论文标题

MMWave大量MIMO的渠道状态信息的获取:基于传统和机器学习的方法

Acquisition of Channel State Information for mmWave Massive MIMO: Traditional and Machine Learning-based Approaches

论文作者

Qi, Chenhao, Dong, Peihao, Ma, Wenyan, Zhang, Hua, Zhang, Zaichen, Li, Geoffrey Ye

论文摘要

通道状态信息(CSI)采集的准确性直接影响毫米波(MMWave)通信的性能。在本文中,我们提供了有关CSI采集的概述,包括MMWave大量多输入多输出系统的光束训练和频道估计。光束训练可以避免估计高维通道矩阵,而通道估计可以灵活利用高级信号处理技术。除了在本文中介绍传统和机器学习的方法外,我们还比较了光谱效率,计算复杂性和开销方面的不同方法。

The accuracy of channel state information (CSI) acquisition directly affects the performance of millimeter wave (mmWave) communications. In this article, we provide an overview on CSI acquisition, including beam training and channel estimation for mmWave massive multiple-input multiple-output systems. The beam training can avoid the estimation of a high-dimension channel matrix while the channel estimation can flexibly exploit advanced signal processing techniques. In addition to introducing the traditional and machine learning-based approaches in this article, we also compare different approaches in terms of spectral efficiency, computational complexity, and overhead.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源