CDMA2000前向链路信道估计及跟踪算法的研究

对CDMA2000移动台接收机的信道估计单元的算法和实现进行了分析，探讨了如何根据衰落速率对相关长度进行自适应的调整，研究了如何在暂态情况下跟踪信道的多径分布的变化。为了实现上述算法简要描述了一种在非理想AFC情况下的多普勒频移测量方法，以上探讨使得信道估计单元能够在准确快速选出有效径的基础上对多径系数进行精确估计。     

CDMA2000前向链路信道估计算法研究

对CDMA2000移动台接收机的信道估计单元的算法和实现进行了分析,探讨了如何根据衰落速率对相关长度进行自适应的调整,以使信道估计单元能够对多径系数进行精确估计。     

基于迭代补偿的快速突发信道估计算法

 在突发信道中,针对接收信噪比大范围波动的情况下对于信道参数快速、稳定、准确获取的系统要求,提出一种基于迭代补偿的快速突发信道估计算法。该算法根据快速相关估计结果对其估计偏差进行补偿,实现信道参数的准确估计,并得到了补偿次数和估计性能的相关结论。理论分析和仿真表明,所提算法在低信噪比(小于 )情况下能准确的估计出信道参数,而且在高信噪比（大于 ）的情况下能够有效改善快速相关算法的估计性能,具有估计误差小、计算复杂度低和抗多径等特点。     

UWB中不可分离多径条件下的ML改进算法

UWB(Ultra Wideband)系统多用于室内环境中,其多径干扰非常严重,在这种情况下对信道进行精确估计是非常必要的,但同时也是非常困难的.在可分离多径情况下,最大似然算法具有比较好的性能.而在不可分离多径情况下,最大似然算法的性能很差,文中对ML算法进行了改进,可以比较理想的估出信道参数使其能够适用于不可分离多径环境.     

OFDMA上行系统中基于随机集理论的多用户信道估计

针对正交频分多址(OFDMA)上行系统,提出一种基于随机集理论的导频辅助多用户信道估计算法。该算法利用有限随机集合来建模和表示OFDMA上行系统中的用户状态、各用户对应的多径信道状态以及信道冲激响应等未知量,采用贝叶斯滤波理论来描述多用户信道估计问题,通过使用Rao-Blackwellized粒子滤波算法,实现了活动用户数和信道多径数动态变化情况下的多用户时变信道估计。计算机仿真结果证明了该算法的有效性。     

一种水声通信Turbo均衡中的软迭代信道估计算法

 Turbo均衡技术是水声相干通信克服信道多径、消除码间干扰(ISI)的有效工具。Turbo均衡实际使用时需要对时变、多径信道进行良好的估计。为了提高信道估计的效果,该文基于时变横向滤波和相位旋转信道模型,提出一种水声通信Turbo均衡中的软迭代信道估计算法。该算法采用快速自优化最小均方算法得到各数据符号处的横向滤波器系数矢量并与二阶锁相环联合优化计算。通过仿真比较,该算法明显优于硬迭代信道估计算法,且相位估计性能优于其他文献中的软迭代信道估计算法。在海上试验中,水声通信距离5 km,方向近似垂直,接收阵起伏周期10 s,起伏幅度5 m左右,在此情况下进行数据采集。将该算法用于对海试数据的单通道Turbo均衡处理,实现无误码输出,验证了所提算法在软迭代信道相位估计方面的优势。     

OFDM系统中一种改进的最大似然同步迭代算法

在考虑多径衰落信道的影响下,改进了基于循环前缀的最大似然(ML)同步迭代算法,弥补了原ML迭代算法只在高斯白噪声信道背景下才能得到准确的定时和频率偏差估计的不足,实现了多径衰落信道下的同步估计.并在多径衰落信道下进行了仿真实验,结果表明改进迭代算法在具有较好的同步性能.     

