A CNN-LSTM-Based Fusion Separation Deep Neural Network for 6G Ultra-Massive MIMO Hybrid Beamforming

A CNN-LSTM-Based Fusion Separation Deep Neural Network for 6G Ultra-Massive MIMO Hybrid Beamforming

In the sixth-generation (6G) cellular networks, hybrid beamforming would be a real-time optimization problem that is becoming progressively more challenging. Although numerical computation-based iterative methods such as the minimal mean square error (MMSE) and the alternative manifold optimization...

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Bibliographic Details
Main Authors: Rafid Umayer Murshed, Zulqarnain Bin Ashraf, Abu Horaira Hridhon, Kumudu Munasinghe, Abbas Jamalipour, Md. Farhad Hossain
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
6G
CNN
hybrid beamforming
LSTM
UM-MIMO
Online Access:https://ieeexplore.ieee.org/document/10098778/

Internet

https://ieeexplore.ieee.org/document/10098778/

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