信号的二阶周期平稳性在无线移动通信中的应用
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摘要
这篇论文研究的内容是基于信号的周期平稳特性的盲信号处理方法在无线移动通信中的应用。利用信号的周期平稳特性解决了无线通信中的盲信噪比估计和OFDM系统中的盲同步参数估计问题，并分析了基于周期平稳的方法在时变信道下的应用。
论文首先介绍了盲信号处理方法在无线移动通信中的应用，并比较了几种不同的盲信号处理方法，说明了基于信号的周期平稳特性的方法在盲信号处理领域的重要地位。随后详细介绍了周期平稳信号的定义和基于周期平稳的方法的优势：例如不需要发送端发送已知信号，提高信息传输速率；提供丰富的分析域；对平稳噪声具有免疫性等。进一步的，介绍了这种方法在无线通信中的应用：比如信号的检测与辨识、信号到达方向估计、信道同步参数估计以及信道的辨识与均衡等。
信噪比是信道质量的衡量标准，又是许多移动通信算法的重要参数，因此信噪比估计的研究一直是无线通信中的一个重要研究课题。论文提出了一种新的利用信号的周期平稳特性进行盲信噪比估计的方法。这种方法首先选取周期频率不为零的信号二阶周期自相关进行信号功率估计，然后根据信号二阶矩与信号和噪声功率的关系，估计出噪声功率，最后得到信噪比的估计。通过理论分析和性能仿真，证明了这种方法广泛适用于MPSK、MQAM等各种调制方式；实信道和复信道；单径信道和多径信道。在较大的信噪比范围内，其估计性能优于M2M4、SVR等其它盲信噪比估计方法，归一化均方误差更加接近于克拉美—罗下界。而且，这种信噪比估计方法的性能几乎不受调制方式的影响，具有较强的鲁棒性。
作为一种多载波系统，OFDM系统比一般的单载波系统对同步的要求更为严格。论文分析了各种OFDM系统下，基于信号周期平稳特性的盲同步参数估计方法。首先，针对每个用户分配单载波的OFDM系统，在以往文献提出的同步参数估计方法的基础上进行了改进，并且针对具有共轭周期平稳特性的信号，提出了一种基于共轭周期平稳特性的频偏修正方法。然后，针对每个用户分配多个子载波的OFDM系统，提出了一种广泛适用于一般子载波分配策略的盲同步参数估计方法。这种盲估计方法的频偏估计依赖于时延估计。进一步的，针对分段子载波分配、间隔子载波分配和混合子载波分配等3种目前被重点研究的子载波分配策略，提出了一种频偏估计与时延估计独立的盲同步参数估计方法。相对于依赖时延估计的频偏估计，这种独立的频偏估计具有更高的精度。最后，分析了所有子载波同步发送数据，即下行OFDM系统下的盲同步参数估计。
针对基于信号的周期平稳的方法在时变信道中的实际应用，论文进行了较为详细的分析。首先讨论了时变信道下估计周期统计量的计算复杂度，对传统方法，实时更新方法和基于快速傅立叶变换的实时更新方法这三种方法的计算量进行了比较。然后对时变信道进行了简化，提出了幅度和相位线性变化的模型。在这种模型下，证明了接收信号的周期平稳性，并推导了周期统计量的估计方法。进行了三种不同仿真环境下的仿真，证明了估计的准确性。对时变信道进行分析，证明了信道相干时间内周期个数与周期统计量估计精度的关系，给出了计算用于估计周期统计量的最佳周期数的经验公式。有了经验公式，在真实环境中，就可以根据信道的变化自适应地调整用于估计周期统计量的周期数，提高估计精度。
The dissertation focuses on the blind signal processing in wireless mobile communications based on the cyclostationarity of signals. In particular, blind estimation of signal-to-noise ratio and synchronization parameters of OFDM systems based on cyclostationarity and their application in time-varing channel are thoroughly investigated in this dissertation.
