Z Lu, R Li, K Lu, X Chen, E Hossain… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Along with the springing up of the semantics-empowered communication (SemCom) research, it is now witnessing an unprecedentedly growing interest towards a wide range of …
This paper deals with the use of emerging deep learning techniques in future wireless communication networks. It will be shown that the data-driven approaches should not …
H Ye, L Liang, GY Li, BH Juang - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this article, we develop an end-to-end wireless communication system using deep neural networks (DNNs), where DNNs are employed to perform several key functions, including …
Thanks to the recent advances in processing speed, data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many …
FA Aoudia, J Hoydis - IEEE Journal on Selected Areas in …, 2019 - ieeexplore.ieee.org
The idea of end-to-end learning of communication systems through neural network (NN)- based autoencoders has the shortcoming that it requires a differentiable channel model. We …
In multi-user millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems, hybrid precoding is a crucial task to lower the complexity and cost while achieving a …
AM Elbir, KV Mishra - IEEE Transactions on Wireless …, 2019 - ieeexplore.ieee.org
In millimeter-wave communications, multiple-input-multiple-output (MIMO) systems use large antenna arrays to achieve high gain and spectral efficiency. These massive MIMO systems …
Existing communication systems exhibit inherent limitations in translating theory to practice when handling the complexity of optimization for emerging wireless applications with high …
AM Elbir - IEEE Communications Letters, 2019 - ieeexplore.ieee.org
Hybrid beamformer design is a crucial stage in millimeter-wave (mmWave) MIMO systems. In this letter, we propose a convolutional neural network (CNN) framework for the joint …