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Deep Learning for Predictive Beamforming by sima.sobhi70 is a document available to read on EtoBox.

What is Deep Learning for Predictive Beamforming about?

This paper presents a deep learning-based framework for predictive beamforming design in multiuser MISO systems, focusing on channel prediction and power optimization. The proposed method utilizes Long Short-Term Memory (LSTM) networks with an attention mechanism to enhance the accuracy of channel predictions based on historical data, thereby reducing overhead and improving spectrum efficiency. Simulation results demonstrate that this approach significantly outperforms traditional methods in terms of effect

Author

sima.sobhi70

Language

EN