SNR is an important parameter in wireless communication, not only as the indicator of channel quality but also as the necessary input information for implementation of some algorithms. A blind SNR estimation based on the cyclostationarity of received signals is proposed in this dissertation. Firstly, the second-order cyclic autocorrelations of received signals on the non-zero cyclic frequencies are used to estimate the power of signal. Then, noise power is estimated according to the relationship between the 2nd-order moment of the received signal and the power of signal and noise. Then estimated SNR can be calculated easily. This estimation can be applied in MPSK or MQAM modulation, real or complex channel, one-path channel or multipath channel, and performs better than other classic blind SNR estimations, such as M2M4 and SVR estimation in a wide SNR region. Also, its normalized MSE is closer to a Cramer-Rao lower bound.
As a multicarrier system, OFDM is far more sensitive to synchronization error than the other single carrier systems. So synchronization has been one of the major research topics in OFDM system. Firstly, the OFDM system is discussed in which one user is allocated one subcarrier. The dissertation introduces an improved blind synchronization parameters estimation based on Bolcskei's estimation. Also for conjugate cyclostationary signal, a modified frequency offset estimation exploiting the second-order conjugate cyclic autocorrelation is proposed. Then, the OFDM system in which one user is allocated more than one subcarrier is discussed. For the general subcarrier allocation schemes, the synchronization parameters estimation is proposed. In this estimation, the estimation of frequency offset is relying on the estimation of time delay, which would degrade the performance. Then aiming at the three significant subcarrier allocation schemes, including block allocation, interleaved allocation and hybrid allocation, a new frequency offset estimation independent of the time delay estimation is proposed. This estimation of frequency offset has higher resolution. At last, the OFDM system in which all subcarriers bear data synchronously is investigated.
The dissertation discusses in detail the application of signal processing based on the cyclostationarity of signals to time-varying channel. Firstly, computational complexity of estimation of cyclic statistics is investigated. The computational complexities of three methods, including conventional estimation, real time updated estimation and real time updated estimation based on FFT, are compared. Then, time-varying channel is approximated and simplified to the model in which amplitude and phase are both linearly changed. In this simplified model, the cyclostationarity of received signal can be proved. Also the estimation of the cyclic statistics of received signal is introduced, and is proved in three different simulation scenarios. Then, the relation between cycle number in the coherence time and the veracity of the cyclic statistics estimation is showed, and the experiential formula to select cycle number is presented. According
论文首先介绍了盲信号处理方法在无线移动通信中的应用，并比较了几种不同的盲信号处理方法，说明了基于信号的周期平稳特性的方法在盲信号处理领域的重要地位。随后详细介绍了周期平稳信号的定义和基于周期平稳的方法的优势：例如不需要发送端发送已知信号，提高信息传输速率；提供丰富的分析域；对平稳噪声具有免疫性等。进一步的，介绍了这种方法在无线通信中的应用：比如信号的检测与辨识、信号到达方向估计、信道同步参数估计以及信道的辨识与均衡等。
信噪比是信道质量的衡量标准，又是许多移动通信算法的重要参数，因此信噪比估计的研究一直是无线通信中的一个重要研究课题。论文提出了一种新的利用信号的周期平稳特性进行盲信噪比估计的方法。这种方法首先选取周期频率不为零的信号二阶周期自相关进行信号功率估计，然后根据信号二阶矩与信号和噪声功率的关系，估计出噪声功率，最后得到信噪比的估计。通过理论分析和性能仿真，证明了这种方法广泛适用于MPSK、MQAM等各种调制方式；实信道和复信道；单径信道和多径信道。在较大的信噪比范围内，其估计性能优于M2M4、SVR等其它盲信噪比估计方法，归一化均方误差更加接近于克拉美—罗下界。而且，这种信噪比估计方法的性能几乎不受调制方式的影响，具有较强的鲁棒性。
作为一种多载波系统，OFDM系统比一般的单载波系统对同步的要求更为严格。论文分析了各种OFDM系统下，基于信号周期平稳特性的盲同步参数估计方法。首先，针对每个用户分配单载波的OFDM系统，在以往文献提出的同步参数估计方法的基础上进行了改进，并且针对具有共轭周期平稳特性的信号，提出了一种基于共轭周期平稳特性的频偏修正方法。然后，针对每个用户分配多个子载波的OFDM系统，提出了一种广泛适用于一般子载波分配策略的盲同步参数估计方法。这种盲估计方法的频偏估计依赖于时延估计。进一步的，针对分段子载波分配、间隔子载波分配和混合子载波分配等3种目前被重点研究的子载波分配策略，提出了一种频偏估计与时延估计独立的盲同步参数估计方法。相对于依赖时延估计的频偏估计，这种独立的频偏估计具有更高的精度。最后，分析了所有子载波同步发送数据，即下行OFDM系统下的盲同步参数估计。
