) mass requests cache technology

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Normal Inverse Gaussian Approximation to Downlink Inter-cell Interference

Normal Inverse Gaussian Approximation to Downlink Inter-cell...

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IEEE International Conference on communications

作者： Xiaojun Yan Jing Xu Yuanping Zhu Yang Yang Guoping Tan Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology (SIMIT) Chinese Academy of Sciences (CAS) Telecommunications Lab Saarland University

ISBN: (纸本)9781467364300

In orthogonal frequency division multiple access (OFDMA)-based cellular networks subject to the distance-dependent path loss and shadow fading (SF), the downlink inter-cell interference (ICI) for a given user equipment (UE) is essentially a sum of several lognormal random variables (RVs). So far, no method of approximating the lognormal sum distribution is explicitly accurate when the component lognormal RVs with different logarithmic means and logarithmic variances are correlated. In this paper, the Normal Inverse Gaussian (NIG) distribution is proposed to approximate the downlink ICI for a given UE with the correlated SF. First, the downlink ICI is modelled as a sum of several correlated lognormal RVs. Then original moments of the lognormal sum in the logarithmic domain are obtained analytically. Finally the estimated parameters of the NIG distribution are computed explicitly by the mean, variance, skewness and kurtosis of the lognormal sum in the logarithmic domain through moment matching. Numerical results verify the accuracy of the NIG approximation when the correlated component lognormal RVs have different logarithmic means and logarithmic variances, and show that the NIG approximation outperforms the MGF-based lognormal approximation in various scenarios.

关键词： Approximation methods Downlink Interference wireless communication Correlation Monte Carlo methods Fading

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Channel measurement and modeling for the 15-GHz radio band in an indoor corridor environment

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Journal of communications and Information networks 2016年第2期1卷 102-108页

作者： XU Hui ZHANG Wuxiong YANG Yang Key Lab of Wireless Sensor Network and Communication Chinese Academy of SciencesShanghai 200050China Shanghai Institute of Microsystem and Information Technology Chinese Academy of SciencesShanghai 200050China Shanghai Research Center for Wireless Communications Shanghai 201210China

Traditional mobile communication systems mainly work on the licensed frequency band near or below 3 GHz;however,this band is becoming increasingly *** the other hand,there are abundant unlicensed spectrum resources in higher frequency bands,e.g.,6 GHz,15 GHz,and 28 GHz,and if those bands are applied,the current spectrum shortage problem could be effectively ***,the wireless channel characteristics and models are important but still unknown,and thus in this study,extensive measurements and modeling have been conducted to study the characteristics of the high-frequency 15-GHz ***,a PN(Pseudo Noise)sequence based time-domain measurement system was built and applied to measure the propagation characteristics of the LOS(Line-of-Sight)and NLOS(Non-Line-of-Sight)scenarios in an indoor corridor at 15 ***,in-depth analysis and modeling on the large-scale characteristics of wireless channels,the relationship between distance and path loss,the path loss exponent,and the shadow fading standard variance are ***,the relationship between received power and different elevation angles was *** the measurement,two 25-dBi horn antennas with a 10 half-power beam width are used to change elevation angles in the transmitting terminal and azimuth angles in the receiving terminal for all measurement *** findings and results in this work will serve as a reference and basis for future theoretical studies of the 15-GHz band.

关键词： 5G mobile network 15 GHz high frequency channel measurement channel modeling

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Deep reinforcement learning for smart home energy management

arXiv

引用

arXiv 2019年

作者： Yu, Liang Xie, Weiwei Xie, Di Zou, Yulong Zhang, Dengying Sun, Zhixin Zhang, Linghua Jiang, Tao Key Laboratory of Broadband Wireless Communication Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing210003 Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210003 Wuhan National Laboratory for Optoelectronics School of Electronics Information and Communications Huazhong University of Science and Technology Wuhan430074

In this paper, we investigate an energy cost minimization problem for a smart home in the absence of a building thermal dynamics model with the consideration of a comfortable temperature range. Due to the existence of model uncertainty, parameter uncertainty (e.g., renewable generation output, non-shiftable power demand, outdoor temperature, and electricity price) and temporally-coupled operational constraints, it is very challenging to determine the optimal energy management strategy for scheduling Heating, Ventilation, and Air Conditioning (HVAC) systems and energy storage systems in the smart home. To address the challenge, we first formulate the above problem as a Markov decision process, and then propose an energy management strategy based on Deep Deterministic Policy Gradients (DDPG). It is worth mentioning that the proposed strategy does not require the prior knowledge of uncertain parameters and building thermal dynamics model. Simulation results based on real-world traces demonstrate the effectiveness and robustness of the proposed strategy. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy management

