基于OFDM的LS信道估计仿真的研究

信道估计技术保证了信号传输的可靠性。基于导频的LS信道估计算法,通过导频子信道的响应得到整个信道的响应,能够很好地跟踪信道的变化,在复杂度不高的情况下取得较好的误差性能,具有很好的实用性。仿真结果表明采用LS信道估计后有效的降低了系统的误码率。     

多种内插算法的信道估计比较

分析了梳状导频插入方式下的信道估计算法的原理和性能,在频域上先对导频子载波进行最小平方估计(LS),并运用多种内插方法获取信道频率响应。运用MATLAB软件进行了仿真,比较分析了OFDM系统中各种信道估计算法的性能优劣。仿真结论对OFDM通信系统以及其它通信系统的信道估计有一定的研究价值。     

基于DFT的信道估计插值算法改进

在采用导频的正交频分复用(OFDM)系统中,常采用离散傅里叶变换(DFT)插值的方法来实现信道估计。针对DFT算法中虚子载波的缺失而导致冲激响应有频谱泄漏的现象,对DFT算法进行了两种改进,一是采用维纳滤波插入法重建虚子载波的信道信息,二是通过优化有效导频的LS信道估计来减小噪声的影响,并提高系统的性能。通过仿真证明,改进算法明显优于传统DFT算法。     

上行MIMO-OFDM系统中基于改进GAIC算法的稀疏信道估计

大量实验证据和物理论证表明,无线信道中的信号传输呈现系统的多径稀疏结构,并随着信号空间维度变大愈加明显,而现有大多数信道估计算法均未在复杂度与准确的稀疏信道估计之间实现平衡。根据大规模MIMO（multiple-input multiple-output）系统固有的稀疏特性,提出基于改进广义Akaike信息准则（GAIC）的具有低矩阵运算量的信道估计算法。该算法根据有效抽头处脉冲幅度值较大特点,利用代价函数获取有效抽头位置准确执行信道估计,最大程度地降低噪声干扰。仿真表明该算法具有良好的抗噪性能和抗多径干扰能力。     

MIMO OFDM系统中基于MDL准则的均方根时延扩展估计

研究了MIMO OFDM系统中最小描述长度(MDL)准则在均方根时延扩展估计中的应用. 分析了多径分量功率和多径分量的自相关矩阵之间的关系, 使MDL可有效地应用于RDS估计. 该估计器能以较低的计算复杂度给出RDS、噪声方差、信道功率和信噪比等多个实时信道参数的准确估计. 根据估计的多径分量功率, 利用MDL准则获得了当前信道环境下的路径数及它们各自时延的估计; 根据路径数得到了噪声方差和各径功率的估计, 从而得到当前信道的功率时延谱和均方根时延扩展的估计. 仿真结果表明该估计器可有效对抗信道中信噪比变化和频率选择性的影响.     

一种快衰落信道中OFDM系统的Kalman信道估计方法

针对频率选择性快衰落信道的多径干扰和较大的多普勒频率扩展,提出了一种基于导频的低维Kalman滤波算法用于正交频分复用(OFDM)系统信道估计.为了简化计算,采用一阶自回归(AR)过程对时变信道进行建模.利用复杂度大大降低的一维Kalman滤波算法进行单个子载波的并行信道估计,并采用基于导频的最小平方(LS)算法估计时变的信道衰减因子a.为了同时跟踪信道的频域相关性,采用了最小均方误差(MMSE)线性合并器对Kalman信道估计结果进行修正.在5.5 GHz频段上的仿真表明了这种基于导频的低维Kalman信道估计方法,降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,并且在一定程度上可以接近于理想信道估计的误码率性能.     

接收IQ不平衡OFDM系统的高性能信道估计和补偿方案(英文)

针对接收IQ不平衡的OFDM系统,设计了横跨2个OFDM符号的特殊训练结构.提出了一种高效的时域最小二乘(TD-LS)信道估计和一种低复杂度的频域高斯消元补偿算法来消除IQ失真.前者与传统的频域LS算法相比,信道估计噪声的影响降低了N/(L+1)倍,其中N为子载波总数,L+1为循环前缀长度;后者实现复杂度低,每个OFDM符号仅需要2N次复数乘法.仿真结果表明:由于充分挖掘了信道参数的时域特性,提出的TD-LS信道估计算法与传统的FD-LS算法相比获得了可观的信噪比增益;提出的低复杂度的GE补偿算法能够获得与基于LS的频域补偿方案几乎相同的误码性能.     

预估稀疏度的压缩感知超宽带信道估计算法研究与仿真实验

设计了信道估计算法实验的一个拓展内容——预估稀疏度的压缩感知超宽带信道估计算法研究与仿真实验,提出一种预估稀疏度的压缩感知超宽带信道估计算法。该算法引入稀疏度预估计,在自适应匹配之前快速估计出信号的稀疏度,避免自适应匹配时步长选择不合理对信道估计结果产生影响。在稀疏度预估计和匹配追踪两个阶段挑选原子时使用广义Dice系数准则来进行每一阶段的最优原子选择工作,并在匹配最优原子阶段引入正则化对已选原子进行二次筛选。     

回归系数LS估计的改进

论述了复共线性对LS估计的影响,复共线性存在时主成分估计比LS估计有较小均方误差.通过实例说明利用主成分估计对LS估计改进的方法与步骤.     

