基于扩展卡尔曼滤波的联合迭代检测译码信道估计方法

针对高速移动场景下信道快衰落、非平稳等特性导致下行链路信道估计性能受限的问题,提出了一种适用于高速移动环境下行链路的信道估计方法.采用自回归过程对信道建模,构造自反馈的扩展卡尔曼滤波器（Extended Kalman Filter,EKF）追踪信道响应及其时域相关系数.为了解决EKF自反馈结构引起的误差传播问题,采用了迭代检测译码的接收机结构,以利用信道编码的冗余提升EKF的信道估计精度.仿真分析表明,在高速移动环境下所提方法相较于最小二乘估计和线性最小均方误差估计等传统方法提升了信道估计的均方误差和系统的误码率性能,可应用于高速列车无线通信设备的接收机基带信号处理系统.     

高速移动环境下基于深度学习的信道估计方法

针对高速移动环境下信道快时变、非平稳特性导致下行链路信道估计性能受限的问题,本文提出一种基于深度学习的信道估计网络,即ChanEstNet.ChanEstNet使用卷积神经网络（Convolutional Neural Network,CNN）提取信道响应特征矢量和循环神经网络（Recurrent Neural Network,RNN）进行信道估计.我们利用标准的高速信道数据对学习网络进行离线训练,充分挖掘训练样本中的信道信息,使其学习到高速移动环境下信道快时变和非平稳的特点,更好的跟踪高速环境下信道的变化特征.仿真结果表明,在高速移动环境下,与传统方法相比,所提信道估计方法计算复杂度低,性能提升明显.     

MIMO扩频通信系统矩阵信道估计

为了解决第三代移动通信系统下行链路容量瓶颈问题，在HSDPA的解决方案中，MIMO系统的提案越来越受到重视。本文提出了一种移动深衰落环境下的MIMO系统信道估计方案，并进行了详细的理论推导，给出了独立MIMO深衰落信道环境下的仿真结果。     

LTE上行引入MIMO后的MLE信道估计算法

主要介绍LTE系统上行链路引入MIMO后的信道估计技术。首先介绍了基础的上行和下行信道估计的方法以及他们的区别,然后着重指出了在进行上行MIMO的信道估计时遇到的问题,并阐述了该问题的具体解决方法和详细的公式推导,最后通过对含有MIMO技术的上行LTE链路层的仿真,对在LTE上行MIMO系统中采用MLE算法进行信道估计的精确性进行了验证。     

MIMO—OFDM低延迟信道估计改进算法

为了克服多输入多输出正交频分复用（MIMO—OFDM）移动系统中采用空间复用技术的下行链路性能出现衰退现象,提出一种信道估计改进算法。它根据信道状态并通过一个决策指导方案为4×4 MIMO系统提供大约4bit／s／Hz的数据。通过使用LDPC短码,在LDPC译码器输出端采用MIMO—OFDM符号重建方法,达到提高估计精度的目的。在3GPP MIMO空间信道模型下进行了仿真验证,结果表明指定速率下的估计精度得到改善。     

MIMO-OFDM低延迟信道估计改进算法

为了克服多输入多输出正交频分复用(MIMO-OFDM)移动系统中采用空间复用技术的下行链路性能出现衰退现象,提出一种信道估计改进算法。它根据信道状态并通过一个决策指导方案为4×4 MIMO系统提供大约4bit/s/Hz的数据。通过使用LDPC短码,在LDPC译码器输出端采用MIMO-OFDM符号重建方法,达到提高估计精度的目的。在3GPP MIMO空间信道模型下进行了仿真验证,结果表明指定速率下的估计精度得到改善。     

大规模MIMO系统中的动态导频分配方案

针对多小区大规模多输入多输出(MIMO)系统中存在的导频污染问题,通过分析MMSE信道估计产生的误差,提出了一种动态导频分配方案.该方案将目标小区与相邻小区相邻的边缘区域内的用户进行动态导频分配,剩余区域内的用户进行随机导频分配来提升系统下行链路的平均可达和速率.仿真结果表明,该方法不仅能显著地提升信道估计的性能,而且还能有效地提高整个系统下行链路的可达和速率.     