基于 ISL0 算法的码间干扰稀疏多径信道估计

针对存在码间干扰ISI的稀疏多径信道,已提出基于压缩感知理论的平滑SL0算法来研究其稀疏特性,然而SL0算法的迭代方向为负梯度方向,存在“锯齿效应”,且其代价函数“陡峭性”性能欠佳,使得信道估计和收敛效果均未达到最优。因此提出利用拉格朗日算子,结合牛顿法来改进和优化SL0算法,获得了快速和高效的信号重构ISL0算法,对稀疏多径信道状态信息进行了相关估计,分析了信噪比SNR和迭代次数等参数对重构信号均方误差MSE的影响。比较了ISL0算法与其他相关算法的迭代时间以及对稀疏信道中ISI均衡效果的差异。算法的优越性通过仿真得到验证,实时仿真结果显示ISL0算法能很好地对稀疏信道进行估计。在同样信道环境条件下,相比CoSaMP、SL0及其他算法,ISL0算法的性能有了较大提高。     

802.16a OFDM系统中基于DFT信道估计算法的研究

信道估计技术是实现OFDM系统的关键技术之一。对OFDM系统中的信道估计算法LS、LMMSE和3种时域估计器进行了研究,分析了它们的复杂度,并在802.16a多径衰落信道下进行了仿真和分析。     

一种基于GY／T220．1-2006标准的OFDM信道估计算法

在卫星移动多媒体广播系统中,由于多普勒频移及多径影响,信道是时变的,需要估计出信道的时域或频域响应来消除时变信道对传输信号的影响。针对GY/T 220.1-2006标准的导频插入图案,提出了一种基于LS估计准则、在时间轴方向二维线性内插、频域轴方向变换域内插的信道估计算法。仿真结果表明,在不同多径信道的情况下,随着信噪比的增加,该算法的性能均优于最近插值、线性插值和低通滤波插值算法。该算法计算复杂度较spline插值和cubic插值低,适于硬件实现。     

Sparse least mean mixed‐norm adaptive filtering algorithms for sparse channel estimation applications

Sparse least‐mean mixed‐norm (LMMN) algorithms are developed to improve the estimation performance for sparse channel estimation applications. Both the benefits of the least mean fourth and least mean square algorithms are utilized to exploit a type of sparse LMMN algorithms. The proposed sparse‐aware LMMN algorithms are implemented by integrating an l ₁‐norm or log‐sum function into the cost function of traditional LMMN algorithm so that they can exploit the sparse properties of the broadband multi‐path channel and achieve better channel estimation performance. The proposed sparse LMMN algorithms are equal to adding an amazing zero‐attractor in the update equation of the traditional LMMN algorithm, which aim to speed up the convergence. The channel estimation performance of the proposed sparse LMMN algorithms are evaluated over a sparse broadband multi‐path channel to verify their effectiveness. Simulation results depict that the sparse LMMN algorithms are superior to the previously reported sparse‐aware least mean square/fourth, least mean fourth and least mean square and their corresponding sparse‐aware algorithms in terms of both the convergence and steady‐state behavior when the broadband multi‐path channel is sparse. Copyright © 2016 John Wiley & Sons, Ltd.     

OFDM系统频偏自适应跟踪算法的研究

为了减小正交频分复用系统受频率偏差的影响,在OFDM系统中设计了一种新的载波频偏估计算法.频偏估计包括跟踪和捕获两个阶段,文中采用变步长自适应算法来进行跟踪,这个跟踪算法的捕捉范围是整个信号带宽的一半.通过此方法,不但可以利用前向纠错的方式来避免反馈,而且可以缩减复数乘法的次数以降低计算复杂度和系统功耗.该方法运算复杂度低,并具有较好的收敛性,能改善ODFM的解调性能.从计算机的仿真效果可以看出无论是在AWGN信道上还是在多径信道上都表现出了卓越的性能.     

