检索结果-内蒙古大学图书馆

2017 IEEE International Conference on Communications, ICC 2017

作者： Wang, Danyang Li, Zan Zhang, Ning Qi, Peihan Shen, Xuemin Sherman State Key Laboratory of Integrated Service Networks Xidian University Xi'an710071 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

ISBN: (纸本)9781467389990

In this paper, we propose a high order cumulants based spectrum sensing and power recognition (CSR) detector for hybrid interweave-underlay spectrum access, where the primary system is with multiple transmit power levels. Specifically, to detect the idle spectrum when primary user (PU) is absent, high order cumulants based spectrum sensing is performed in interweave model. When PU is detected, the working model is switched to underlay model, where detection of PU's transmit power level is performed to allow secondary user (SU) to adjust its power for fully exploring spectrum access opportunities without harmful interference to PU. Given a certain order and a certain lag, the test statistics of the proposed detector is derived by leveraging general likelihood ratio test. Since cumulants higher than second order are zero for Gaussian distributions, the proposed CSR detector can extract non-Gaussian signal from Gaussian noise even when the noise is colored. Additionally, the proposed detector does not require any prior knowledge about the noise variance, thus it is robust to noise uncertainty. Closedform results for threshold expression are derived, and numerical results are provided to evaluate the proposed detector. © 2017 IEEE.

关键词： Gaussian noise (electronic)

来源：评论

学校读者我要写书评

暂无评论

Frequency synchronization for uplink massive MIMO with adaptive MUI suppression in angle-domain

arXiv

引用

arXiv 2018年

作者： Ge, Yinghao Zhang, Weile Gao, Feifei Li, Geoffrey Ye MOE Key Lab for Intelligent Networks and Network Security School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an Shaanxi710049 China State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States

In this paper, we develop a novel angle-domain adaptive filtering (ADAF)-based frequency synchronization method for the uplink of a massive multiple-input multiple-output (MIMO) multiuser network, which is applicable for users with either separate or overlapped angle-of-arrival (AoA) regions. For each user, we first introduce the angle-constraining matrix (ACM), which consists of a set of selected match-filter (MF) beamformers pointing to the AoAs of the interested user. Then, the adaptive beamformer can be acquired by appropriately designing the ADAF vectors. Such beamformer can achieve two-stage adaptive multiuser interference (MUI) suppression, i.e., inherently suppressing the MUI from non-overlapping users by ACM in the first stage and substantially mitigating the MUI from adjacent overlapping users by ADAF vector in the second stage. For both separate and mutually overlapping users, the carrier frequency offset (CFO) estimation and subsequent data detection can be performed independently for each user, which significantly reduces computational complexity. Moreover, ADAF is rather robust to imperfect AoA knowledge and side cluster of scatterers, making itself promising for multiuser uplink transmission. We also analyze the performance of CFO estimation and obtain an approximated closed-form expression of mean-squared error (MSE). The effectiveness of the proposed method and its superiority over the existing methods are demonstrated by numerical results. Copyright © 2018, The Authors. All rights reserved.

关键词： Adaptive filters

来源：评论

学校读者我要写书评

暂无评论

Special issue on 2016 International Conference on Intelligence Science and Big Data engineering

Special issue on 2016 International Conference on Intelligen...

引用

作者： Zheng, Wei-Shi Gao, Xinbo Li, Yuanqing Lai, Jianhuang School of Data and Computer Science Sun Yat-sen University China State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an710071 China School of Automation Science and Engineering South China University of Technology China Guangzhou Key Laboratory of Brain Computer Interface and Applications Guangzhou 510640 China School of Data and Computer Science Sun Yat-sen University Guangzhou510275 China

来源：评论

学校读者我要写书评

暂无评论

Cooperative Secrecy to Resist Authentication Error in Two-Hop Wireless networks

引用

Chinese Journal of Electronics 2016年第4期25卷 746-752页

作者： SHEN Yulong PEI Qingqi MA Jianfeng School of Computer Science and Technology Xidian University The State Key Laboratory of Integrated Services Networks School of Telecommunications Engineering Xidian University

The authentication error in two-hop wireless networks is considered without knowledge of eavesdropper channels and *** wireless informationtheoretic security has attracted considerable attention recently.A prerequisite for available works is the precise distinction between legitimate nodes and *** it is unrealistic in the wireless *** is always existing in the node authentication *** of our knowledge,there are no works focus on solving this problem in the information-theoretic *** paper presents a eavesdropper model with authentication error and two eavesdropping ***,the number of eavesdroppers can be tolerated is analyzed while the desired secrecy is achieved with high probability in the limit of a large number of relay ***,we draw two conclusions for authentication error:1) The impersonate nodes are chosen as relay is the dominant factor of the transmitted message leakage,and the impersonation attack does seriously decrease the number of eavesdroppers can be tolerated.2) The error authentication to legitimate nodes is almost no effect on the number of eavesdroppers can be tolerated.

