Localized Coverage Connectivity Based on Shape and Area Using Mobile Sensor Robots in Wireless Sensor Networks

A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works.

Application of Wireless Local Area Network Technology in Mobile Robot for Finned Tube Inspection

This paper introduces a novel robot for outer surface inspection of boiler tubes. The paper describes the hardware system, wireless communication strategy, communication procedure and system software of the robot. The WLAN technology is used in the robot. It solves the problem of shielding generated by iron boiler and 11Mbps bandwidth made it possible for video and control stream real-time transmit within the same channel. Though TCP/IP protocol is robust, serial server is a transparent channel but cannot detect error and retransmit the data. In order to improve the reliability of serial communication, a new communication protocol is proposed. Key words boiler tubes - mobile robotics - wireless local area network Project Supported by the National High-Tech Program (Grant No. 2002AA420080)

Research on the Teaching Reform of ＂Wireless Local Area Network＂ in the Background of＂Wireless Business Circle＂

This paper proposes the teaching reform of the ＂Wireless Local Area Network＂ in the background of ＂Wireless Business Circle＂ . At present, WLAN technology is becoming more and more mature, the application is then becoming more and more extensive, the campus network will grow rapidly on wireless LAN applications especially the research and higher education institutions on the wireless LAN demand is increasing with wireless LAN will have a very broad market development space. GIS business circle analysis model is to determine business enterprise location or expand their existing business outlets of information necessary to say on the map by G1S visual function of the model. This paper makes the combination of the mentioned items that will then and later influence the performance of the model.

基于自发数据传输的高效双LAN太赫兹无线局域网MAC协议

针对现有的双局域网(LAN)太赫兹无线局域网(Dual-LAN THz WLAN)相关介质访问控制(MAC)协议中存在的某些节点会在多个超帧内重复发送相同的信道时隙请求帧以申请时隙资源以及网络运行的一些时段存在空闲时隙等问题,提出一种基于自发数据传输的高效MAC协议——SDTE-MAC(high-Efficiency MAC protocol based on Spontaneous Data Transmission)。SDTE-MAC通过让各节点都维护一张或多张时间单元链表,使各节点与其余节点在网络运行时间上达到同步,从而获悉各节点应该在信道空闲时隙的什么位置开始发送数据帧,优化了传统的信道时隙分配和信道剩余时隙再分配的流程,提高了网络吞吐量和信道时隙利用率,降低了数据时延,能够进一步提升双LAN太赫兹无线局域网的性能。仿真结果表明,网络饱和时,相较于AHT-MAC(Adaptive High Throughout multi-pan MAC protocol)中的N-CTAP(Normal Channel Time Allocation Period)时段时隙资源分配新机制以及自适应缩短超帧时段机制,SDTE-MAC的MAC层吞吐量提升了9.2%,信道时隙利用率提升了10.9%,数据时延降低了22.2%。

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 protocol.Due to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate users.Moreover,the security design of the wireless structure is vulnerable to versatile attacks.For example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false messages.Althoughmany security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world applications.This paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks effectively.The proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the attack.The scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in theWLAN.The proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related work.The experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

基于IRF-PF算法的WLAN室内定位方法

针对室内复杂环境下无线局域网接收信号强度的时变波动性,提出一种基于改进随机森林算法并融合粒子滤波的室内定位方法。首先,通过自适应滑动窗口选取接收信号强度较为平滑的信号接入点作为定位指纹特征建立决策树,从而减少特征空间的噪声;然后,利用bagging抽样后的袋外数据赋予决策树不同的投票权重等级,增大决策树类别间判别差异性,优化随机森林算法在目标位置与接收信号强度间弱映射关联性场景下定位精度低的问题,依据改进的随机森林算法建立位置坐标与接收信号强度间的映射模型,计算定位点的位置;最后,为了提高定位准确性与稳定性,将依据改进随机森林算法计算出的位置作为粒子滤波的观测量,利用粒子滤波对目标位置进行估计和预测。在Zenodo数据集上的实验结果表明:提出的算法在定位误差2 m范围内精度达到75.8%,在4 m范围内精度已经高达94.8%;相比于传统随机森林算法,能够将2 m内的定位精度提高11.5%;与K近邻、岭回归和贝叶斯等室内定位算法相比,定位精度和算法实时性也得到明显提升。

