论文标题
基于特征特征的MMWave系统的新型频道识别体系结构
A Novel Channel Identification Architecture for mmWave Systems Based on Eigen Features
论文作者
论文摘要
由于高速，大带宽和超低延迟的许多优势，毫米波（mmwave）通信技术已经迅速发展。但是，MMWave通信系统遭受快速褪色和频繁阻断的困扰。因此，MMWave的理想通信环境是视线（LOS）频道。为了提高MMWave系统的效率和能力，并更好地构建所有内容（IOE）服务网络的互联网，本文重点介绍了视线（LOS）和非LOS（NLOS）环境中的频道识别技术。考虑到用户设备（UES）的计算能力有限，本文提出了一种基于特征特征的新型通道识别体系结构，即通道状态信息（CSI）的特征特征，即特征和特征。此外，本文使用MMWave探索了聚类的延迟线（CDL）通道识别，该渠道由第三代合作伙伴项目（3GPP）定义。实验结果表明，基于EMEV的方案可以实现99.88％的识别精度，假设CSI完美。在鲁棒性测试中，可以耐受最大噪声为SNR = 16 dB，阈值ACC \ geq 95％。此外，基于EMEV功能的新型体系结构将使综合开销降低约90％。
Millimeter wave (mmWave) communication technique has been developed rapidly because of many advantages of high speed, large bandwidth, and ultra-low delay. However, mmWave communications systems suffer from fast fading and frequent blocking. Hence, the ideal communication environment for mmWave is line of sight (LOS) channel. To improve the efficiency and capacity of mmWave system, and to better build the Internet of Everything (IoE) service network, this paper focuses on the channel identification technique in line-of- sight (LOS) and non-LOS (NLOS) environments. Considering the limited computing ability of user equipments (UEs), this paper proposes a novel channel identification architecture based on eigen features, i.e. eigenmatrix and eigenvector (EMEV) of channel state information (CSI). Furthermore, this paper explores clustered delay line (CDL) channel identification with mmWave, which is defined by the 3rd generation partnership project (3GPP). Ther experimental results show that the EMEV based scheme can achieve identification accuracy of 99.88% assuming perfect CSI. In the robustness test, the maximum noise can be tolerated is SNR= 16 dB, with the threshold acc \geq 95%. What is more, the novel architecture based on EMEV feature will reduce the comprehensive overhead by about 90%.