关键词： Wireless networks Information-theoretic security Cooperative secrecy Authentication error

来源：评论

学校读者我要写书评

暂无评论

Dual-Connectivity Enabled Traffic Offloading via Small Cells Powered by Energy-Harvesting

Dual-Connectivity Enabled Traffic Offloading via Small Cells...

引用

2017 IEEE Global Communications Conference, GLOBECOM 2017

作者： Wu, Yuan Qian, Li Ping Yang, Xiaowei Zheng, Jianchao Zhou, Haibo Shen, Xuemin Sherman College of Information Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China Institute of Communications Engineering PLA University of Science and Technology Nanjing China Department of Electrical and Computer Engineering University of Waterloo ON Canada

ISBN: (纸本)9781509050208;9781509050192

Dual-connectivity (DC), an emerging paradigm in the recent 3GPP specification, is envisioned as a promising solution to enhance mobile users' (MUs') traffic offloading by aggregating radio resources at both macro and small cells. In this paper, we investigate the energy-efficient DC-enabled traffic offloading through small cells which are powered by the on-grid power supply and harvesting renewable energy from nature. In spite of reducing the on-grid power consumption, powering traffic offloading by energy harvesting (EH) leads to the offloading outage due to the intermittency in EH power-supply, which degrades the offloading throughput. Therefore, to reap both the advantages of DC and the EH-supply, we propose a joint traffic scheduling and power allocation scheme that aims at minimizing the total on-grid power consumption, while accounting for the offloading outage and guaranteeing the MU's quality of service (QoS) requirement. In spite of the non-convexity nature of the joint optimization of traffic scheduling and power allocation, we propose an algorithm to efficiently compute the optimal offloading solution. Numerical results are provided to validate our proposed algorithm and the performance gain of the proposed DC-enabled traffic offloading scheme. © 2017 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

A FIWARE-Based Component for Data Analysis in Smart Mobility Context 1

A FIWARE-Based Component for Data Analysis in Smart Mobility...

引用

1st IEEE Summer School on Smart Cities, S3C 2017

作者： De Fatima Pereira Marquesone, Rosangela De Brito Carvalho, Tereza Cristina Melo Guimaraes, Lucas Batista Dias, Eduardo Mario Laboratory of Computer Networks and Architecture LARC Polytechnic School University of São Paulo São Paulo Brazil Department of Energy Engineering and Automation Polytechnic University of São Paulo São Paulo Brazil

ISBN: (纸本)9781538610633

Smart mobility is an emerging concept characterized by the use of disruptive technologies, such as cloud computing, Big Data and artificial intelligence. In this paper we propose a FIWARE-based component focus on improving the data analysis process, from data generated in services and applications existing in the smart mobility context. Our proposal aims to provide features that allows the development of solutions from the industry 4.0 concept and smart cities. Firstly, we briefly contextualize these terms, then we describe the characteristics and architectural design of our FIWARE component, highlighting how it can improve the support to smart services and applications. We also present real application scenarios where this component can be applied, specially considering the Brazilian cities. © 2017 IEEE.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

Artificial noise aided secure cognitive beamforming for cooperative MISO-NOMA using SWIPT

arXiv

引用

arXiv 2018年

作者： Zhou, Fuhui Chu, Zheng Sun, Haijian Hu, Rose Qingyang Hanzo, Lajos Department of Electrical and Computer Engineering Utah State University United States School of Information Engineering Nanchang University 330031 China State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China University of Surrey GuildfordGU2 7XH United Kingdom Electrical and Computer Engineering Department Utah State University USA United States University of Southampton SouthamptonSO17 1BJ United Kingdom

Cognitive radio (CR) and non-orthogonal multiple access (NOMA) have been deemed two promising technologies due to their potential to achieve high spectral efficiency and massive connectivity. This paper studies a multiple-input single-output NOMA CR network relying on simultaneous wireless information and power transfer (SWIPT) conceived for supporting a massive population of power limited battery-driven devices. In contrast to most of the existing works, which use an ideally linear energy harvesting model, this study applies a more practical non-linear energy harvesting model. In order to improve the security of the primary network, an artificial-noise-aided cooperative jamming scheme is proposed. The artificial-noise-aided beamforming design problems are investigated subject to the practical secrecy rate and energy harvesting constraints. Specifically, the transmission power minimization problems are formulated under both perfect channel state information (CSI) and the bounded CSI error model. The problems formulated are non-convex, hence they are challenging to solve. A pair of algorithms either using semidefinite relaxation (SDR) or a cost function are proposed for solving these problems. Our simulation results show that the proposed cooperative jamming scheme succeeds in establishing secure communications and NOMA is capable of outperforming the conventional orthogonal multiple access in terms of its power efficiency. Finally, we demonstrate that the cost function algorithm outperforms the SDR-based algorithm. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Coarse-to-Fine Learning for Single-Image Super-Resolution

