… and downlink with joint optimization of power allocation and transceiver beamforming. However,
… Deep learning (DL), also known as the deep neural network technology, that consists of …

… paper, we propose a deep learning framework for the optimization of downlink beamforming.
In … Using this framework, we construct three beamforming neural networks (BNNs) for three …

… Hence, we consider the joint problem with hybrid beamformers and write the joint antenna
… RF beamformers for the given channel matrix. We introduce the proposed deep learning …

… tasking DNN where the DNN is trained to jointly do classification and regression task. To …
deep learning methods to train a multi-tasking DNN and directly design the hybrid beamforming …

… beamforming vector, we propose a deep learning framework to obtain each user’s beamforming
… analysis, we construct a beamforming deep neural network (BFDNN) to predict nu and …

… deep learning and coordinated beamforming solution, and develop its system operation and
machine learning … , but also predicting best NLOS beamforming vectors given the joint multi…

… a deep learning approach where the optimization module is replaced with a well-trained
deep … To this end, we develop a structural learning process which constructs a DNN to always …

… In this study, a novel deep learning-based optimisation method is proposed to overcome
the high computational complexity of joint beamforming design and power allocation …

… In this paper, we formulate the joint design of beamforming, … deep reinforcement learning.
By using the greedy nature of … Over the last two years, the use of deep learning in wireless …

… consider joint antenna selection and hybrid beamformer design problem in deep learning …
) where antenna selection and hybrid beamformer design can be performed jointly. In order to …