MC V-BLAST系统的MIMO信道盲估计

本文研究多载波垂直分层空时(MC V-BLAST)系统的下行频率选择性衰落多输入多输出(MIMO)无线信道估计问题.本文首先为MC V-BLAST系统提出了一种新颖的移不变性编码方法.利用上述移不变性性质,本文进一步提出了相应的下行频率选择性衰落MIMO无线信道的盲估计方法.仿真结果表明了本文移不变性编码方法的有效性和信道盲估计方法的性能.     

扩谱系统信道估计优化

本文提出一种易于集成实现的扩谱系统优化接收机信道估计方案，并以WCDMA系统下行链路为例进行了详细的理论推导与分析。给出了其在移动信道环境下的仿真结果。结果表明，改进方案与理想性能仅差约零点几分贝，比一般情形改进至少2dB。     

大规模MIMO无线专网下行链路检测算法研究

以充分开发利用大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)空间上的无线资源、提升系统频谱效率和功率效率为目标,在充分分析无线专网信道特点的基础上,提出了线性检测和非线性检测2种方案,将多级预编码和检测算法有机结合,对高斯、乡村、市区及山区等信道条件下的误码性能和吞吐量进行了仿真分析,验证了球形译码算法优于MMSE检测算法,适用于基于大规模MIMO无线通信专网下行链路高性能接收机。     

数字并行接收机在时变信道下的信道估计与均衡方法

为了适应高速宽带无线通信的需要,本文在一种高速数字并行接收机(APRX)结构的基础上,提出了一种时变信道下的信道估计和均衡方法。使用伪随机(pseudo-randomnumber,PN)序列相关进行信道估计,将所得到的信道频率响应粗估计按照一个DFT块的长度在一帧内进行线性内插得到信道频率响应细估计,将其用来在频域进行信道均衡。这种结构能适应高速率传输的要求,并且能有效地对抗时间和频率选择性衰落。仿真结果表明,在多径衰落信道下,APRX已经无法工作,而本文提出的数字并行接收机的信道估计和均衡方法有较好的性能,并且该方法实现简单,便于应用。     

基于历史信息的软卡尔曼滤波迭代时变信道估计方法

针对高速移动MIMO-OFDM系统,提出了一种基于历史信息的软卡尔曼滤波迭代时变信道估计方法。考虑高速铁路环境中不同列车在相同位置处的信道具有很强的相关性,首先利用历史列车的信道信息获取最优基函数,基于该基函数对信道建模,将对信道的估计转换成基系数的估计,降低了计算复杂度和提高了信道估计精度。其次,在每次迭代中采用了软卡尔曼滤波和数据检测联合的方法估计基系数;为了更好地减少数据检测误差传播的影响,采用软数据检测方法,并且在每次迭代中将软数据检测误差作为噪声进行处理。另外,采用的软卡尔曼滤波器不涉及 AR 模型跟踪因子,避免了估计跟踪因子引入的计算复杂度。仿真结果表明,所提方法具有更好的估计性能,且更适用于实际的高速移动场景的时变信道获取。     

基于BEM的非平稳双选信道估计方法

面向高速环境下的无线通信系统,针对高速信道的双选衰落和非平稳特性,提出一种基于基扩展模型（Basis Expansion Model,BEM）的贝叶斯滤波的信道估计方法.针对双选衰落特性,采用BEM信道模型,降低估计复杂度,消除子载波间干扰;针对非平稳特性,提出一种基于贝叶斯滤波的联合估计信道冲激响应与时变的时域自相关系数的信道估计方法.仿真分析表明,所提方法相较最小二乘法等传统方法在高速环境下能够提升估计精度和误码率性能.本方法特别适用于高速铁路的无线通信系统.     

高速铁路场景下环境反向散射辅助的无线传输方案

将反向散射技术引入到高铁场景的无线通信系统中,提出一种反向散射辅助无线传输方案（Backscatter Aided Wireless Transmission,BAWT）,并针对BAWT和传统无线传输方案（Direct Wireless Transmission,DWT）进行了收发信机设计,包括信道估计以及信号检测。与传统无线传输方案相比,证明了在固定的火车天线和不变的轨道情况下,BAWT可以获得信道统计信息为信道估计提供助力。通过仿真对比两种方案的信道估计均方误差,BAWT方案相较DWT方案的信道估计准确性明显提高;对比BAWT、传统中继技术以及DWT方案,当信噪比为20 dB时,对应的BAWT方案和中继技术、DWT方案的误码率分别为1%和2%和12%,BAWT方案误码检测性能获得明显提升。此外,针对广域环境下的环境反向散射通信,推导了高铁场景下使用蜂窝移动通信信号作为RF信源的无线链路预算,反向散射信号在车厢内的覆盖范围内可以满足接收机的灵敏度要求,从链路预算角度论证了BAWT方案实现的可行性。     

