no code implementations • 15 Nov 2023 • YiFan Li, Feng Shu, Jun Zou, Wei Gao, Yaoliang Song, Jiangzhou Wang
To satisfy the high-resolution requirements of direction-of-arrival (DOA) estimation, conventional deep neural network (DNN)-based methods using grid idea need to significantly increase the number of output classifications and also produce a huge high model complexity.
no code implementations • 11 Sep 2022 • YiFan Li, Baihua Shi, Feng Shu, Yaoliang Song, Jiangzhou Wang
To improve the accuracy of direction-of-arrival (DOA) estimation, a deep learning (DL)-based method called CDAE-DNN is proposed for hybrid analog and digital (HAD) massive MIMO receive array with overlapped subarray (OSA) architecture in this paper.
no code implementations • 2 Mar 2022 • YiFan Li, Feng Shu, Jinsong Hu, Shihao Yan, Haiwei Song, Weiqiang Zhu, Da Tian, Yaoliang Song, Jiangzhou Wang
The simulation results show that the machine learning-based methods can achieve good results in signal classification, especially neural networks, which can always maintain the classification accuracy above 70\% with massive MIMO receive array.
no code implementations • 3 Nov 2020 • YiFan Li, Feng Shu, Baihua Shi, Xin Cheng, Yaoliang Song, Jiangzhou Wang
First, fixing the nth BS, by exploiting multiple measurements along trajectory, the position of UAV is computed by ML rule.