• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Sequential Monte Carlo methods for data detection and channel parameters estimation.
【24h】

Sequential Monte Carlo methods for data detection and channel parameters estimation.

机译：用于数据检测和信道参数估计的顺序蒙特卡洛方法。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Mobile wireless channels are characterized by time-variation and multipath propagation which result in intersymbol interference (ISI) and sever distortion of the pulse shape of the transmitted data. Data detection in such environment requires the development of equalization techniques that can reverse, or at least minimize, the deleterious effect of the channel. The design of such equalization techniques is challenging as the equalizers are required to be sufficiently fast to adaptively estimate the time-varying channel. Moreover, prior to equalization, accurate estimation of the synchronization parameters is critical for reliable communication. Unfortunately, optimal estimators for synchronization parameters are impossible to obtain in general and, therefore, most of the existing techniques are based on approximate and heuristic methods.; In this thesis work, we developed novel equalization and synchronization algorithms for data detection over mobile wireless channels. Our approach to the problems is based on the Bayesian methodology by deriving sequential Monte Carlo, also known as particle filtering, algorithms. We regard the application of particle filtering in this context very appealing, as it is capable to yield near optimal numerical solutions when, as in this case, analytic solutions do not exist.; In the first part of the thesis work, we deal with the equalization problem. The problem is first formulated as dynamic state space (DSS) model where the channel values and the transmitted data are considered as the hidden states of the model whereas the received signal is taken as the observed signal. With this formulation, we have developed blind algorithms for joint data detection and channel estimation in frequency-selective channels based on particle filtering. The proposed algorithms are flexible and efficient and have shown, through computer simulations, better performance than the per-survival-processing which is the popular conventional method.; In the second part of the thesis work, we develop particle filtering based algorithms for the joint estimation of synchronization parameters and the detection of transmitted data. In doing so, we first represent the problem in an extended DSS model where we assume the symbol delay and the frequency offset variation to be first-order autoregressive (AR) stochastic processes. Furthermore, the flat-fading channel, whose complex coefficient can be considered as the signal amplitude attenuation and phase offset, is modeled by a second-order AR process driven by a complex white Gaussian noise. With this formulation, efficient and blind algorithms based on particle filtering methods are developed. In the development of the synchronization algorithms, two receiver configurations that remove the ISI and consequently that enable us to attain close-to-optimal symbol error rate (SER) are proposed. Computer simulations demonstrated that the developed algorithms achieve close to optimal performances and are superior to receivers based on the conventional timing error detectors (TEDs).
机译：移动无线信道的特点是时变和多径传播，这会导致符号间干扰（ISI）和传输数据的脉冲形状严重失真。在这样的环境中的数据检测需要开发均衡技术，该均衡技术可以逆转或至少最小化信道的有害影响。由于要求均衡器足够快以自适应地估计时变信道，因此这种均衡技术的设计具有挑战性。此外，在均衡之前，同步参数的准确估计对于可靠的通信至关重要。不幸的是，通常不可能获得同步参数的最佳估计量，因此，大多数现有技术都是基于近似和启发式方法的。在本文工作中，我们开发了新颖的均衡和同步算法，用于通过移动无线信道进行数据检测。我们针对这些问题的方法是基于贝叶斯方法，通过推导顺序蒙特卡罗算法（也称为粒子滤波）算法。在这种情况下，我们认为粒子滤波的应用非常吸引人，因为当不存在解析解时，它能够产生接近最佳的数值解。在论文的第一部分中，我们处理均衡问题。首先将问题表述为动态状态空间（DSS）模型，其中将通道值和传输的数据视为模型的隐藏状态，而将接收到的信号视为观察到的信号。通过这种公式，我们已经开发了基于粒子滤波的频率选择信道中联合数据检测和信道估计的盲算法。所提出的算法灵活高效，并且通过计算机仿真显示出比普遍使用的常规方法的每个生存过程更好的性能。在论文的第二部分，我们开发了基于粒子滤波的算法，用于联合估计同步参数和检测传输数据。这样做时，我们首先在扩展DSS模型中表示问题，在该模型中，我们将符号延迟和频率偏移变化假定为一阶自回归（AR）随机过程。此外，其平坦系数的复数可被视为信号幅度衰减和相位偏移的平坦衰落信道是由复杂的高斯白噪声驱动的二阶AR过程建模的。利用这种公式，开发了基于粒子滤波方法的高效且盲目的算法。在同步算法的发展中，提出了两种接收机配置，它们消除了ISI，从而使我们能够获得接近最佳的符号误码率（SER）。计算机仿真表明，所开发的算法可达到接近最佳的性能，并且优于基于常规定时误差检测器（TED）的接收器。

著录项

  • 作者

    Ghirmai, Tadesse.;

  • 作者单位

    State University of New York at Stony Brook.;

  • 授予单位 State University of New York at Stony Brook.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 171 p.
  • 总页数 171
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号