OFDM同步跟踪阶段的频偏估计算法

ＯＦＤＭ对栽频偏差是很敏感的，因此不仅在同步的捕获阶段，而且在同步的跟踪阶段，精确的频偏估计是很重要的。文献［３］提出了一种简化的相干判决反馈的迭代算法来估计同步跟踪阶段的载频偏差，对于１２８个子载波、ＱＰＳＫ调制的ＯＦＤＭ系统，在多径衰落信道下，当频偏小于子载波间隔的１５％时，频偏估计的标准方差小于１％，但是这个结果是在假设信道频率响应、定时偏差、载波相位等参数已知的条件下取得的，而当这些参数的估计存在误差时，由仿真结果可看出，频偏估计性能恶化了，因此，提出了采用差分判决反馈的频偏估计算法，虽然只能估计小于子载波间隔 ８％的频偏，但差分判决反馈算法不需要知道信道的参数，由于在同步跟踪阶段，频偏一般都较小，因此采用差分判决反馈算法可以很好地估计出同步跟踪阶段的频率偏差。     

Channel Estimation in OFDM Systems With Unknown Power Delay Profile Using Transdimensional MCMC

This paper considers the problem of channel estimation for orthogonal-frequency-division multiplexing (OFDM) systems, where the number of channel taps and their power delay profile are unknown. Using a Bayesian approach, we construct a model in which we estimate jointly the coefficients of the channel taps, the channel order and decay rate of the power delay profile (PDP). In order to sample from the resulting posterior distribution we develop three novel Trans-dimensional Markov chain Monte Carlo (TDMCMC) algorithms and compare their performance. The first is the basic birth and death TDMCMC algorithm. The second utilizes Stochastic Approximation to develop an adaptively learning algorithm to improve mixing rates of the Markov chain between model subspaces. The third approximates the optimal TDMCMC proposal distribution for between-model moves using conditional path sampling proposals. We assess several aspects of the model in terms of sensitivities to different prior choices. Next we perform a detailed analysis of the performance of each of the TDMCMC algorithms. This allows us to contrast the resulting computational effort required under each approach versus the estimation performance. Finally, using the TDMCMC algorithm which produces the best performance in terms of exploration of the model subspaces, we assess its performance in terms of channel estimation mean-square error (MSE) and bit error rate (BER). It is shown that the proposed algorithm can achieve results very close to the case where both the channel length and the PDP decay rate are known.      

一种基于非完全数据的路径损耗模型选择算法

为尽可能选择反应实际信道衰减特性的路径损耗模型,该文针对无线传感器网络中的路径损耗提出一种多模型选择算法。首先分析一组路径损耗模型的统计特性,然后考虑接收信号强度(RSS)的非完全数据,提出基于期望最大化(EM)的参数估计算法,最后在准则函数的基础上给出表征模型优劣的权重系数,建立了一种进行路径损耗模型筛选的量化方法。实验分析表明,该算法的参数估计较为准确,且与同类算法相比,该算法甄别出的最优模型与实验数据有较好的拟合度。     

Frequency estimation in slowly fading multipath channels

This paper concerns the estimation of a frequency offset of a known (pilot) signal propagated through a slowly fading multipath channel, such that channel parameters are considered to he constant over the observation interval. We derive a maximum-likelihood (ML) frequency estimation algorithm for additive Gaussian noise and path amplitudes having complex Gaussian distribution when covariance matrices of the fading and noise are known; we consider in detail the algorithm for the white noise and Rayleigh fading, in particular, for independent fading of path amplitudes and pilot signals with diagonal autocorrelation matrices. For the latter scenario, we also derive an ML frequency estimator when the power delay profile is unknown, but the noise variance and bounds for the path amplitude variances are specified; in particular, this algorithm can be used when path delays and amplitude variances are unknown. Finally, we consider frequency estimators which do not use a priori information about the noise variance; these algorithms are also operable without timing synchronization. All the frequency estimators exploit the multipath diversity by combining periodograms of multipath signal components and searching for the maximum of the combined statistic. For implementation of the algorithms, we use a fast Fourier transform-based coarse search and fine dichotomous search. We perform simulations to compare the algorithms. The simulation results demonstrate high accuracy performance of the proposed frequency estimators in wide signal-to-noise ratio and frequency acquisition range.     