CBTC系统WLAN车地无线通信网络在线监测关键技术及应用

目前国内大部分城市轨道交通车地无线通信系统仍采用IEEE 802.11 b/g协议,工作在2.4 GHz ISM开放频段,车地通信故障易造成列车紧急停车等情况。针对目前车地无线通信监测完整性和实用性不足、全链条监测手段缺乏等问题,结合无线通信系统范围广、场景多、故障现象迷惑性强等特点,融合无线场强采集、数据流监听、无线图谱定位、贝叶斯网络故障等定位技术,利用软硬件结合的方式构建全链条车地无线智能分析监测系统。采用射频处理单元+运行处理单元软硬件分离的架构模式设计无线监测终端,采用C/S架构和人工智能技术设计车地无线智能分析监测系统,实现从车载到轨旁无线场强、漫游切换、多信道监测等智能分析功能。该系统已在北京地铁亦庄线、昌平线、10号线等多条线路上应用,运用效果良好,满足现场无线监测需求,大幅提升了车地无线通信监测能力及应急处置响应效率,对保障列车运营安全具有重要意义。

Wireless-LAN安全及认证方法的研究与分析

首先介绍了无线局域网面临的安全问题,并对无线局域网的安全要求进行了分析;介绍了国内外Wire-less-LAN安全认证机制的研究现状,在此基础上详细分析了基于EAP的无线网络安全认证方法;最后对几种主要的认证方法进行了分析比较。

An adaptive joint source and channel coding scheme for H.264 video multicasting over wireless LAN

This paper proposes an adaptive joint source and channel coding scheme for H.264 video multicast over wireless LAN which takes into account the user topology changes and varying channel conditions of multiple users, and dynamically allocates available bandwidth between source coding and channel coding, with the goal to optimize the overall system performance. In particular, source resilience and error correction are considered jointly in the scheme to achieve the optimal performance. And a channel estimation algorithm based on the average packet loss rate and the variance of packet loss rate is proposed also. Two overall performance criteria for video multicast are investigated and experimental results are presented to show the improvement obtained by the scheme.

Radio map updated method based on subscriber locations in indoor WLAN localization

With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.

A Semi-Supervised WLAN Indoor Localization Method Based on l1-Graph Algorithm

For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be collected in offline phase. Therefore,collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper,the traditional semisupervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed,and the result shows that the k-NN or ε-NN graph are sensitive to data noise,which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem,it proposes a l1-graph-algorithm-based semi-supervised learning( LG-SSL) indoor localization method in which the graph is built by l1-norm algorithm. In our system,it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase,and then uses LG-SSL to estimate user's location in online phase. Extensive experimental results show that,benefit from the robustness to noise and sparsity ofl1-graph,LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.

基于VxLAN协议的新型SDN架构及应用

针对指挥信息系统云数据中心的传统网络架构存在的网络资源利用率不高、网络策略与业务无法自适应以及虚拟机迁移困难等问题,设计了一种基于虚拟扩展本地局域网(VxLAN)协议的新型软件定义网络(SDN)架构。分析了该架构的优势及信息处理流程,并以指挥信息系统双活云数据中心为例给出了该架构的应用效果。应用分析可见,该架构既可满足网络集中控制和网络服务质量适应差异化业务的需求,又可提升网络资源利用率、虚拟机跨域迁移能力以及指挥信息系统运行稳定性与可靠性。

基于神经网络和遗传算法的高密集WLAN公平性保障算法

为了满足用户在各类场景下对无线业务日益增长的要求,高密集部署的无线局域网(wireless local area network,WLAN)是未来发展的趋势。但由于频率资源有限,相同信道必然存在多个WLAN无线接入点(access point,AP),然而处于同一信道的AP会互相干扰,造成网络中小区间吞吐量的公平性下降,无法为用户提供良好的服务质量。为了提高网络公平性,改善用户体验,需要制定合理的网络参数调优方法,给出了一种基于神经网络和遗传算法对WLAN参数优化的方法。采用神经网络构建网络参数与网络吞吐量公平性之间的映射,将训练完成的模型作为遗传算法的适应度评估函数,通过遗传算法求解优化参数组合配置来改善WLAN吞吐量公平性问题。仿真结果表明所提出算法能够使得高密集WLAN吞吐量公平性得到提升。

Synchronization in Wireless Networks for Practical MIMO-OFDM Systems

In this paper a frequency offset estimation technique for Wireless Local Area and Wireless Metropolitan Ar- ea Networks is presented. For frequency offset estimation, we have applied a low-complexity frequency offset estimator for simple AWGN channels to fading channels for MIMO-OFDM systems. Simulation results have shown that the performance of the proposed estimator is better than the low complexity frequency offset estimator designed for AWGN channels.

