太赫兹MIMO系统中基于SRCGAN的空时频信道估计方案  

Space-Time-Frequency Channel Estimation Scheme for Terahertz MIMO Based on SRCGAN Systems

作　　者：蒋奕采 季薇[1] JIANG Yicai;JI Wei(College of Telecommunications and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003

出　　处：《移动通信》2024年第6期97-104,114,共9页Mobile Communications

基　　金：国家自然科学基金“基于量子机器学习的6G空频时非平稳信道估计和预编码技术研究”(62271265)。

摘　　要：为了能有效利用THz-MIMO系统的多维信道特性,提出一种基于SRCGAN的THz-MIMO系统信道估计方案。在该方案中,由预估计模块获得的初始空时域信道响应矩阵被视作一张二维的低分辨率图像,利用SRCGAN网络提取太赫兹信道的空时特性进行空时域信道补全获得完整的信道信息,然后相邻子载波之间的频率相关性作为SRGAN提供的条件信息提升信道估计精度。为了增强SRCGAN网络对时变信道预测的鲁棒性,在线上估计阶段,基于最大均方误差准则采用梯度下降算法对输入的预估计信道信息矩阵进行迭代更新。仿真结果证明了基于SRCGAN的空时频信道估计方案性能的优越性,以及利用信道“空时频”的相关性提升估计精度的有效性。Terahertz's input multi-output technology is of bandwidth and high reuse gain,which can provide higher data rates and larger network capacity.It is the core technology of the sixth generation of mobile communication.However,the severe frequency selective decline effect and a large number of antennas in the Terahertz MIMO system have brought huge challenges to channel estimates.Traditional channel estimation methods are difficult to accurately estimate channels in the increasingly complex wireless communication environment.In the past research,some scholars combine super-resolution with deep learning network to propose the channel estimation framework.The network estimates all channel status information based on the channel information of the pilot.However,the previous work was mainly concentrated in the mapping of learning frequency domains and time domain channels,and there was no comprehensive consideration of the channel correlation among time,space and frequency domain.This article focuses on the three-dimensional channel correlation and proposes a channel estimation algorithm based on super resolution conditional generative adversarial networks.In this scheme,the initial space-time channel response matrix in this scheme is regarded as a two-dimensional low-resolution picture.Then,the space-time characteristics of the terahertz channel are extracted by the super resolution generative adversarial network,and the high-resolution picture is obtained by the adversarial learning of the generator and discriminator,namely the complete channel matrix.In order to make full use of the multi-dimensional channel characteristics of terahertz channel and further improve the performance of the channel estimation,this thesis proposes a channel estimation algorithm based on super resolution conditional generative adversarial network.The data is optimized with pre-arranged methods and the structure of deep neural networks.In this scheme,we cache the channel matrix of the previous subcarrier based on the rough estimate of pilot

关 键 词：THz-MIMO 信道估计 空时频域 超分辨率 条件生成对抗网络 

分 类 号：TN929.5[电子电信—通信与信息系统]