多用户大规模MIMO-OTFS信道参数估计方法

Channel Parameter Estimation for Multi-user Massive MIMO-OTFS Systems

高速移动环境会导致信道的双弥散效应,给无线通信系统带来巨大挑战。正交时频空间(orthogonal time frequency space,OTFS)调制通过将时-频域的双弥散信道转换为时延-多普勒域的平坦衰落信道,能够有效缓解双弥散信道带来的频率和时间选择性衰落的影响。针对多用户大规模多输入多输出(multiinput multi-output,MIMO)OTFS系统中的信道参数估计问题,通过对多天线信道结构特征进行深入分析,将用户与基站间的信道建模为稀疏结构模型。将大规模MIMO信道划分为多个群组,设计了适用于多用户大规模MIMO-OTFS系统的导频图案,提出了基于群组块共稀疏阈值结构化贝叶斯学习信道估计算法。利用估计得到的信道状态信息设计了分数多普勒频移、到达角度等信道参数估计方法,从而进一步感知用户状态。仿真结果表明,提出的信道参数估计算法具有更高的估计精度和系统频谱效率。

High-mobility scenarios are known to pose a significant challenge to wireless communications systems due to the resulting doubly-dispersive wireless channel.The orthogonal time frequency space(OTFS)modulation is a two-dimensional modulation method that maps the transmitted signal to the delay-Doppler domain.By converting the doubly-dispersive channel in the time-frequency domain into a flat channel in the delay-Doppler domain,the OTFS modulation can effectively overcome the effects of frequency selective fading and time selective fading.To address the channel parameter estimation problem in multi-user massive multi-input multi-output(MIMO)OTFS systems,firstly,through in-depth analysis of the multi-antenna channel structure characteristics,the channel between users and base stations is modeled as a sparse structure model.Afterwards,the massive MIMO channel is divided into multiple groups,and a pilot pattern suitable for multi-user massive MIMO-OTFS systems is designed.A sparse Bayesian learning channel estimation algorithm based on group block structure and common sparse threshold is proposed.Finally,with the estimated channel state information,a method for estimating channel parameters such as fractional Doppler and angle of arrival is designed to further perceive the users'states.The simulation results show that the proposed channel parameter estimation algorithm outperform the traditional methods in estimation accuracy and system spectral efficiency.