基于Aloha算法的帧长及分组数改进研究

对射频识别（RFID）系统中一类解决多标签间碰撞问题的防碰撞算法现状进行了综述,分析了各算法的优势与不足。针对目前最常用的动态帧时隙算法,在分析其帧长调整方法缺点的基础上,提出了一种帧长及分组数动态调整方案。仿真结果显示,改进方案提高了系统的识别效率和稳定性。     

全分组不等长时隙的DFSA算法

标签碰撞是无线射频识别技术中的常见问题,它将大大降低系统的效率,如何有效解决这个问题对整个系统来说尤其重要。首先对Aloha及其几种改进算法进行研究分析,针对目前最常用的动态帧时隙算法中标签估计和帧长调整方法存在的缺点,根据冲突问题本身,以及Aloha防冲突机制的数学特性,对识别过程进行分析,提出了一种帧长及分组数动态调整方案,减少空时隙和碰撞时隙占用时间,同时制定取舍规则,当标签数量大时,在识别初始阶段分组延迟一部分标签。仿真证明,该方案可减少标签冲突,提高识别效率。     

分组部分时隙帧预测的RFID防碰撞算法

针对最大帧长度受限情况下射频识别中的标签碰撞问题,提出分组部分时隙帧预测ALOHA算法。通过分组操作,限定每次待识别标签数在最大帧长的有效识别范围内。采用部分时隙帧预测,若部分时隙的碰撞或空闲比例超过门限值,则立即调整帧长,从而减少使用的时隙数。实验结果表明,该算法能有效降低使用的时隙数,提高系统识别效率,在标签大量动态变化的情况下,平均识别率可达35.58%,具有良好的适用性。     

一种优化帧长及分组的动态帧时隙防碰撞算法

在改进防碰撞算法的研究中,针对现有RFID系统中易发生碰撞与标签数过大时识别效率低等现象,通过对现有防碰撞算法进行分析,提出了一种优化帧长及分组的动态帧时隙防碰撞算法;通过预先估算系统的标签数并将其分类处理,当标签数小时,通过引入查询命令时间T完善帧长的调整机制并采用自适应选择模式;当标签数大时,根据标签位数进行二进制分组模式;从而达到简化硬件电路、提高算法的准确率的目的.实验结果表明,算法具有稳定性高、冲突率低等优势,具有一定的实用价值.     

自适应帧长调整DS-ALOHA防碰撞算法

针对射频识别(RFID)碰撞发生概率较大等问题及读写时隙、帧长等参数影响识别性能等分析,提出了高效自适应帧长调整动态时隙ALOHA(DS-ALOHA)防碰撞算法。它在RFID阅读器对应答器读写中,通过估计应答器数量,自适应调整帧长及动态时隙,使帧长与应答器数量相匹配,获得最佳吞吐量,极大减小碰撞概率,以有效提高传输效率。仿真表明:与现有算法相比,在应答器数为1000等相同条件下,传输时隙减少了约200个,较好改善了RFID系统识别效果,可用于快速标记识别物联网等实用系统。     

基于信号强度的分组帧时隙ALOHA防碰撞算法

针对现有ALOHA防碰撞算法存在系统吞吐量低下的问题,利用射频识别阅读器和标签之间的信号能量传输特点,对帧时隙ALOHA算法( FSA)进行改进,提出一种分组帧时隙ALOHA防碰撞算法。根据接收信号能量的强度将标签均匀分布到帧时隙中进行分组应答,从而降低标签碰撞概率。仿真实验结果表明,在标签数与帧时隙数之比小于1.8的情况下,该算法最大系统吞吐量可达50%,优于FSA算法及碰撞分组算法。     

一种新的RFID混合防碰撞算法

针对射频识别（RFID）系统随机性防碰撞算法中标签识别效率低的问题,提出了一种新的RFID混合防碰撞算法。新算法采用帧时隙ALOHA（FSA）机制,根据碰撞时隙数直接估计出总的未识读标签数目,经多次动态调整帧长,获得最优帧长,然后使读写器按照最优帧长分配时隙以供标签响应,在碰撞时隙内调用自适应搜索矩阵（ASM）算法对响应标签进行识别。理论研究和仿真表明,新算法有效实用,可有效提高系统性能,使时隙吞吐量达到40%以上。     