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A high-resolution DOA estimation method with a family of nonconvex penalties

arXiv

引用

arXiv 2017年

作者： Wu, Xiaohuan Zhu, Wei-Ping Yan, Jun Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Department of Electrical and Computer Engineering Concordia University Montreal Canada School of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

The low-rank matrix reconstruction (LRMR) approach is widely used in direction-of-arrival (DOA) estimation. As the rank norm penalty in an LRMR is NP-hard to compute, the nuclear norm (or the trace norm for a positive semidefinite (PSD) matrix) has been often employed as a convex relaxation of the rank norm. However, solving a nuclear norm convex problem may lead to a suboptimal solution of the original rank norm problem. In this paper, we propose to apply a family of nonconvex penalties on the singular values of the covariance matrix as the sparsity metrics to approximate the rank norm. In particular, we formulate a nonconvex minimization problem and solve it by using a locally convergent iterative reweighted strategy in order to enhance the sparsity and resolution. The problem in each iteration is convex and hence can be solved by using the optimization toolbox. Convergence analysis shows that the new method is able to obtain a suboptimal solution. The connection between the proposed method and the sparse signal reconstruction (SSR) is explored showing that our method can be regarded as a sparsity-based method with the number of sampling grids approaching infinity. Two feasible implementation algorithms that are based on solving a duality problem and deducing a closed-form solution of the simplified problem are also provided for the convex problem at each iteration to expedite the convergence. Extensive simulation studies are conducted to show the superiority of the proposed methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Covariance matrix

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A real-time video watermarking algorithm for streaming media

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第14期6卷 504-511页

作者： Cheng, Chunling Wan, Teng Wei, Lei Zhu, Hong Zhang, Dengyin College of Computer Nanjing University of Posts and Telecommunications Nanjing Jiangsu 210003 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing Jiangsu 210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Jiangsu Province Nanjing Jiangsu 210003 China Power Dispatching Centre Nanjing Power Supply Company Nanjing 210008 China

Video watermarking technology is a useful method to track piracy for digital videos. However, most watermarking algorithms cannot be directly applied to H.264 streaming media because of their poor real-time performance, which may cause users to watch the video unsmoothly. In order to solve this problem, a real-time H.264 video watermarking algorithm (RVWA) is proposed. First, the video is segmented before embedding watermark, which makes watermark embedding and video transmission be carried on at the same time. Then, the concept of watermark embedding margin of frame (WEMF) is proposed to shorten the watermark embedding time. By calculating the value of WEMF for each B frame, which is related to its frame bits, suitable B-frames can be selected to embed watermark without decoding it completely. Finally, with the characteristic of variable macro block size in H.264 coding standard, a simplified formula is presented to quickly calculate the just noticeable difference (JND) value of the macro block, and then the macro blocks with larger JND value are selected to embed watermark into their motion vectors, which also provides good invisibility. Experimental results show that the proposed algorithm can find suitable embedding positions and embed watermark quickly with good invisibility and less increase of the bit-rate of video. RVWA algorithm can be used in stream media environment in real time.

关键词： Multimedia systems

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The hybrid encryption algorithm of lightweight data in cloud storage

The hybrid encryption algorithm of lightweight data in cloud...

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International Symposium on Agents, Multi-Agent Systems and Robotics (ISAMSR)

作者： Chengliang Liang Ning Ye Reza Malekian Ruchuan Wang College of Computer Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa Key Lab of Broadband Wireless Communication and Sensor Network Nanjing University of Post and Telecommunications Nanjing China

In this paper, we proposed a hybrid encryption algorithm in order to solve the security problems on lightweight data on the cloud storage service. This paper first improves the RSA algorithm in the cloud environment by increasing the length of the RSA key to an extent that it can quickly generate big primes. Then, we merge AES and RSA algorithms on the basis of the improved RSA algorithm. This is called a hybrid encryption algorithm which is suitable for security of the lightweight data in cloud storage environment in order to further enhance the confidentiality of data in the cloud. The experimental result shows that the hybrid encryption algorithm has advantages of fast encryption and decryption, more secure, and it is also able to settle the security problems of users' lightweight data in a certain extent.

关键词： Encryption Cloud computing Algorithm design and analysis Public key Access control

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