初始判决指导下的DS/CDMA最大似然检测算法

本文首先给出了多径异步多用户ＤＳ／ＣＤＭＡ系统的一种数学模型，得出了恒参信道下最大似然检测（ＭＬＳＥ）算法的一种新的表示形式。然后作者具体分析了以ＲＡＫＥ接收机作为衰落信道的匹配滤波器时，最大似然检测器的算法设计问题。分析指出，在多径环境下ＭＬＳＥ算法的复杂度和计算量与多径时延的分布有关，如果用户时延扩散在一个信息码元之内，算法复杂度和恒参信道下相同，而其实现可以用状态数可变的Ｖｉｔｅｒｂｉ算法来实现。最后，本文用传统判决方法得出的初始判决信息缩减Ｖｉｔｅｒｂｉ算法的搜索空间，在保证一定性能的前提下，算法的计算复杂度大大降低。     

Channel Estimation Method with Improved Performance for the UMTS-TDD Mode

Channel estimation is an essential building block for UTRA-TDD high performance receivers. Once the performance of the channel estimator algorithm proposed by 3GPP is highly dependent on the time spreading between consecutive multi-path components, a Successive Multi-path channel Estimation Technique (SMET) that improves the time resolution is proposed in this paper. A SMET based maximum likelihood approach for vectorial channel estimation, to include the estimation of the direction-of-arrival, is also proposed. This algorithm solves efficiently the complex problem of DOA estimation of multiple users in a multi path propagation environment even when the number of required DOA's exceeds the number of antenna array elements. Another property of the proposed algorithm is its ability to resolve signals from different users arriving from the same direction. This is due to processing in both time and space dimensions. The performance of these algorithms is assessed by resorting to simulations in multi-path environments using the UMTS-TDD specifications, and also by comparing the rms estimation errors against the Crámer-Rao Bound. The effect of imperfect channel estimation on the performance of RAKE and Hard-Decision Parallel Interference Canceller receivers is also analysed. The results show that a good performance can be achieved with SMET, from low to high values of Eb/n ₀.     

5G多载波通信中信道估计干扰抑制均衡算法

传统5G多载波通信中信道估计干扰抑制算法存在着均衡性能较差的问题,表现为误码元数与误码率偏高,因此文章提出5G多载波通信中信道估计干扰抑制均衡算法。该算法首先对干扰项进行过采样处理,引入预处理矩阵以减小模损失的影响,对信道估计干扰进行均衡抑制。仿真实验结果表明,在信噪比相同的情况下,5G多载波通信中信道估计干扰抑制均衡算法的误码元数比两种传统算法分别低了161、192,其误码率分别低了24%、31%,均衡性能较好。     

八天线TD-LTE系统的波束赋形算法分析

多天线是天线技术的发展趋势,TD-LTE引入了8发2收的天线配置.基于小间距多天线阵列,利用TDD系统信道互易性,波束赋形技术可以根据上行导频获得信道信息,形成对基带(中频)信号的最佳组合或者分配,补偿无线传播过程中由空间损耗、多径效应等因素引入的信号衰落与失真,同时降低同信道用户间的干扰.EBB(Eigen-based Beamforming)算法是波束赋形主要算法之一,该算法中在整个波束空间中,找到使接收信号功率最大的赋形权矢量.通过仿真,对EBB算法在各种应用场景下的性能进行了分析,结果表明八天线EBB波束赋形算法可以正确实现波束合成,在低速或上行信道信息估计误差较小情况下能够明显提高系统性能.