Drone Attitude and Position Prediction via Stacked Hybrid Deep Learning Model for Massive MIMO Applications

Drone Attitude and Position Prediction via Stacked Hybrid Deep Learning Model for Massive MIMO Applications

This paper presents a novel stacked hybrid deep learning model for real-time prediction of drone attitude and position, specifically designed to support applications in massive Multiple-Input Multiple-Output (MIMO) systems. The proposed model integrates Long Short-Term Memory (LSTM) networks, autoen...

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Bibliographic Details
Main Author: Abdullah Al-Ahmadi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Drone attitude prediction
massive MIMO
deep learning
LSTM
autoencoder
attention mechanism
Online Access:https://ieeexplore.ieee.org/document/10795165/
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https://ieeexplore.ieee.org/document/10795165/

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