降低无效时隙开销的RFID防碰撞算法

为了进一步提高射频识别系统的识别效率,降低空时隙和碰撞时隙时长,提出了一个降低无效时隙开销的防碰撞算法。该算法将空时隙和碰撞时隙的检测分开进行处理,降低了无效时隙的开销。并根据时隙不等长原理动态调整帧长,最大限度地降低无效时隙的开销,以获得最优的识别效率。算法分析和仿真实验结果表明该算法降低了空时隙和碰撞时隙的时长,识别速度明显增加,在一个识别周期内成功时隙数增多,碰撞时隙数减少,帧长的调整次数减少。     

基于分组动态帧时隙的RFID防碰撞算法

为了解决射频识别(RFID)系统中的多标签防碰撞问题,在分析帧时隙ALOHA算法的基础上,提出一种基于分组动态帧时隙的RFID防碰撞算法。当标签数量庞大时,该算法可以通过分组限制响应标签数量达到较高的识别效率。仿真结果表明,当标签数为1 000时,与传统算法相比,该算法能使时隙利用率提高80%以上。     

RFID系统中一种动态帧时隙算法的研究与仿真

在多个电子标签的识别过程中,利用防碰撞算法解决标签的碰撞问题是射频识别系统中的一项关键技术。对一种动态帧时隙Aloha算法进行了描述与仿真,根据估算所得的标签数,结合标签的EPC对标签进行了分组,将分组码作为激活码每次激活一组标签而屏蔽其它标签,对激活的这组标签用FSA算法进行识别。采用这种方法可将每次响应的标签数目限制在一定范围之内,并且与最大帧长基本匹配,从而在各个识别周期之内不需要再调整帧长,简化了算法且保证了较高的识别率。仿真结果表明：在标签数目较大时,阅读器的识别效率可以稳定在30.5%—36.     

一种ALOHA算法的帧长度调整方法

在介绍动态帧时隙ALOHA算法的基础上,提出了一种帧长度调整算法。该方法利用一帧周期中碰撞及正确接收的信息推测阅读器有效范围内可能存在的标签数目,指导阅读器设定适当的值继续下一帧清点。仿真表明该方法具有可行性和实用性。     

A novel-Q DFSA algorithm for passive RFID system

The tag detection ability of Passive Radio Frequency Identification (RFID) systems are critically challenged by the collision occurrence due to simultaneous responding tags during the identification process. The dynamic scheduling of the frame size governed by Dynamic Frame Size ALOHA(DFSA) process, by adjusting the frame lengths according to the size of tag population can avoid the collisions during the identification. However, the performance of DFSA majorly depends on the frame size selection policy which in previous studies was adopted to achieve the target of throughput maximization during a frame. This condition is obtained at the cost of equating the frame size up to the number of estimated tags responding during the time frame. This approximation enhances the throughput value but contributes to massive energy wastages as the frame lengths approach to a very large value in large tag population size. Therefore, it is essential to develop the new frame size estimation policy for DFSA achieving the aim of optimization between throughput and energy for improved time and energy performance. In this paper, we have proposed an EPC C1G2 standards based Novel-Q DFSA algorithm which optimizes the frame size accounting both the energy and the throughput. The combined throughput and energy trade-offs are measured through Energy–Time-Delay (ET) cost which is minimum for our proposed algorithm compared to the existing solutions. Furthermore, the Throughput-Time Delay product approves the stability in large population size making it suitable for numerous identification applications.     

