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A NEW APPROACH FOR ERROR CORRECTION DECODING BASED ON THE BP ALGORITHM IN LTE AND WIMAX SYSTEMS lte和wimax系统中基于bp算法的纠错译码新方法
Pub Date : 2018-06-15 DOI: 10.30534/IJCCN/2018/25722018
Ewit
Abstract—Many wireless communication systems such as IS-54, enhanced data rates for the GSM evolution (EDGE), worldwide interoperability for microwave access (WiMAX) and long term evolution (LTE) have adopted low-density parity check (LDPC), tail-biting Convolutional, and turbo codes as the forward error correcting codes (FEC) scheme for data and overhead channels. Therefore, many efficient algorithms have been proposed for decoding these codes. However, the different decoding approaches for these two families of codes usually lead to different hardware architectures. Since these codes work side by side in these new wireless systems, it is a good idea to introduce a universal decoder to handle these two families of codes. The present work exploits the parity-check matrix (H) representation of tail biting Convolution and turbo codes, thus enabling decoding via a unified belief propagation (BP) algorithm. Indeed, the BP algorithm provides a highly effective general methodology for devising low-complexity iterative decoding algorithms for all Convolution code classes as well as turbo codes. While a small performance loss is observed when decoding turbo codes with BP instead of MAP, this is offset by the lower complexity of the BP algorithm and the inherent advantage of a unified decoding architecture.
许多无线通信系统,如IS-54、增强数据速率的GSM演进(EDGE)、微波接入的全球互操作性(WiMAX)和长期演进(LTE)等,都采用低密度奇偶校验(LDPC)、卷尾码和turbo码作为数据和间接信道的前向纠错码(FEC)方案。因此,人们提出了许多有效的算法来解码这些代码。然而,这两类代码的不同解码方法通常会导致不同的硬件架构。由于这些代码在这些新的无线系统中并行工作,因此引入一个通用解码器来处理这两个代码族是一个好主意。本研究利用咬尾卷积和turbo码的奇偶校验矩阵(H)表示,从而通过统一的信念传播(BP)算法实现解码。事实上,BP算法为设计所有卷积码类和turbo码的低复杂度迭代解码算法提供了一种高效的通用方法。虽然使用BP而不是MAP解码turbo码时观察到较小的性能损失,但这被BP算法较低的复杂性和统一解码架构的固有优势所抵消。
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引用次数: 0
A SECURE ANTI-COLLUSION DATA SHARING SCHEME FOR DYNAMIC GROUPS IN THE CLOUD 一种针对云中动态组的安全防合谋数据共享方案
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/55722018
Ewit
Cloud computing is used to achieve an effective and economical approach for data sharing among group members with the characters of low maintenance and little management cost. Sharing data while providing privacy-preserving is still a challenging issue, especially for an entrusted cloud due to the collusion attack. First, a secured way for key distribution without any secure communication channels is created. Second, can achieve fine-grained access control. Third, we can protect the scheme from collusion attack. Finally, fine efficiency is achieved which means previous users need not to update their private keys for the situation either a new user joins in the group or a user is revoked from the group.
采用云计算实现群组成员之间的数据共享,具有维护成本低、管理成本低的特点。在提供隐私保护的同时共享数据仍然是一个具有挑战性的问题,特别是对于由于串谋攻击而受委托的云。首先,在没有任何安全通信通道的情况下,创建了一种安全的密钥分发方式。第二,可以实现细粒度的访问控制。第三,我们可以保护方案免受合谋攻击。最后,实现了良好的效率,这意味着以前的用户不需要更新他们的私钥,以应对新用户加入组或用户从组中被撤销的情况。
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引用次数: 1
Audio/Text Aided System Using Sign Language 使用手语的音频/文本辅助系统
Pub Date : 2018-06-15 DOI: 10.30534/IJCCN/2018/10722018
Ewit
This paper presents an intelligent system allowing handicapped aphasiacs to perform basic communication tasks. It has the following features:A 2-sensor data measures the hand gestures of a patient in terms of the bending degrees of his hands,A hand language recognition subsystem recognizes language components from the hand gestures. It employs multiple regression analysis to automatically extract proper hand features so that the recognition model can be fast and correctly constructed by a radial basis function neural network,A coordinate-indexed virtual keyboard allows the users to directly access the letters on the keyboard at a practical speed. The system serves as a viable tool for natural and affordable communication for handicapped aphasiacs through continuous hand language input.
