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2017 9th International Conference on Advanced Infocomm Technology (ICAIT)最新文献

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Simulations of novel radiometer systems using compressed sensing 基于压缩传感的新型辐射计系统仿真
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388817
Yu Tao, Y.-M. Niu, Yaoliang Song
In this paper, a novel radiometer system using compressed sensing technique is simulated. Millimeter-wave radiometer is a high-sensitivity noise power receiver that can detect the microwave radiation from objects. Millimeter wave radiometer is one of the key technologies in millimeter wave passive detection and imaging. The novel system this paper proposed using compressed sensing is a focal plane system, which simultaneously receives signals through multiple feeds. Each feed receives the corresponding pixel point of millimeter wave radiation energy. The system achieves the similar function of the dam-board by on-off the switch. The system reduces the number of receiver channels via the use of compressed sensing. The proposed system not only overcomes the shortcomings of the traditional systems, but also recovers the image according to the theory of compressed sensing. The system performance is validated through simulations.
本文对一种采用压缩传感技术的新型辐射计系统进行了仿真。毫米波辐射计是一种高灵敏度噪声功率接收机,可以探测到来自物体的微波辐射。毫米波辐射计是毫米波被动探测与成像的关键技术之一。本文提出的压缩感知系统是一个焦平面系统,通过多个馈源同时接收信号。每个馈送接收相应像素点的毫米波辐射能量。该系统通过开关的通断来实现与坝板类似的功能。该系统通过使用压缩感知减少了接收信道的数量。该系统不仅克服了传统系统的不足,而且根据压缩感知理论对图像进行了恢复。通过仿真验证了系统的性能。
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引用次数: 0
Uncertainty cost analysis of heterogeneous wireless network based on loan repayment approach 基于贷款偿还方法的异构无线网络不确定性成本分析
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388909
Usman Rauf Kamboh, Qinghai Yang, Meng Qin, Sundas Rauf
Mobile Network Operators (MNO) are recently fronting the extreme penetration of high data rate demands, rapidly expansion in smart mobile devices and round-delay trip time, which decoupling the service provider investments with mobile traffic flow. Therefore, an urgent need to deployment of such capable business approaches who provide the ultimate solution in sense to reduce the entire wireless network cost and to split the uncertain expenditures with well-organized manners. In this case, we consider the foremost issues of the wireless network for uncertainty cost analysis that comprising on different types of parameters such as site leasing, radio network controller, backhauling, integrating, electricity bills, interest rate, operation & maintenance, base station equipment's and implementation charges. We calculate the total cost of ownership (TCO), operator investments and recurring expenses using the well-known loan repayment method. Finally, comparing the indoor coverage-capacity experimental results among each site structure, we are able to conclude that femto base station and distributed antenna system (DAS) using as the alternate have significant impact on operator margins regarding their low cost in our proposed scenario.
移动网络运营商(MNO)最近面临着高数据速率需求的极端渗透,智能移动设备的快速扩张和往返延迟时间,这使得服务提供商的投资与移动流量脱钩。因此,迫切需要部署这种有能力的业务方法,在意义上提供最终的解决方案,以降低整个无线网络的成本,并以良好的方式分配不确定的支出。在这种情况下,我们考虑无线网络的首要问题进行不确定性成本分析,包括不同类型的参数,如站点租赁,无线网络控制器,回运,集成,电费,利率,运营和维护,基站设备和实施费用。我们使用众所周知的贷款偿还方法计算总拥有成本(TCO),运营商投资和经常性费用。最后,通过比较不同站点结构的室内覆盖容量实验结果,我们可以得出这样的结论:在我们提出的方案中,femto基站和分布式天线系统(DAS)作为备选方案对运营商边际利润有显著影响,因为它们的成本较低。
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引用次数: 2
A modified DV-hop localization algorithm based on communication radius dynamic adjustment 一种改进的基于通信半径动态调整的dv跳定位算法
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388926
Jing Zhang, Linghua Zhang
DV-Hop node localization algorithm is one of representative node positioning algorithms that are ranged-free in wireless sensor network. in actual measurement, we discover that if we define the hop number as one hop in the case of the distance that is less than or equal to communication radius, it will cause great positioning error. So, the improved algorithm introduces multiple communication radius in order to subdivide hop numbers and deduces a formula of hop numbers with the numbers of radius changing, amends average hop distance by correcting the weighted value. Simulation results proof that the algorithm availably cuts down the positioning error under the same network topology, comparing to traditional algorithm and the common weighted algorithm.
