下一代移动无线通信系统的目标是实现无所不在的、高质量的、高速率的移动多媒体传输.htm

研究和开发移动道中数字传输技术的第一步工作就是认识移动信道本身的特性

<p class=MsoNormal style='text-indent:1.0cm;line-height:150%'><span
style='font-family:宋体;mso-ascii-font-family:"Times New Roman";mso-hansi-font-family:
"Times New Roman";letter-spacing:.5pt'>论文第五章提出一种适用于稀疏多径衰落信道改进的</span><span
lang=EN-US style='letter-spacing:.5pt'>OFDM</span><span style='font-family:
宋体;mso-ascii-font-family:"Times New Roman";mso-hansi-font-family:"Times New Roman";
letter-spacing:.5pt'>系统信道估计算法。在无线通信中，我们通常是用多径传播来描述信道的。例如，在一个宏区中，当基站天线位置较高时，这时的多径信道将主要由</span><span
lang=EN-US style='letter-spacing:.5pt'>2</span><span style='font-family:宋体;
mso-ascii-font-family:"Times New Roman";mso-hansi-font-family:"Times New Roman";
letter-spacing:.5pt'>到</span><span lang=EN-US style='letter-spacing:.5pt'>6</span><span
style='font-family:宋体;mso-ascii-font-family:"Times New Roman";mso-hansi-font-family:
"Times New Roman";letter-spacing:.5pt'>条反射路径构成。我们可以使用参数化的信道模型来描述这种信道。在该模型中，各路径只包含时延和复增益系数两个参数。这种参数化的方法可使信道估计问题的维数明显减少。而我们知道，当训练数据数量相同时，减小所要估计问题的维数便可提高估计的准确性。特别是本章显示，对于稀疏多径衰落信道，当基于参数化信道模型来构造信道相关矩阵时，可以明显减少信道相关矩阵的信号子空间维数。对于</span><span
lang=EN-US style='letter-spacing:.5pt'>MMSE</span><span style='font-family:
宋体;mso-ascii-font-family:"Times New Roman";mso-hansi-font-family:"Times New Roman";
letter-spacing:.5pt'>信道估计器，减小信号子空间的维数可直接提高估计器的性能。另外在移动环境中，路径时延变化是很慢的，而路径增益系数的幅度和相位变化都非常快，一般认为它们是按</span><span
lang=EN-US style='letter-spacing:.5pt'>Rayleigh</span><span style='font-family:
宋体;mso-ascii-font-family:"Times New Roman";mso-hansi-font-family:"Times New Roman";
letter-spacing:.5pt'>衰落的。这一特性可进一步简化信道估计器的设计。</span><span style='font-family:
宋体;mso-hansi-font-family:"Times New Roman";letter-spacing:.5pt'>所以，我们提出使用一种利用导频并基于参数化信道模型的信道估计方法。基于该模型的信道估计器就是要估计包括路径数、各路径的时延及复数增益系数在内的这些信道参数。首先，我们采用最小描述长度<span
lang=EN-US>(Minimum Description Length, MDL)准则来检测信道中的路径数。然后，利用估计信号参数的旋转不变法(Estimation
of Signal Parameters by Rotational Invariance Techniques，ESPRIT)来对各路径时延进行初始估计。因为路径时延的慢变化，所以我们提出使用路径间干扰抵消(Inter-Path
Interference Cancellation, IPIC)的延迟锁定环路(DLL)来跟踪信道路径时延。最后，利用信道的路径时延信息，我们推导出一个对信道频域响应的MMSE估计器。仿真结果显示MDL准则和ESPRIT方法可自适应地对信道参数进行初始估计。而IPIC
DLL也被证明是一种估计和跟踪路径时延的有效方法。分析和仿真还表明，这里提出的基于参数化信道模型的信道估计算法相对于基于非参数信道模型的方法，可明显改善OFDM传输系统在稀疏多径信道下的性能。<o:p></o:p></span></span></p>