引用

IEEE Transactions on Neural networks and Learning Systems 2017年第5期28卷 1109-1122页

作者： Zhang, Kaibing Tao, Dacheng Gao, Xinbo Li, Xuelong Li, Jie School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an Shaanxi710119 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China

This paper develops a coarse-to-fine framework for single-image super-resolution (SR) reconstruction. The coarse-to-fine approach achieves high-quality SR recovery based on the complementary properties of both example learning-and reconstruction-based algorithms: example learning-based SR approaches are useful for generating plausible details from external exemplars but poor at suppressing aliasing artifacts, while reconstruction-based SR methods are propitious for preserving sharp edges yet fail to generate fine details. In the coarse stage of the method, we use a set of simple yet effective mapping functions, learned via correlative neighbor regression of grouped low-resolution (LR) to high-resolution (HR) dictionary atoms, to synthesize an initial SR estimate with particularly low computational cost. In the fine stage, we devise an effective regularization term that seamlessly integrates the properties of local structural regularity, nonlocal self-similarity, and collaborative representation over relevant atoms in a learned HR dictionary, to further improve the visual quality of the initial SR estimation obtained in the coarse stage. The experimental results indicate that our method outperforms other state-of-the-art methods for producing high-quality images despite that both the initial SR estimation and the followed enhancement are cheap to implement. © 2012 IEEE.

关键词： Optical resolving power

来源：评论

学校读者我要写书评

暂无评论

A Subpixel Target Detection Approach to Hyperspectral Image Classification

引用

IEEE Transactions on Geoscience and Remote Sensing 2017年第9期55卷 5093-5114页

作者： Xue, Bai Yu, Chunyan Wang, Yulei Song, Meiping Li, Sen Wang, Lin Chen, Hsian-Min Chang, Chein-I Center for Hyperspectral Imaging in Remote Sensing Information and Technology College Dalian Maritime University Dalian China Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States Key Laboratory of Spectral Imaging Technology Chinese Academy of Sciences Xi'an China State Key Laboratory of Integrated Services Networks Xi'an China School of Physics and Optoelectronic Engineering Xidian University Xi'an China Department of Medical Research Taichung Veterans General Hospital Taichung Taiwan Department of Computer Science and Information Management Providence University Taichung02912 Taiwan

Hyperspectral image classification faces various levels of difficulty due to the use of different types of hyperspectral image data. Recently, spectral-spatial approaches have been developed by jointly taking care of spectral and spatial information. This paper presents a completely different approach from a subpixel target detection view point. It implements four stage processes, a preprocessing stage, which uses band selection (BS) and nonlinear band expansion, referred to as BS-then-nonlinear expansion (BSNE), a detection stage, which implements constrained energy minimization (CEM) to produce subpixel target maps, and an iterative stage, which develops an iterative CEM (ICEM) by applying Gaussian filters to capture spatial information, and then feeding the Gaussian-filtered CEM-detection maps back to BSNE band images to reprocess CEM in an iterative manner. Finally, in the last stage Otsu's method is applied to converting ICEM-detected real-valued maps to discrete values for classification. The entire process is called BSNE-ICEM. Experimental results demonstrate BSNE-ICEM, which has advantages over support vector machine-based approaches in many aspects, such as easy implementation, fewer parameters to be used, and better false classification and precision rates. © 1980-2012 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

High precision seeder control system based on fuzzy algorithm

High precision seeder control system based on fuzzy algorith...

引用

IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference

作者： Yan Jiang MaoLi Wang Jie Duan Jingbo Zhao College of Automation Engineering Qingdao University of Technology Qingdao China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center (National Super computer Center in Jinan) Jinan China

Seeder mechanical vibration control difficult. Aiming at the problem that the precision control of the seeder is not high, the position control system of the stepper motor with Fuzzy controller as the controller is designed. This system uses SCI serial port to communicate with the host computer, through the photoelectric encoder to measure the mechanical walking position and feedback to the Fuzzy controller, the controller according to the feedback results in real time to adjust the PWM signal frequency control motor speed.

关键词： Stepper Motor Fuzzy Algorithm Photoelectric Encoder Zero Crossing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：