A transfer learning method is proposed in this paper based on the assumption that some com-mon features exist among different channel models.
Abstract—Angle-of-arrivals (AoAs) estimation is one of the key tasks of localization in massive multiple-input-multiple-output. (MIMO) system.
Extensive simulation results demonstrate that the AoAs estimation accuracy of the proposed method is comparable to that of supervised DL-based methods, ...
Data-driven methods follow the end-to-end principle of DL, where the estimation is achieved by training neural networks on a large number of training data (e.g. ...
journal：2022 IEEE/CIC International Conference on Communications in China (ICCC) Authors：Zhiheng Guo; Kuijie Lin; Xiang Chen; Chong-Yung Chit
In this paper, for CF massive MIMO system based on FDD, we provide compressive sensing (CS) of directions of arrival (DoAs) estimation approach of access point ...
Missing: Arrivals | Show results with:Arrivals
In this paper, we propose deep learning-based channel estimation and pilot reduction for mmWave point-to-point multi-input multi-output systems.
Missing: Arrivals | Show results with:Arrivals
This thesis investigates the opportunities of using machine learning for DoA estimation in these automotive radar systems. We have focussed on different aspects ...
Jul 16, 2023 · DOA estimation using massive MIMO systems could achieve an ultra-high precision of angles, which could pave the way to the angle of arrival (AOA) ...
Missing: Arrivals | Show results with:Arrivals
Abstract—This paper analyzes the feasibility of deep convo- lutional neural networks (DCNN) for accurate ultra-wideband. (UWB) angle of arrival estimation ...