<p class=MsoPlainText style='text-indent:1.0cm;line-height:150%'><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-hansi-font-family:
"Courier New";letter-spacing:.5pt;mso-fareast-language:ZH-CN'>在论文第六章中，我们针对非参数化信道模型，提出并分析了低复杂度的基于加窗<span
lang=EN-US>DFT的MMSE信道估计算法。在非参数化信道模型方法中，最小均方误差(Minimum Mean Square Error, MMSE)准则经常被用来设计OFDM系统的信道估计器，但是理想的MMSE估计器的复杂度一般都很高，而利用离散傅立叶变换(Discrete
Fourier Transform, DFT)来进行OFDM信道估计可大大降低估计器的复杂度。基于DFT的方法既可用到内插的情形中，又可用到非内插的情形中。用于内插时，DFT是一种简单的，并且计算上十分高效的内插算法。但是完全精确的内插需要信道中各路径时延必须按OFDM采样间隔来分布。实际中，信道的多径时延一般不是按OFDM采样间隔分布的，甚至信道的功率时延分布根本不是离散的，而是连续的。这种情况下，如果在进行基于DFT的内插之前，我们不用一个窗函数对观测到的信道频率响应向量进行加窗处理，则内插后，由能量泄漏而引起的混叠现象将导致信道估计的错误平底(Error
floor)。另外，由于导频信号通常对信道频率响应进行过采样，所以在接收端得到的等效信道冲击响应向量中，信道能量主要集中在一个较小的范围内，而噪声能量则分布在整个向量范围内。所以，我们可以在时域对等效信道冲击响应向量使用一个加权函数来减小信道噪声的影响。对于非内插情形，基于DFT的方法也是利用了DFT实现的低复杂度和信道能量在等效信道冲击响应向量中分布相对集中的特性。</span></span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>在本章中，我们针对内插和非内插不同的情形，提出一种低复杂度的，基于加窗</span><span
lang=EN-US style='font-size:10.5pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:
宋体;letter-spacing:.5pt;mso-fareast-language:ZH-CN'>DFT</span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>的</span><span lang=EN-US style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;mso-fareast-font-family:宋体;letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>MMSE</span><span style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:"Courier New";
mso-hansi-font-family:"Courier New";letter-spacing:.5pt;mso-fareast-language:
ZH-CN'>信道估计算法。首先，在频域，我们使用一个推广的</span><span lang=EN-US style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;mso-fareast-font-family:宋体;letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>Hanning</span><span style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:"Courier New";
mso-hansi-font-family:"Courier New";letter-spacing:.5pt;mso-fareast-language:
ZH-CN'>窗函数，对由导频得到的信道频率响应观测向量进行加窗操作，来减小能量泄漏。另外，在时域，我们还对得到的等效信道冲击响应向量使用一个加权函数来减小信道噪声的影响。对于一个给定的频域窗函数，我们是通过使信道估计均方误差</span><span
lang=EN-US style='font-size:10.5pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:
宋体;letter-spacing:.5pt;mso-fareast-language:ZH-CN'>(Mean Square Error, MSE)</span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>最小，来选取时域加权函数的。另外，由于信道估计的</span><span lang=EN-US
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:宋体;
letter-spacing:.5pt;mso-fareast-language:ZH-CN'>MSE</span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>还依赖于频域窗函数的形状，我们将通过搜索来找到使信道估计</span><span
lang=EN-US style='font-size:10.5pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:
宋体;letter-spacing:.5pt;mso-fareast-language:ZH-CN'>MSE</span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>达到最小的最佳窗函数形状。</span><span style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;font-family:宋体;mso-hansi-font-family:"Courier New";
letter-spacing:.5pt;mso-fareast-language:ZH-CN'>分析和仿真表明，采用频域加窗可消除内插情形中信道估计的错误平底，并可在非内插情形中带来更好的噪声滤除性能。而在时域中的<span
lang=EN-US>MMSE加权是一种抑制信道噪声和改进信道估计性能的很有效的方法。而且，分析和仿真结果还显示，建议方法的性能接近于最优的MMSE信道估计器的性能，但复杂度却减小很多，</span></span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>这是因为在建议的方法中，我们使用了快速算法</span><span lang=EN-US
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:宋体;
letter-spacing:.5pt;mso-fareast-language:ZH-CN'>IFFT/FFT</span><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:
"Courier New";mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>来实现</span><span lang=EN-US style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;mso-fareast-font-family:宋体;letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>IDFT/DFT</span><span style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:"Courier New";
mso-hansi-font-family:"Courier New";letter-spacing:.5pt;mso-fareast-language:
ZH-CN'>，并且在频域的加窗过程和在时域的</span><span lang=EN-US style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;mso-fareast-font-family:宋体;letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>MMSE</span><span style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:"Courier New";
mso-hansi-font-family:"Courier New";letter-spacing:.5pt;mso-fareast-language:
ZH-CN'>加权过程，都是简单的</span><span style='font-size:10.5pt;mso-bidi-font-size:10.0pt;
font-family:宋体;mso-hansi-font-family:"Courier New";letter-spacing:.5pt;
mso-fareast-language:ZH-CN'>单个元素与单个元素相乘的操作</span><span style='font-size:10.5pt;
mso-bidi-font-size:10.0pt;font-family:宋体;mso-ascii-font-family:"Courier New";
mso-hansi-font-family:"Courier New";letter-spacing:.5pt;mso-fareast-language:
ZH-CN'>。</span><span lang=EN-US style='font-size:10.5pt;mso-bidi-font-size:
10.0pt;mso-fareast-font-family:宋体;letter-spacing:.5pt;mso-fareast-language:
ZH-CN'><o:p></o:p></span></p>

