摘要
未来通信系统在实现数据可靠传输的基础上还要满足高速率传输的要求。正交频分复用(OFDM)系统能够有效的对抗多径衰落并具有较高的频谱资源利用率。而多发射多接收天线(MIMO)技术能够大幅度提高系统的吞吐量。因此MIMO与OFDM结合将成为未来移动通信的发展趋势。
同步问题是通信信号处理中首先需要解决的问题，直接关系到后续基带信号处理算法的性能。OFDM系统对同步误差非常敏感，很小的载波频偏都将导致系统性能的急剧下降。因此准确的符号定时和精确的载波频偏估计是OFDM系统正常工作的前提。引入MIMO技术后，同步误差还会引起严重的天线间干扰。因此，MIMO-OFDM系统中的同步问题更为关键。
论文主要就频率选择性衰落信道下MIMO-OFDM系统中的同步理论和算法进行了深入的研究，并将所提出的新的算法与当前国际上的一些经典算法进行了比较。论文的主要研究成果如下：
一、对定时偏移和载波频偏对OFDM系统性能的影响进行了全面的数学建模和理论分析总结，并通过仿真对分析结果进行了验证。理论分析结果为后续章节的同步算法设计提供了理论基础。
二、研究时域相关峰值检测的同步算法。指出在多径衰落信道中，相关窗的长度对时域相关峰值检测算法性能有直接的影响。研究表明，当相关窗长度大于信道最大多径迟延时，采用检测相关值斜率最大值的方法理论上能够有效地估计出接收端第一径的位置。提出了两种基于时域相关峰值检测的同步估计改进算法：1)采用一个OFDM符号做为训练序列，在接收端进行差分相关以解决时间度量函数中出现的平台效应。所提出的算法定时度量函数具有陡峭的波形，大大提高的符号定时估计性能。2)提出了一种采用接收信号与发送导频信号的副本相关的同步算法。在接收端，以多径区域能量和噪声区域能量之比作为符号定时的判决函数，从而使所形成的峰值更加明显。在多天线情况下，随着收发天线数的增加，信道的多径数目将线性增加，从而获得更多的分集增益，同步性能随之变好。
三、研究基于空子载波的载波频偏最大似然比估计算法，指出采用重复训练序列相关的载波频偏估计算法等价于采用等间隔空子载波的载波频偏最大似然比估计算法。进一步分析了在频率选择性衰落信道下，空载波和信道零点的数目与位置对基于空子载波的载波频偏估计算法可辨识性的影响。理论分析证明：采用等间隔放置的空子载波或数据子载波进行载波频偏估计，得到的载波频偏估计结果独立于信道零响应。
四、深入研究了基于子空间的盲估计算法。提出了一种基于多重信号分类(MUSIC)原理的上行交织频分多址(IFDMA)系统载波频偏估计算法。所提出的算法通过设计一种特殊的频率估计因子，解决了传统MUSIC算法中对参数空间进行多维搜索的问题，使得上行IFDMA系统多用户载波频偏估计转换成一个一维估计问题，算法复杂度低。
五、研究了分布式MIMO-OFDM系统中的同步问题，提出了一种改进的分布式MIMO-OFDM系统定时偏移和载波频偏估计算法。该算法利用Gold码良好的相关特性降低天线间干扰，有效地估计各发射天线的迟延和载波频偏。相比其他的分布式MIMO-OFDM同步估计方法，所提出了算法具有更高的定时估计精度。
本论文研究的目的是为宽带移动通信系统的同步问题提供新的理论和解决方案，应用环境为频率选择性衰落信道。论文所提出的新的算法相对于传统算法具有更高的效率，适合实际当中的应用。
Both of high quality and high data rate will be required in the future wireless communication systems. Orthogonal Frequency Division Multiplexing (OFDM) is robust to frequency selective fading and can achieve high spectral efficiency. Meanwhile, Multi-Input Multi-Output (MIMO) technique can provide high throughput. The combination of OFDM and MIMO has been regarded as a promising solution for future wireless communication systems.
Synchronization is the primary procedure for signal processing, which influences the performance of following baseband signal processing. OFDM system is sensitive to synchronization errors. Very small carrier frequency offset (CFO) may degrade system performance severely. Correct symbol timing and precise CFO estimation are necessary for OFDM systems. When introducing MIMO technique into OFDM system, synchronization error may lead to severe inter-antenna interference. Hence the synchronization is much more important in MIMO-OFDM systems.
In this thesis, synchronization theories and algorithms for MIMO-OFDM systems are deeply analyzed and researched over frequency selective channels, and several new synchronization algorithms are proposed and compared with key conventional algorithms. The main contributions of this thesis can be described as follows:
Firstly, the influences of symbol timing error and CFO on OFDM system performance are mathematically modeled and analyzed. The results are confirmed by computer simulations, which also provide theoretical foundations for synchronization algorithm designs in the following chapters.
Secondly, synchronization algorithms based on the time domain correlation peak are analyzed. It is shown that over multi-path channels, the correlation length affects the performance of synchronization algorithms based on the time domain correlation peak significantly. The first arriving path can be effectively estimated by detecting the maximum value of the gradient of the correlation value, when the correlation length exceeds the largest multipath delay. Two improved synchronization algorithms based on the time domain correlation peak are proposed. The first one uses only one OFDM symbol as the training sequence and performs differential correlation at the receiver to eliminate the peak plateau of the timing metric. This algorithm can achieve considerable symbol timing accuracy with a steep roll-off timing metric trajectory. The second one is based on the correlation between the received signals and the copy of pilots at the receiver. Symbol timing is estimated depending on the ratio of multi-path power to noise power, which makes the timing metric peak more obvious. With multiple antennas, the number of multipaths increases linearly as the number of antennas increasing, which brings more available multipath diversity gains and can improve algorithm performance.
Thirdly, the maximum-likelihood CFO estimation algorithms based on null-subcarrier are investigated, and it is shown that the maximum-likelihood CFO estimation algorithm based on equispaced null-subcarriers is equivalent to the CFO estimation algorithm utilizing the correlation of repeated training sequences. The further analysis indicates the necessary conditions of the channel zero numbers and locations, when the CFO estimation algorithm is identifiable over frequency-selective fading channels. Theoretical analysis shows that with equispaced null-subcarriers or data subcarriers, the CFO estimation are independent to channel zero locations.
Fourthly, subspace-based blind synchronization algorithms are investigated, and an improved MUSIC (Multiple Signal Classification) algorithm is proposed for the uplink CFO estimation in IFDMA systems. Unlike conventional MUSIC algorithms which require multi-dimensional search over the parameter space, the proposed algorithm utilizes a special designed CFO estimation factor and makes the multi-user CFO estimations for the uplink in IFDMA systems be a one-dimensional estimation, and is much more efficient compared with conventional algorithms.
Lastly, the synchronization problem in distributed MIMO-OFDM systems is investigated, and an improved synchronization algorithm is proposed. The proposed algorithm utilizes the good cross-correlation properties of Gold sequence to reduce the inter-antenna interference, and makes the estimations of the delay and CFO for different antennas more efficient. Compared with conventional synchronization algorithms for distributed MIMO-OFDM systems, the proposed algorithm offers more accurate timing estimation.
The main target of the thesis is to provide new theories and algorithms for the synchronization problem for broadband wireless communication systems. The proposed algorithms have high efficiency and are more applicable compared with conventional algorithms.
引文
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