本文为美国路易斯安那州立大学（作者：Zhongshan Wu）的博士论文，共141页。

在这个新的信息时代，高数据速率和强大的可靠性是无线通信系统的特点，并且正成为商业网络成功部署的主导因素。MIMO-OFDM（多输入多输出正交频分复用）是一种新型的无线宽带技术，以其高速传输能力和抗多径衰落等能力而受到广泛欢迎。MIMO-OFDM系统面临的一个主要挑战是如何准确、快速地获取信道状态信息，以实现对信息符号的相干检测和信道同步。

本文首先对MIMO-OFDM系统的信道估计问题进行了研究，提出了一种基于导频的信道估计算法。采用矩阵表示法建立了一种复杂的等效基带MIMO-OFDM信号模型，通过在一个正交频分复用符号中选择N个子载波的L等间距等功率导频，得到了原始信号模型的下采样表示。此外，该信号模型被转换成线性形式的最小二乘估计算法。在此基础上，提出了一种简单的导频设计方法，即采用酉矩阵的形式，其行代表频域中不同的导频集，列代表空间域中不同的发射天线。

本文通过对导频设计的分析和综合，证明了导频矩阵本质上是一个酉矩阵，从而可以降低MIMO系统的计算复杂度，并证明了该算法是一种在实现最小均方误差意义上的针对固定导频功率的最优信道估计量。第二部分主要研究了基于MIMO-OFDM技术的WiMax网络中的无线定位问题。根据TDOA（到达时间差）、AOA（到达角）的测量数据或两者的结合，建立了LS型解的拟线性形式。假设观测数据被方差很小的零均值AWGN（加性高斯白噪声）污染，在此假设下，证明了拟线性形式的噪声项具有近似正态分布。因此，ML（最大似然）估计和LS型解是等效的。但由于其计算复杂，且最优解可能不存在，ML估计方法在这里是不可行的。我们提出的方法能够非常准确地估计移动站MS的位置，计算量要少得多。然而，在不引入另一个独立约束的情况下，MS（移动站）位置估计的最终结果不能直接从LS类型的解中获得。为了解决这一问题，研究了拉格朗日乘子法求解约束LS型优化问题的最优解。

In this new information age, high data rate and strong reliabilityfeatures our wireless communication systems and is becoming the dominant factorfor a successful deployment of commercial networks. MIMO-OFDM (multiple inputmultiple outputorthogonal frequency division multiplexing), a new wirelessbroadband technology, has gained great popularity for its capability of highrate transmission and its robustness against multi-path fading and otherchannel impairments. A major challenge to MIMO-OFDM systems is how to obtainthe channel state information accurately and promptly for coherent detection ofinformation symbols and channel synchronization. In the flrst part, thisdissertation formulates the channel estimation problem for MIMO-OFDM systemsand proposes a pilot-tone based estimation algorithm. A complex equivalentbaseband MIMO-OFDM signal model is presented by matrix representation. Bychoosing L equally-spaced and equally-powered pilottones from N sub-carriers in one OFDM symbol, adown-sampled version of the original signal model is obtained. Furthermore,this signal model is transformed into a linear form solvable for the LS(least-square) estimation algorithm. Based on the resultant model, a simplepilot-tone design is proposed in the form of a unitary matrix, whose rows standfor different pilot-tone sets in the frequency domain and whose columnsrepresent distinct transmit antennas in the spatial domain. From the analysisand synthesis of the pilot-tone design in this dissertation, our estimation algorithmcan reduce the computational complexity inherited in MIMO systems by the factthat the pilot-tone matrix is essentially a unitary matrix, and is proven an optimalchannel estimator in the sense of achieving the minimum MSE (mean squared error)of channel estimation for a flxed power of pilot tones. In the second part,this dissertation addresses the wireless location problem in WiMax (worldwideinteroperability for microwave access) networks, which is mainly based on theMIMO-OFDM technology. From the measurement data of TDOA (time difierence ofarrival), AOA (angle of arrival) or a combination of those two, a quasilinearform is formulated for an LS-type solution. It is assumed that the observation datais corrupted by a zero-mean AWGN (additive white Gaussian noise) with a very smallvariance. Under this assumption, the noise term in the quasi-liner form isproved to hold a normal distribution approximately. Hence the ML(maximum-likelihood) estimation and the LS-type solution are equivalent. Butthe ML estimation technique is not feasible here due to its computationalcomplexity and the possible nonexistence of the optimal solution. Our proposedmethod is capable of estimating the MS location very accurately with a muchless amount of computations. A final result of the MS (mobile station) locationestimation, however, cannot be obtained directly from the LS-type solutionwithout bringing in another independent constraint. To solve this problem, theLagrange multiplier is explored to flnd the optimal solution to the constrainedLS-type optimization problem.

1 引言

2 MIMO-OFM信道估计

3 基于OFDM系统的无线定位

4 结论

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