Blind multiuser detection: from MOE to subspace methods

The minimum output energy (MOE) multiuser receiver has been shown to approach the minimum mean-square-error (MMSE) receiver at high signal-to-noise ratio (SNR). However, performance degradation is incurred by noise induced channel estimation error. In this paper, we propose a Power of R (POR) technique to significantly improve the performance of the MOE receiver. It is shown that the new receiver asymptotically converges to the MMSE receiver without performance penalty. The convergence is established either under high SNR, with large exponent raised in the power of the covariance matrix, or with sufficiently large number of data samples. Connection between our POR method and a widely studied subspace method is investigated from the respective optimization criteria. Asymptotic equivalence between these two methods is also established. Extensive simulations based on finite data samples show that the proposed method significantly outperforms the subspace method in systems with medium to heavy loading, severe multipath distortion, or smaller processing gain. Moreover, adaptive implementation of the proposed method exhibits very robust performance in a dynamic loading environment.     

Hybrid channel estimation for MIMO relay systems with Doppler offset influences

The design of the channel estimation method in a multiple‐input multiple‐output (MIMO) relay system plays a highly crucial role in deciding the overall system performance. For the realistic scenarios specifically, with fast time‐varying channel conditions due to highly mobile communicating nodes, the degree of accuracy to which the channel estimates are obtained for MIMO relay systems influences the communication system reliability significantly. However, most of the channel estimation approaches proposed in literature for MIMO relay systems assume that the Doppler offset contributed by highly mobile nodes is already known to the receiver, ignoring the resulting nonlinear system dynamics. Hence, a novel hybrid algorithm is proposed to address the issue of time‐varying channel estimation under fast‐fading channel condition with Doppler offset influences contributed by high‐mobility communicating nodes for a 1‐way 2‐hop MIMO amplify‐and‐forward relaying system. The problem is first formulated as a nonlinear state‐space model, and then an algorithm is developed to estimate the individual source‐to‐relay and relay‐to‐destination channels in the presence of the associated dynamic Doppler offset. In the proposed method, a set of superimposed orthogonal pilots is used for aiding in the updation of the channel gains, since Kalman filter–based updation may lead to accumulation of estimation and prediction error. A detailed computational complexity analysis of the proposed hybrid algorithm is presented, which shows that the algorithm has moderate computational complexity with a good performance in fast time‐varying channel conditions with high node mobility in a dual‐hop MIMO relay system.     

基于压缩感知的高速移动环境中OFDM信道估计

针对目前高速移动信道中通信质量较差,为降低高速移动环境中信道估计误差,建立了以Winner Ⅱ信道为基础的高速信道OFDM系统仿真模型,通过压缩感知技术对移动信道进行估计,并与传统的信道估计方法进行比较.仿真结果表明,压缩感知技术能大幅度提高高速移动环境中的OFDM系统信道估计精度.     

Soft‐output MMSE V‐BLAST receiver with MMSE channel estimation under correlated Rician fading MIMO channels

For wireless multiple‐input multiple‐output (MIMO) communications systems, both channel estimation error and spatial channel correlation should be considered when designing an effective signal detection system. In this paper, we propose a new soft‐output MMSE based Vertical Bell Laboratories Layered Space‐Time (V‐BLAST) receiver for spatially‐correlated Rician fading MIMO channels. In this novel receiver, not only the channel estimation errors and channel correlation but also the residual interference cancellation errors are taken into consideration in the computation of the MMSE filter and the log‐likelihood ratio (LLR) of each coded bit. More importantly, our proposed receiver generalizes all existing soft‐output MMSE V‐BLAST receivers, in the sense that, previously proposed soft‐output MMSE V‐BLAST receivers can be derived as the reduced forms of our receiver when the above three considered factors are partially or fully simplified. Simulation results show that the proposed soft‐output MMSE V‐BLAST receiver outperforms the existing receivers with a considerable gain in terms of bit‐error‐rate (BER) performance. Copyright © 2011 John Wiley & Sons, Ltd.