DV-Hop节点定位算法是无线传感器网络中具有代表性的无距离节点定位算法之一。在实际测量中,我们发现如果在距离小于等于通信半径的情况下,将跳数定义为一跳,将会产生很大的定位误差。为此,改进算法引入多个通信半径对跳数进行细分,推导出随半径数变化的跳数公式,通过修正加权值修正平均跳距离。仿真结果表明,与传统算法和常用加权算法相比,该算法有效地降低了相同网络拓扑下的定位误差。
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引用次数: 2
Minimum end-to-end transmission delay based routing algorithm for VANETs 基于最小端到端传输延迟的VANETs路由算法
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388910
Shangxin Peng, Rong Chai, Qianbin Chen, Yuanzheng Qin
Vehicular ad hoc networks (VANETs) are expected to offer both safety-related applications and user applications for vehicular users. In this paper, we consider a VANET scenario where one source vehicle (SV) tends to transmit real-time messages such as security related information to its destination vehicle (DV). We assume that the DV is out of the one hop range of the SV, and study the routing algorithm between the SV and DV. Stressing the importance of transmission delay, we formulate the end-to-end transmission delay between the SV and DV as the total transmission delay experienced at intermediate relay vehicles (RVs) along the transmission route, and design an optimization problem which minimizes the end-to-end transmission delay subject to routing selection constraints. To tackle the difficulties in evaluating the transmission performance of intermediate RVs, we apply stochastic network calculus theory. By modeling the stochastic arrival curve of the SV and the stochastic service curve of the RVs, the transmission delay at each intermediate RV can be examined. We then map the network scenario as a weighted graph and apply Dijkstra algorithm to obtain the optimal route between the SV and DV. Numerical results demonstrate the effectiveness of the proposed algorithm.
车辆自组织网络(vanet)有望为车辆用户提供安全相关应用和用户应用。在本文中,我们考虑了一个VANET场景,其中一个源车辆(SV)倾向于向其目的车辆(DV)传输实时消息,如安全相关信息。假设DV在SV的一跳范围之外,研究了SV和DV之间的路由算法。强调传输延迟的重要性,将SV和DV之间的端到端传输延迟表述为中间中继车(rv)沿传输路径经历的总传输延迟,并设计了在路由选择约束下端到端传输延迟最小化的优化问题。为了解决中间rv传输性能评估的困难,我们应用随机网络演算理论。通过对SV的随机到达曲线和RV的随机服务曲线进行建模,可以检验每个中间RV的传输延迟。然后,我们将网络场景映射为加权图,并应用Dijkstra算法获得SV和DV之间的最优路由。数值结果表明了该算法的有效性。
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引用次数: 3
Temperature-insensitive thinned double-cladding fiber with enhanced sensitivity for refractive index measurement 具有增强折射率测量灵敏度的温度不敏感薄双包层光纤
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388885
Jiajing Cheng, Huanhuan Liu, F. Pang, Tingyun Wang
We have proposed a temperature-insensitive sensor with enhanced sensitivity for refractive index (RI) measurement based on thinned double-cladding fiber. The RI sensitivity is increased by 6 times to 6000 nm/RIU compared with none-thinned double-cladding fiber.