一种改进EM算法的联合信道估计与数据检测

最近的一些研究表明,在接收机利用可用的信道估计误差的统计时,可以显著提高检测性能.对此,提出了一种基于改进期望最大化（EM）算法的数据辅助信道估计,它通过在每次迭代中提供估计误差的统计信息,减少在各自的接收器信道估计误差的影响.仿真结果表明,与传统的EM及VBEM算法相比,在不需增加接收机复杂程度的情况下,改进的EM算法在估计精度上优于其对应的传统估计方法,有效降低了信道估计误差,其误码性能接近理想信道时的性能.     

稀疏长时延水声信道的压缩感知估计(英文)

提出一种基于压缩感知框架下的长时延水声信道估计算法.用传统的自适应算法如最小二乘(LS)算法处理典型的长时延水声信道的估计问题时,会导致其收敛速率下降,即跟踪能力有限,而使用时延多普勒函数则加大了计算量和复杂度.通过训练序列构建一个Toeplitz矩阵作为测量矩阵,将长时延信道估计问题转为压缩感知问题,并利用信道的稀疏结构特性进行稀疏估计.与传统的l1范数或基于指数形式的近似l0范数稀疏恢复策略不同,所提出的是一种新的似l0范数稀算法(简称AL0),该算法通过融合最陡梯度和迭代投影寻优进行求解.仿真与海试数据结果验证了所提算法的优越性.     

采用压缩感知的数字广播信道估计(英文)

为降低导频数目并提高频谱利用率,将最新提出的压缩感知技术应用于数字广播的信道估计.在欧洲电信标准协会DRM标准规定的6种信道模式中,对于确定了信道模式多径数目的情况,采用子空间跟踪算法估计各径的时延扩展和衰减,设定算法迭代终止条件为估计结果的稀疏度等于多径数目;对于多径数目未知的情况,采用正交匹配追踪算法估计信道参数,设定算法迭代终止条件为估计误差等于噪声方差.仿真结果表明,在相同的导频数目下,压缩感知算法优于传统的基于内插的最小二乘信道估计算法;在多径数目先验的情况下,子空间跟踪算法优于正交匹配追踪算法.     

Time-domain training sequences design for MIMO OFDM channel estimation

This paper describes a Least Squares （LS） channel estimation scheme for MIMO OFDM systems based on time-domain training sequence. We first compute the minimum mean square error （MSE） of the LS channel estimation, and then derive the optimal criteria of the training sequence with respect to the minimum MSE. It is shown that optimal time-domain training sequence should satisfy two criteria. First, the autocorrelation of the sequence transmitted from the same antenna is an impulse function in a region longer than the channel maximum delay. Second, the cross-correlation between sequences transmitted from different antennas is zero in this region. Simulation results show that the estimator using optimal time-domain training sequences has better performance than that using optimal frequency training sequence at low signal-to-noise ratio （SNR）. To reduce the training overhead, a suboptimal training sequence is also proposed. Comparing with optimal training sequence, it has low computation complexity and high transmission efficiency at the expense of little performance degradation.     

Liberal studies reform in Hong Kong secondary education: contrasting desirability with feasibility

In major curriculum reforms, there are inevitably gaps between design and implementation issues, taking the introduction of liberal studies (LS) into the senior secondary curriculum in Hong Kong as a classic example. The current paper illustrates how the implementation of LS as a compulsory core subject has impacted noticeably on Hong Kong senior secondary education. The LS curriculum setup is somewhat different from traditional subjects due to both the interdisciplinary nature of its design and the conceptions of learning, teaching, and assessment. The current study therefore attempts to portray the delicate balance that exists between the desirability ans feasibility of LS curriculum reform through interviewing members of the working group on the review of the academic structure for senior secondary education and interface with higher education. The study reports that, while LS policy makers considered both desirability and feasibility angles of the LS curriculum in their initial planning, the implementation of the LS public examination and teacher training to support the radical curriculum innovation fell short of expectations. Findings in the study clearly indicate that much more should be taken into account in respect of the dominance of an examination culture as well as teachers’ professional development when making major curriculum design changes.     

空时MIMO-OFDM 系统中基于扩展Kalman 滤波的信道估计

A space-time coded multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is considered as a solution to the future wideband wireless communication system.This paper proposes an extended Kalman filtering-based (EKF-based) channel estimation method for space-time coded MIMO-OFDM systems.The proposed method can exploit pilot symbols and an extended Kalman filter to estimate channel without any prior knowledge of channel statistics.In comparison with the least square (LS) and the least mean square (LMS) methods,the EKF-based approach has a better performance in theory.Computer simulations demonstrate the proposed method outperforms the LS and LMS methods.Therefore it can offer dramatic system performance improvement at a modest cost of computational complexity.