OTFS系统SBL-Turbo压缩感知信道估计算法  

SBL-Turbo Compressed Sensing for Channel Estimation in OTFS Systems

作　　者：张华卫[1] 刘佳 蒋占军[1] 李翠然[1] 唐喜娟 ZHANG Huawei;LIU Jia;JIANG Zhanjun;LI Cuiran;TANG Xijuan(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou,Gansu 730070,China)

机构地区：[1]兰州交通大学电子与信息工程学院,甘肃兰州730070

出　　处：《信号处理》2024年第6期1074-1081,共8页Journal of Signal Processing

基　　金：国家自然科学基金(62161016);甘肃省科技计划基金资助项目(20JR10RA273)。

摘　　要：针对正交时频空调制(OTFS)系统由多普勒频移引起的信道估计准确度下降的问题,本文提出了一种联合无线信道在时延-多普勒域稀疏特性的SBL-Turbo压缩感知信道估计算法。首先,对时延-多普勒域稀疏信道建模,使其服从以噪声功率为条件的高斯先验分布,利用稀疏贝叶斯学习模块估计得到稀疏信道的均值与方差,并结合期望最大化算法更新高斯先验模型中的参数。其次,引入了LMMSE(线性最小均方误差)估计器模块,该模块对稀疏信道的后验分布进行再估计,提高估计的准确度。通过对每个模块估计得到的信道后验分布进行数据处理,使得模块的输入值与输出值解耦,进而减少模块间的错误传播。最后,两个模块采用Turbo结构迭代估计信道的后验分布,得到信道状态信息。实验结果表明,相较于其他估计方法,该算法能够显著提高信道估计的精度,并且改善系统的误码率性能,能够有效地解决OTFS系统中由多普勒频移引起的信道估计问题。In order to solve the problem of channel estimation accuracy degradation caused by Doppler shift in an orthogonal time frequency space(OTFS)system,this study investigated an SBL-Turbo compressed sensing channel estimation algorithm that jointly characterized the sparse nature of a wireless channel in a delay-Doppler domain.First,the sparse channel in the delay-Doppler domain was modeled as obeying a Gaussian prior model conditioned on the noise power.The mean and variance of the sparse channel were obtained by using a sparse Bayesian learning module,and an expectation-maximization algorithm was incorporated to update the parameters of the Gaussian prior model.Second,a linear minimum mean square error estimator module was introduced to improve the accuracy of the estimates,which re-estimated the posterior distribution of the sparse channel.The input values of the modules were decoupled from the output values by performing data processing on the channel posterior distribution estimated by each module,which in turn reduced the error propagation between blocks.Finally,the two modules used the Turbo structure to iteratively estimate the posteriori distribution of the channel and obtained the channel state information.Experimental results showed that compared with other estimation methods,this algorithm could improve the channel-estimation accuracy and BER perfor‐mance of the system,and effectively solve the channel estimation problem caused by the Doppler shift in an OTFS system.

关 键 词：正交时频空调制 信道估计 压缩感知 稀疏贝叶斯学习 

分 类 号：TN92[电子电信—通信与信息系统]