我们提出了一种基于薄双包层光纤的温度不敏感传感器,该传感器具有增强的折射率测量灵敏度。与未增薄的双包层光纤相比,其RI灵敏度提高了6倍,达到6000nm /RIU。
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引用次数: 0
An efficient object recognition based on Gabor transform and LBP variance 基于Gabor变换和LBP方差的高效目标识别
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388952
Yongxin Chang, Shijie Feng, Jing Zhang
Recognizing objects from arbitrary aspects is always a highly challenging problem in applied engineering and computer vision fields. At present, most existing algorithms mainly focus on specific viewpoint detection. Hence, in this paper we propose a novel recognizing model, which combines Gabor transform with LBP variance to handle the problem of different viewpoints and pose changing. Then, the images of inaccurate recognizing are evaluated by learning and fed back the detector to avoid the same mistakes in the future. The principal idea is to extract intrinsic viewpoint invariant features from the unseen poses of object, and then to take advantage of these features to support recognition. Compared with other recognition models, the proposed approach can efficiently tackle the multi-view problem and promote the recognition performance. For a quantitative evaluation, this novel algorithm has been tested on two benchmark datasets such as Caltech 101 and PASCAL VOC 2011datasets. The experimental results validate that our approach can recognize objects more precisely and outperforms others single view recognition methods.
在应用工程和计算机视觉领域,从任意角度识别物体一直是一个极具挑战性的问题。目前,大多数现有算法主要集中在特定视点检测上。因此,本文提出了一种新的识别模型,将Gabor变换与LBP方差相结合来处理不同视点和姿态变化问题。然后,通过学习对识别不准确的图像进行评估,并反馈给检测器,以避免以后出现同样的错误。其主要思想是从物体不可见的姿态中提取固有的视点不变特征,然后利用这些特征来支持识别。与其他识别模型相比,该方法能有效地解决多视图问题,提高识别性能。为了进行定量评估,该算法已经在两个基准数据集(如Caltech 101和PASCAL VOC 2011数据集)上进行了测试。实验结果表明,该方法可以更精确地识别物体,并且优于其他单视图识别方法。
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引用次数: 0
Research on model mapping and analysis method of space-based early warning system based on complex network 基于复杂网络的天基预警系统模型映射与分析方法研究
Pub Date : 2017-11-01 DOI: 10.1109/icait.2017.8388956
Yang Miaoben, Xiong Wei
As an important component of the national military defense system, the space-based early warning system can play an important role in safeguarding national security and acquiring potential threat of targets. Therefore, the modeling and analysis of the system network of the space-based early warning system becomes an important method to understand the system network and measure the performance of the system. Based on this background, this paper puts forward the abstract mapping and feature information extraction of the space-based early warning system based on the complex network theory to complete the construction and rendering of the system network topology model, the discovery and extraction of the important nodes and the acquisition of the basic attributes of the system network model and so on.
天基预警系统作为国家军事防御体系的重要组成部分,在维护国家安全和获取潜在威胁目标方面发挥着重要作用。因此,对天基预警系统的系统网络进行建模和分析成为了解系统网络和衡量系统性能的重要方法。基于此背景,本文提出了基于复杂网络理论的天基预警系统抽象映射与特征信息提取,完成系统网络拓扑模型的构建与绘制、重要节点的发现与提取、系统网络模型基本属性的获取等工作。
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引用次数: 0
An ORB based visual SLAM system by RGB-D camera of LeTV 基于ORB的乐视RGB-D摄像机视觉SLAM系统
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388954
Yang Fan, Li Ming
This paper presents a visual simultaneously localization and mapping (SLAM) system based on Oriented FAST and Rotated BRIEF (ORB) and the RGB-D camera accessory of LeTV. Frame matching is performed through ORB feature and random sample and consensus (RANSAC) algorithm. G2o library is used as graph based pose optimization framework. Alternative key frame generation method is proposed to get increased processing capacity. Dense point cloud map which can be used for following intelligent robot related applications is generated from the depth information captured with color image simultaneously by the calibrated RGB-D camera.
