… network mapping method for hybrid beamforming. By mapping the various HB architectures
to neural networks, the non-convex optimization of the hybrid beamforming problem can be …

… Hybrid beamforming techniques are used to reduce the number of RF chains with minimal
… complexity orthogonal hybrid beamforming design with the aid of a machine learning based …

… from the deep learning training process. In this paper, we adopt a mixed methodology in
designing the hybrid beamforming systems with the help of machine learning techniques. A …

… deep learning method to design the hybrid beamforming in massive MIMO systems. Furthermore,
we propose i) a method to … (IA); and ii) a method to design the codebook for the analog …

… machine learning method, perfect CSI is only required at the offline training phase to obtain
accurate beamformer … , and we just feed the learning network with noisy channel estimates [6]…

… This article proposes a hybrid beamforming design with … based on unsupervised machine
learning framework that exploits … The proposed hybrid beamforming scheme reduces the multi…

… Abstract—In this paper, we present a machine learning based radio resource management
(… We combine the radio resource management and hybrid beamforming design constraint to …

… of designing hybrid beamformers. Motivated by the recent success of machine learning (ML) …
can be effectively used for SVD and hybrid BF. To this end, we first present a data-driven …

… were employed to derive hybrid beamformers. In this paper, we introduce a deep
learning (DL) approach for channel estimation and hybrid beamforming for frequency-selective, …

… In this letter, we propose a federated learning (FL) framework for hybrid beamforming.
We … and hybrid beamformer design using unquantized and quantized deep learning networks,” …