<p class=MsoPlainText style='text-indent:1.0cm;line-height:150%'><span
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-hansi-font-family:
"Courier New";letter-spacing:.5pt;mso-fareast-language:ZH-CN'>第七章是论文的总结和结论，并对进一步工作提出了建议。<span
lang=EN-US><o:p></o:p></span></span></p>

<p class=MsoPlainText style='line-height:150%'><span lang=EN-US
style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:宋体;mso-hansi-font-family:
"Courier New";letter-spacing:.5pt;mso-fareast-language:ZH-CN'><![if !supportEmptyParas]>&nbsp;<![endif]><o:p></o:p></span></p>

<p class=MsoPlainText align=center style='text-align:center;line-height:150%'><b><span
lang=EN-US style='font-size:14.0pt;mso-bidi-font-size:10.0pt;font-family:"Times New Roman"'>Timing
Recovery &amp;Channel Estimation Algorithms for<o:p></o:p></span></b></p>

<p class=MsoPlainText align=center style='text-align:center;line-height:150%'><b><span
lang=EN-US style='font-size:14.0pt;mso-bidi-font-size:10.0pt;font-family:"Times New Roman"'>Wireless
Communication Systems Using OFDM<o:p></o:p></span></b></p>

<p class=MsoNormal align=center style='text-align:center'><span lang=EN-US
style='font-size:14.0pt;mso-bidi-font-size:10.0pt'>Abstract<o:p></o:p></span></p>

<p class=MsoNormal style='text-indent:34.5pt;mso-char-indent-count:3.0;
mso-char-indent-size:11.5pt'><span lang=EN-US style='letter-spacing:.5pt'>The
next-generation wireless personal communication systems are expected to provide
ubiquitous, high-quality, and high-rate mobile multimedia transmission.
However, to achieve this objective various technical challenges must be
overcome. For example, the deployment of broadband wireless access systems would
require a transmission technique which can mitigate the detrimental effects of
the inter-symbol interference (ISI) caused by the multipath fading channels. In
recent years, there has been a lot of interest in applying Orthogonal Frequency
Division Multiplexing (OFDM) in wireless systems because of its various
advantages in lessening the severe effects of ISI. However, the OFDM system is
vulnerable to synchronization errors and channel estimation errors. How to
effectively do the synchronization and do the channel estimation at the OFDM
receiver are the important issues, which need be addressed in OFDM systems.
Hence, the dissertation focuses on the timing recovery and channel estimation
algorithms design for OFDM receivers. <o:p></o:p></span></p>

<p class=MsoNormal style='text-indent:34.5pt;mso-char-indent-count:3.0;
mso-char-indent-size:11.5pt'><span lang=EN-US style='letter-spacing:.5pt'>Chapter
2 gives a brief introduction about the characteristics of the wireless
communication channels, and mainly discusses the inter-symbol interference
caused by the channel multipath delay spread.<o:p></o:p></span></p>

<p class=MsoPlainText style='text-align:justify;text-justify:inter-ideograph;
text-indent:34.5pt;mso-char-indent-count:3.0;mso-char-indent-size:11.5pt'><span
lang=EN-US style='font-size:10.5pt;mso-bidi-font-size:10.0pt;font-family:"Times New Roman";
mso-fareast-font-family:宋体;mso-bidi-font-family:"Courier New";letter-spacing:
.5pt;mso-fareast-language:ZH-CN'>In Chapter 3, we discuss the OFDM receiver
design issues. We first introduce the basic principles about OFDM transmission,
including the ideal signal model. Specifically, we use the block transmission
model to represent the OFDM system. After that, we consider several
unsynchronized factors impacts on the OFDM transmission and introduce a real
OFDM transmission model. We then divide the OFDM receiver as inner-receiver and
outer-receiver. Finally, we present an inner-receiver design of OFDM system.<o:p></o:p></span></p>

<p class=MsoBodyText style='text-align:justify;text-justify:inter-ideograph;
text-indent:31.5pt;mso-char-indent-count:3.0;mso-char-indent-size:10.5pt'><span
lang=EN-US>In Chapter 4, we</span><span lang=EN-US style='mso-fareast-font-family:
宋体;mso-fareast-language:ZH-CN'> </span><span lang=EN-US>propose a scheme for
performing timing recovery that includes symbol synchronization and sampling
clock synchronization in OFDM systems. In OFDM transmission systems, the
synchronization tasks include carrier frequency synchronization and timing
recovery that can be further divided into symbol synchronization and sampling
clock synchronization. The purpose of symbol synchronization is to find the
correct position of the fast Fourier transform (FFT) window. Symbol
synchronization may be done at the receiver with the aid of the dedicated
training symbols. The cyclic property of the guard interval preceding the OFDM
symbol can be also evaluated for symbol synchronization, thus reducing the need
for training symbols. In multipath fading channels, however, the guard interval
is corrupted by ISI and the periodic property is destroyed. Consequently,
correct symbol synchronization cannot be guaranteed in the case of ISI. If the