Super-resolution with selective filter based on adaptive window and variable macro-block size

Super-resolution (SR) covers a set of techniques whose objective is to improve the spatial resolution of a video sequence or a single frame. In this scope, fusion SR techniques obtain high-resolution (HR) frames taking as a reference several low-resolution (LR) frames contained in a video sequence. This paper is based on a selective filter to decide the best LR frames to be used in the super-resolution process. Additionally, each frame division into macro-blocks (MBs) is analyzed both in a fixed block size approach, which decides which MBs should be used in the process, and in a variable block size approach with an adaptive MB size, which has been developed to set an appropriate frame division into MBs with variable size. These contributions not only improve the quality of video sequences, but also reduce the computational cost of a baseline SR algorithm, avoiding the incorporation of non-correlated data. Furthermore, this paper explains the way in which the enhanced algorithm proposed in it outperforms the quality of typical SR applications, such as underwater imagery, surveillance video, or remote sensing. The results are provided in a test environment to objectively compare the image quality enhancement obtained by bilinear interpolation, by the baseline SR algorithm, and by the proposed methods, thus presenting a quantitative comparison based on peak signal-to-noise ratio (PSNR) and Structural SIMilarity (SSIM) index parameters. The comparison has also been extended to other relevant proposals of the state of the art. The proposed algorithm significantly speeds up the previous ones, allowing real-time execution under certain conditions.     

视频监控中无监督异常事件检测

介绍了一种视频监控中无监督异常事件检测方法,其核心是通过均值法将训练视频对视频的背景进行提取,用帧差法将背景提出并测算面积并划分正常面积值域。用同样的方法对测试视频进行检测,若超过阈值范围,则标记异常目标。     

RFID系统实时高效ALOHA防冲突算法研究与仿真

简要介绍了当前几种主要的ALOHA算法基本思想和系统效能,详细讨论了间接估算自适应帧时隙（DFSA）算法的原理和帧长度调整方法,并就DFSA算法对未识读标签的估计方法进行了统计分析,最后基于MatLab对各种算法性能进行了仿真。结果表明,间接估算DFSA算法较其它算法更能使RFID系统保持较高的系统效率,能够实时准确地识别标签。     

三维场景中高分辨率输出技术的研究

论文围绕三维景观系统中的高分辨率输出技术进行了分析与探讨,针对传统输出方法因受帧缓冲大小的限制所存在的不足之处,提出了一种新的行之有效的高分辨率输出方法。其主要思想是对整个三维场景采用“分而绘之”的方法,通过动态调整透视投影参数来达到不同区域场景的高分辨率独立绘制,并最终获得满足要求且无缝拼接的三维渲染效果图。     

Dynamic frame length channel assignment in wireless multihop ad hoc networks

A good channel assignment scheme in a multihop ad hoc network should not only guarantee successful data transmissions without collisions but also enhance the channel spatial reuse to maximize the system throughput. From the channel assignment schemes in time division multiple access (TDMA) slot assignment protocols developed in previous studies, we have found that these protocols do not have a convenient frame length shrink scheme after the expansion of the frame length. As the network size grows, the frame length expands quickly, particularly when we set the frame length as a power of two. A very long frame may result in poor channel utilization when it contains many unused slots. In this paper, we propose a dynamic frame length expansion and recovery method called dynamic frame length channel assignment (DFLCA). This strategy is designed to make better use of the available channels by taking advantage of the spatial reuse concept. In DFLCA, the increase in the spatial reuse is achieved by adding certain amount of control overhead. We show that the bandwidth saved due to the channel spatial reuse is larger than the additional bandwidth spent on the control overhead.     

基于光纤智能夹层的车架有限元分析与试验研究

以某型轻卡车架为研究对象,建立了车架有限元模型,提出采用光纤智能夹层结构分析弯曲、扭转工况下车架的应力分布。采用波分复用形式构建了分布式光纤智能夹层传感器网络,对车架在弯曲、扭转工况下车架关键点的应力分布进行了试验研究,并用Patran软件进行了车架结构静强度的有限元分析。试验结果与有限元模拟结果吻合得较好。该研究结果为同型车型开发、改型及优化设计提供了技术手段和依据。     

分数频率复用的帧结构及性能分析

针对现代无线通信系统在干扰控制方面越来越高的要求,利用通信帧中子载波的重新分配,提出了帧结构设计中一种新的分数频率复用方法—时频分分数频率复用,并将其与传统的分数频率复用方式进行比较。这一新方法是在对系统容量进行建模之后,综合资源块分配中的时分和频分模式提出的,其对应的帧结构相对于传统的FFR具有更高的调节粒度。实验结果验证了这种设计以少量系统容量为代价,在提升系统公平性、提高边缘用户吞吐率方面的性能优势。