A NOVEL LINK ADAPTATION SCHEME TO ENHANCE PERFORMANCE OF IEEE 802.11G WIRELESS LAN

A novel link adaptation scheme using linear Auto Regressive （AR） model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength （RSS） is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed schelne.

一种宽带WLAN贴片天线

文中提出了一种单馈的宽带贴片天线应用于无线局域网络通信。该天线由方形贴片、电抗性阻抗表面以及电磁带隙结构组成。文中提出同时加载电抗性阻抗表面和电磁带隙结构能够实现小型化以及宽带化。电抗性阻抗表面作为接地平面能够降低天线的谐振频率。电磁带隙结构能够提高天线的阻抗带宽。测试结果表明所提出的WLAN贴片天线的相对带宽为22.3%(S11=-10 dB),覆盖4.77~5.97 GHz,可以获得6.3~7.2 dBi增益。与现有宽带小型化天线相比,该天线在保证宽带小型化的前提下仍具有较高增益,且辐射性能具有较高的一致性,十分有利于其应用。该天线能够覆盖IEEE 802.11a标准所规定的5 GHz频段,能够实现无线局域网之间的高速数传。

802.11ax WLAN与LTE系统共存环境中的用户分配方案

随着使用智能设备移动用户的爆炸式增长,无线局域网逐渐呈密集部署态势。2021年发布的IEEE802.11ax标准与持续演进的系统长期共存。针对共存环境下用户如何连接网络实现用户吞吐量最大化的问题,提出了吞吐量感知的用户分配方案。该方案将两种网络的性能与用户需求相匹配,并基于实际距离分配用户连接哪个网络。数值分析表明,所提出的方案在吞吐量和能效方面优于已有方案。

多媒体中WLAN技术的跨层设计分析

随着移动通信技术的快速发展,无线局域网(Wireless Local Area Network,WLAN)技术成为人们日常生活中的重要组成部分。然而由于无线信道的不稳定性和带宽资源的有限性,如何提高多媒体传输的效率和质量成为一个重要的研究课题。跨层设计作为一种有效的解决方案,可以在不同的网络层之间进行信息交互,从而提升整个系统的性能。基于此,文章主要分析跨层设计在WLAN无线网络通信技术中的应用意义和策略,并展望未来的发展方向。

基于WLAN分析的网络安全技术

由于无线网络主要在开放的空间环境内展开数据信息传输,而不是固定在物理线缆上,存在一定的安全隐患。因此,必须要优化落实对无线网络的安全防护。文章强调了无线局域网(Wireless Local Area Network,WLAN)安全防护的必要性,并对恶意攻击、非法用户入侵、重传攻击等影响计算机无线网络安全的主要因素进行了分析。在此基础上,从无线与有线一体化关联分析技术、无线网络安全保障机制、WLAN安全技术这几方面入手,着重阐述了基于WLAN的网络安全防护技术的具体应用,以营造更为安全的WLAN无线网络运行环境。

基于LTE-M与WLAN混合组网的通信系统可靠性研究

近年来,城市轨道交通建设加速增长,对城市轨道交通车地通信系统的可靠运行提出了更高的要求。随着第四代移动网络(4th Generation mobile networks,4G)具体化的长期演进(Long Term Evolution,LTE)系统已经广泛地进行了部署,而且技术也逐渐趋于成熟,地铁长期演进(Long Term Evolution for Metro,LTE-M)车地通信系统具有较强的抗干扰能力、支持快速移动状态下的列车通信、资源调度灵活等优点,突破融合不同通信制式的关键技术,研制出信号通信设备样机,并根据列车控制系统的业务需求对新的通信制式进行测试,保障城铁列车的安全稳定运行。