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Channel estimation and equalization for doubly-selective channels using basis expansion models.

机译：使用基本扩展模型的双选信道的信道估计和均衡。

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摘要

The nature of the wireless channels places fundamental limitations on the performance of wireless communication systems. In addition to the frequency-selectivity characteristics caused by multipath propagation, the high-rate wireless and mobile links often exhibit time-selectivity characteristics caused by the user's mobility, so-called doubly-selective wireless channels. The quality of channel acquisition has a major impact on the overall system performance. Therefore, reliable estimation of doubly-selective channels is well motivated. Equalization is used at the receiver to compensate for intersymbol interference created by multipath propagation and improve received signal quality. Equalizers should be adaptive since the channel is time-varying.;In this dissertation, channel estimation and equalization for doubly-selective channels are considered in Chapter 2 (under single input single output models) and Chapter 3 (under multiple input multiple output models), where the time-varying channel is assumed to be well described by basis expansion models (BEM). Our focus is on time-multiplexed training for channel estimation where the training symbols are periodically inserted and use all transmitted power during their transmission.;The linear equalization and decision feedback equalization (DFE) of doubly-selective channels modeled via BEMs are introduced in Chapter 4. There has been much interest in designing time-variant serial finite impulse response (FIR) linear and DFE equalizers using complex exponential (CE-) BEMs for equalizers in addition to using CE-BEM for modeling the channel itself. In this dissertation we show that the Kalman filter formulation of the linear equalizer and an alternative formulation of the FIR DFE based on a CE-BEM channel model yields the same or an improved BER at a lower computational cost, without incurring the approximation error inherent in CE-BEM modeling of equalizers.;In Chapter 5, an adaptive channel estimation scheme, exploiting the oversampled complex exponential basis expansion model (CE-BEM), is presented for doubly-selective channels where we track the BEM coefficients via a multiple model approach in this dissertation. We propose to use a multiple model framework where several candidate Doppler spread values are used to cover the range from zero to an upper bound, which leads to multiple CE-BEM channel models, each corresponding to an assumed value of the Doppler spread. Subsequently, the well known interacting multiple model (IMM) algorithm is used for symbol detection based on multiple state-space models corresponding to the multiple estimated channels.;Orthogonal Frequency-Division Multiplexing (OFDM), a digital multi-carrier modulation scheme, has developed into a popular scheme for wideband wireless communication due to its high spectral efficiency and simple equalization. We extend the optimum time-multiplexed training based channel estimation introduced in Chapter 2 to OFDM systems under doubly-selective channels in Chapter 6. Compared to the traditional frequency-domain training design, the main advantages of time-domain training for OFDM system is that the information symbols are not contaminated by the training symbols as in the frequency-domain training case.
机译：无线信道的性质对无线通信系统的性能施加了根本限制。除了由多径传播引起的频率选择性特性之外，高速率无线和移动链路通常还表现出由用户的移动性引起的时间选择性特性，即所谓的双选择性无线信道。通道获取的质量对整个系统的性能有重大影响。因此，很好地促进了双选择通道的可靠估计。在接收机处使用均衡来补偿由多径传播产生的符号间干扰，并改善接收信号的质量。由于信道是随时间变化的，因此均衡器应该是自适应的；在本文中，第二章（在单输入单输出模型下）和第三章（在多输入多输出模型下）考虑了双选信道的信道估计和均衡。 ，其中时变信道被基本扩展模型（BEM）很好地描述了。我们的重点是用于信道估计的时分复用训练，其中定期插入训练符号并在其传输过程中使用所有发射功率;通过BEM建模的双选信道的线性均衡和决策反馈均衡（DFE）在本章中介绍4.除了使用CE-BEM对通道本身进行建模之外，对于使用均衡器的复指数（CE-）BEM设计时变串行有限脉冲响应（FIR）线性和DFE均衡器也引起了很多兴趣。在本文中，我们表明，线性均衡器的卡尔曼滤波器公式和基于CE-BEM信道模型的FIR DFE的替代公式可以以较低的计算成本产生相同或改进的BER，而不会产生固有的近似误差。 CE-BEM均衡器建模。在第5章中，提出了一种自适应信道估计方案，该方法利用了过采样的复指数基础扩展模型（CE-BEM），用于双选通道，其中我们通过多模型方法跟踪BEM系数。在这篇论文中。我们建议使用多模型框架，其中使用多个候选多普勒扩展值覆盖从零到上限的范围，这将导致多个CE-BEM信道模型，每个模型对应于一个假定的多普勒扩展值。随后，基于对应于多个估计信道的多个状态空间模型，使用众所周知的交互多模型（IMM）算法进行符号检测。正交频分复用（OFDM）是一种数字多载波调制方案，具有由于其高频谱效率和简单的均衡，已发展成为一种流行的宽带无线通信方案。在第6章的双选信道下，我们将第2章介绍的基于最佳时分复用训练的信道估计扩展到OFDM系统。与传统的频域训练设计相比，OFDM系统的时域训练的主要优势在于：信息符号不会像频域训练情况那样被训练符号污染。

著录项

  • 作者

    Song, Liying.;

  • 作者单位

    Auburn University.;

  • 授予单位 Auburn University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 166 p.
  • 总页数 166
  • 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

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