针对基于信号的周期平稳的方法在时变信道中的实际应用，论文进行了较为详细的分析。首先讨论了时变信道下估计周期统计量的计算复杂度，对传统方法，实时更新方法和基于快速傅立叶变换的实时更新方法这三种方法的计算量进行了比较。然后对时变信道进行了简化，提出了幅度和相位线性变化的模型。在这种模型下，证明了接收信号的周期平稳性，并推导了周期统计量的估计方法。进行了三种不同仿真环境下的仿真，证明了估计的准确性。对时变信道进行分析，证明了信道相干时间内周期个数与周期统计量估计精度的关系，给出了计算用于估计周期统计量的最佳周期数的经验公式。有了经验公式，在真实环境中，就可以根据信道的变化自适应地调整用于估计周期统计量的周期数，提高估计精度。
The dissertation focuses on the blind signal processing in wireless mobile communications based on the cyclostationarity of signals. In particular, blind estimation of signal-to-noise ratio and synchronization parameters of OFDM systems based on cyclostationarity and their application in time-varing channel are thoroughly investigated in this dissertation.
SNR is an important parameter in wireless communication, not only as the indicator of channel quality but also as the necessary input information for implementation of some algorithms. A blind SNR estimation based on the cyclostationarity of received signals is proposed in this dissertation. Firstly, the second-order cyclic autocorrelations of received signals on the non-zero cyclic frequencies are used to estimate the power of signal. Then, noise power is estimated according to the relationship between the 2nd-order moment of the received signal and the power of signal and noise. Then estimated SNR can be calculated easily. This estimation can be applied in MPSK or MQAM modulation, real or complex channel, one-path channel or multipath channel, and performs better than other classic blind SNR estimations, such as M2M4 and SVR estimation in a wide SNR region. Also, its normalized MSE is closer to a Cramer-Rao lower bound.
As a multicarrier system, OFDM is far more sensitive to synchronization error than the other single carrier systems. So synchronization has been one of the major research topics in OFDM system. Firstly, the OFDM system is discussed in which one user is allocated one subcarrier. The dissertation introduces an improved blind synchronization parameters estimation based on Bolcskei's estimation. Also for conjugate cyclostationary signal, a modified frequency offset estimation exploiting the second-order conjugate cyclic autocorrelation is proposed. Then, the OFDM system in which one user is allocated more than one subcarrier is discussed. For the general subcarrier allocation schemes, the synchronization parameters estimation is proposed. In this estimation, the estimation of frequency offset is relying on the estimation of time delay, which would degrade the performance. Then aiming at the three significant subcarrier allocation schemes, including block allocation, interleaved allocation and hybrid allocation, a new frequency offset estimation independent of the time delay estimation is proposed. This estimation of frequency offset has higher resolution. At last, the OFDM system in which all subcarriers bear data synchronously is investigated.
The dissertation discusses in detail the application of signal processing based on the cyclostationarity of signals to time-varying channel. Firstly, computational complexity of estimation of cyclic statistics is investigated. The computational complexities of three methods, including conventional estimation, real time updated estimation and real time updated estimation based on FFT, are compared. Then, time-varying channel is approximated and simplified to the model in which amplitude and phase are both linearly changed. In this simplified model, the cyclostationarity of received signal can be proved. Also the estimation of the cyclic statistics of received signal is introduced, and is proved in three different simulation scenarios. Then, the relation between cycle number in the coherence time and the veracity of the cyclic statistics estimation is showed, and the experiential formula to select cycle number is presented. According
引文
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