Enhanced Position-Aided Beam Prediction Using Real-World Data and Enhanced-Convolutional Neural Networks

Enhanced Position-Aided Beam Prediction Using Real-World Data and Enhanced-Convolutional Neural Networks

Millimeter-wave (mmWave) communication systems utilize narrow beamforming to ensure adequate signal power. However, beam alignment requires significant training overhead, especially in high-mobility scenarios. Previous research has utilized synthetic data for position-aided beam prediction, which do...

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Bibliographic Details
Main Authors: Ahmed Abd El Moaty Mohamed Gouda, Ehab K. I. Hamad, Aziza I. Hussein, M. Mourad Mabrook, A. A. Donkol
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Position-aided beam prediction
convolutional neural networks
millimeter-wave
Online Access:https://ieeexplore.ieee.org/document/10974954/
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https://ieeexplore.ieee.org/document/10974954/

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