提出了一种基于定向FAST和旋转BRIEF (ORB)和乐视RGB-D相机配件的视觉同步定位与制图系统(SLAM)。通过ORB特征和RANSAC (random sample and consensus)算法进行帧匹配。采用g20库作为基于图的姿态优化框架。提出了替代关键帧生成方法以提高处理能力。通过标定后的RGB-D相机同时采集彩色图像的深度信息,生成可用于后续智能机器人相关应用的密集点云图。
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引用次数: 1
Resources allocation in SWIPT aided fog computing networks SWIPT辅助雾计算网络中的资源分配
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388922
Haoye Chai, S. Leng, Jie Hu, Kun Yang
Fog computing has emerging as a promising technique to meet the ultra-low latency services in wireless network such as Augmented Reality (AR). The fog paradigm tends to distribute computing, storage, control, network resources and services closer to terminal devices as much as possible while most of User Equipments (UEs) do not have constant power supply thus the power supplement has developed as a nontrivial challenge to realize the paradigm. In this paper, simultaneous wireless information and power transfer (SWIPT) is introduced as a power resource to guarantee the UEs complete their computing tasks. We proposed a power, time and data allocation scheme to minimize the total consumption of energy at source node while maintaining the latency requirement. A Quantum particle swarm optimization (QPSO) algorithm in introduced to solve the non-convex problem, numerical results reveal that our proposed allocation scheme consumes less energy than the conventional particle swarm optimization approach.
雾计算作为一种很有前途的技术,在满足无线网络中的超低延迟服务,如增强现实(AR)。雾范式倾向于将计算、存储、控制、网络资源和服务尽可能地分布到终端设备上,而大多数用户设备(ue)没有恒定的电源供应,因此电源补充成为实现该范式的一个重要挑战。本文引入同步无线信息与功率传输(SWIPT)作为电力资源,保证终端完成其计算任务。我们提出了一种功率、时间和数据的分配方案,以最小化源节点的总能量消耗,同时保持延迟要求。引入量子粒子群优化算法求解非凸问题,数值结果表明,本文提出的分配方案比传统的粒子群优化方法能耗更低。
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引用次数: 5
Massive MIMO downlink channel estimation based on improved CAMP-MMV algorithm 基于改进CAMP-MMV算法的大规模MIMO下行信道估计
Pub Date : 2017-11-01 DOI: 10.1109/ICAIT.2017.8388899
Yue Xiu, Wenyuan Wang, Jiao Wu, Yongliang Shen
Downlink channel estimation in massive multiple-input multiple-output (MIMO) systems is challenging due to the large training and feedback overhead. So, it is necessary to reduce the pilot overhead. we propose a new compressive sensing (CS)CSI estimation scheme for frequency division duplexing (FDD)massive MIMO systems, which combines the algorithm of supports identify and the complex approximate message passing-multiple measurement vector (CAMP-MMV) algorithm. The approach by using information of supports position to improve the performance of CAMP-MMV. The analytic performance guarantees of the proposed scheme are the length of non orthogonal pilot and signal noise ratio (SNR). The numerical results show that performance of CSI estimation and achieve higher estimation accuracy as compared to an existing sparse Bayesian algorithm.
在大规模多输入多输出(MIMO)系统中,由于训练和反馈开销较大,下行信道估计具有挑战性。因此,有必要减少飞行员的开销。针对频分双工(FDD)大规模MIMO系统,提出了一种新的压缩感知(CS)CSI估计方案,该方案将支持度识别算法与复杂近似消息传递-多重测量向量(CAMP-MMV)算法相结合。利用支架位置信息提高CAMP-MMV性能的方法。非正交导频长度和信噪比是该方案分析性能的保证。数值结果表明,与现有的稀疏贝叶斯算法相比,CSI估计的性能和估计精度更高。
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引用次数: 0
期刊
2017 9th International Conference on Advanced Infocomm Technology (ICAIT)
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