Machine-learning-based high-resolution DOA measurement and robust directional modulation for hybrid analog-digital massive MIMO transceiver  

作　　者：Zhihong ZHUANG Ling XU Jiayu LI Jinsong HU Linlin SUN Feng SHU Jiangzhou WANG 

机构地区：[1]School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China [2]The College of Physics and Information,Fuzhou University,Fuzhou 350108,China [3]School of Engineering and Digital Arts,University of Kent,Canterbury CT27NT,UK

出　　处：《Science China(Information Sciences)》2020年第8期17-34,共18页中国科学（信息科学）（英文版）

基　　金：National Natural Science Foundation of China(Nos.61771244,61871229)。

摘　　要：At hybrid analog-digital(HAD)transceiver,an improved HAD estimation of signal parameters via rotational invariance techniques(ESPRIT),called I-HAD-ESPRIT,is proposed to measure the direction of arrival(DOA)of a desired user,where the phase ambiguity due to HAD structure is dealt with successfully.Subsequently,a machine-learning(ML)framework is proposed to improve the precision of measuring DOA.Meanwhile,we find that the probability density function(PDF)of DOA measurement error(DOAME)can be approximated as a Gaussian distribution by the histogram method in ML.Then,a slightly large training data set(TDS)and a relatively small real-time set(RTS)of DOA are formed to predict the mean and variance of DOA/DOAME in the training stage and real-time stage,respectively.To improve the precisions of DOA/DOAME,three weight combiners are proposed to combine the-maximum-likelihood-learning outputs of TDS and RTS.Using the mean and variance of DOA/DOAME,their PDFs can be given directly,and we propose a robust beamformer for directional modulation(DM)transmitter with HAD by fully exploiting the PDF of DOA/DOAME,especially a robust analog beamformer on RF chain.Simulation results show that:(1)the proposed I-HAD-ESPRIT can achieve the HAD Cramer-Rao lower bound(CRLB);(2)the proposed ML framework performs much better than the corresponding real-time one without training stage;(3)the proposed robust DM transmitter can perform better than the corresponding non-robust ones in terms of secrecy rate.

关 键 词：hybrid analog and digital ESPRIT statistical learning DM robust precoder 

分 类 号：TN911.7[电子电信—通信与信息系统] TP181[电子电信—信息与通信工程]