本文提出了一个智能系统,允许残疾失语症患者执行基本的沟通任务。它具有以下特点:一个双传感器数据根据患者双手的弯曲程度来测量患者的手势,一个手势语言识别子系统从手势中识别语言成分。采用多元回归分析,自动提取合适的手部特征,通过径向基函数神经网络快速、正确地构建识别模型;采用坐标索引虚拟键盘,使用户能够以实用的速度直接访问键盘上的字母。该系统通过持续的手部语言输入,为残疾失语症患者提供了一种可行的、自然的、负担得起的交流工具。
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引用次数: 0
SECURE ANALYSIS OF SENSOR DATA IN BIG-DATA PLATFORM FOR GEO-SOCIAL NETWORK 地理社交网络大数据平台中传感器数据的安全分析
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/43722018
Ewit
: Geosocial Network information can be provided as service for the users to take decisions for the events that occurs in the real-world like earth quakes, bombblast, and fire and also other events occurred in the different places in the world. After analyzing the data the user can able to take decisions for the real-time to predict for the future which are the places that will be affected by the particular events.We propose a system that should be able to handle the data generated by the different sensors in a secure manner the data sent by the sensors will be stored in the encrypted format in the Geo-social network. When the user is searching for the particular event that occurred the user need to decrypt the data before using the information . Twitter is analyzed using the proposed system to recognize the events like earth quakes, fire, Bomb related data. We are using the Hadoop system for analysis of the big-data generating by the different sensors.
: Geosocial Network信息可以作为服务,为用户提供在现实世界中发生的事件,如地震、爆炸、火灾等,以及在世界不同地方发生的其他事件的决策。在分析数据后,用户可以实时做出决策,预测未来哪些地方会受到特定事件的影响。我们提出了一个系统,应该能够以安全的方式处理不同传感器产生的数据,传感器发送的数据将以加密格式存储在地理社交网络中。当用户搜索发生的特定事件时,用户需要在使用信息之前对数据进行解密。利用所提出的系统对Twitter进行分析,以识别地震、火灾、炸弹等事件相关数据。我们正在使用Hadoop系统来分析不同传感器产生的大数据。
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引用次数: 0
Characterization of Health Data using Neural Network and Routing in Health Monitoring 健康监测中使用神经网络和路由表征健康数据
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/49722018
Ewit
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引用次数: 0
NAVIGATION OF CATAMARAN USING WIRELESS TECHNOLOGY 双体船无线导航技术
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/23722018
Ewit
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引用次数: 0
Health Monitoring System Using IoT and Raspberry Pi 使用物联网和树莓派的健康监测系统
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/34722018
Ewit
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引用次数: 1
ACCESS CONTROL FOR TIME SENSITIVE DATA BY USING TIME AND ATTRIBUTE FACTORS IN PUBLIC CLOUD 利用公有云中的时间和属性因素对时间敏感数据进行访问控制
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/20722018
Ewit
Cloud storage benefit has critical points of interest on both advantageous information sharing and cost lessening. Therefore, an ever increasing number of endeavors and people outsource their information to the cloud to be profited from this administration. Nonetheless, this new worldview of information stockpiling postures new difficulties on information secrecy conservation. As cloud benefit isolates the information from the cloud benefit customer (people or substances), denying their immediate control over these information, the information proprietor can't believe the cloud server to lead secure information get to control. In this way, the safe access control issue has turned into a testing issue out in the open cloud storage.
云存储的好处在有利的信息共享和降低成本两个方面都具有关键点。因此,越来越多的努力和人们将他们的信息外包给云,以从这种管理中获利。然而,这种新的信息储存世界观给信息保密提出了新的难题。由于云效益将信息与云效益客户(人或物)隔离开来,拒绝他们对这些信息的直接控制,信息所有者无法相信云服务器会导致安全信息得到控制。这样,安全访问控制问题就变成了开放云存储中的一个测试问题。
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引用次数: 0
IMPLEMENTATION OF SMARTCRAWLER FOR DEEP-WEB SITES 深层网站的智能爬虫实现
Pub Date : 2018-06-15 DOI: 10.30534/ijccn/2018/30722018
Ewit
Deep web is termed as data present on web but inaccessible to search engine. Due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. Smart crawler for hidden web interfaces consist of mainly two stages, first is site locating another is in-site exploring. Site locating starts from seed sites and obtains relevant websites through reverse searching and obtains relevant sites through feature space of URL, anchor and text around URL. Second stage takes input from site locating and goes to find relevant link from those sites. The adaptive link learner is used to find out relevant links with help of link priority and link rank.. To eliminate bias on visiting some highly relevant links in hidden web directories, we design a link tree data structure to achieve wider coverage for a website.
深网是指存在于网络上但搜索引擎无法访问的数据。由于网络资源的巨大容量和深网的动态性,实现广覆盖和高效率是一个具有挑战性的问题。隐藏界面智能爬虫主要包括两个阶段,一是站点定位阶段,二是站点内探索阶段。网站定位从种子网站开始,通过反向搜索获得相关网站,通过URL、锚点、URL周围文字的特征空间获得相关网站。第二阶段从站点定位输入,并从这些站点找到相关链接。自适应链接学习器通过链接优先级和链接等级来寻找相关链接。为了消除访问隐藏网络目录中一些高度相关链接的偏见,我们设计了一个链接树数据结构,以实现网站的更广泛覆盖。
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引用次数: 0
DENSITY BASED TRAFFIC SIGNAL CONTROL WITH POWER SAVER STREET LIGHT 基于密度的节能路灯交通信号控制
Pub Date : 2018-06-15 DOI: 10.30534/IJCCN/2018/19722018
Ewit
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引用次数: 0
期刊
International Journal of Computing, Communications and Networking
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