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Beam Prediction

The beam prediction task involves determining the optimal beam or set of beams to use for signal transmission between a base station and a user device. Beam prediction is crucial in millimeter-wave (mmWave) and massive MIMO systems, where highly directional beams are used to overcome signal attenuation and ensure high data rates. The goal is to predict the most suitable beam(s) based on environmental factors, user location, and historical signal data, without exhaustive search over all possible beams, which can be computationally intensive.

Papers

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Showing 26–50 of 52 papers

TitleStatusHype
Model-based Deep Learning for Beam Prediction based on a Channel Chart—0
Joint Sensing and Communication Optimization in Target-Mounted STARS-Assisted Vehicular Networks: A MADRL Approach—0
A Low-Complexity Machine Learning Design for mmWave Beam Prediction—0
Uncertainty Aware Deep Learning for Particle Accelerators—0
Multimodal Transformers for Wireless Communications: A Case Study in Beam PredictionCode1
Vehicle Cameras Guide mmWave Beams: Approach and Real-World V2V Demonstration—0
Camera Based mmWave Beam Prediction: Towards Multi-Candidate Real-World Scenarios—0
Deep Regularized Waveform Learning for Beam Prediction With Limited Samples in Non-Cooperative mmWave SystemsCode0
Digital Twin Based Beam Prediction: Can we Train in the Digital World and Deploy in Reality?Code0
Environment Semantics Aided Wireless Communications: A Case Study of mmWave Beam Prediction and Blockage Prediction—0
Millimeter Wave Drones with Cameras: Computer Vision Aided Wireless Beam Prediction—0
How to Define the Propagation Environment Semantics and Its Application in Scatterer-Based Beam Prediction—0
Multi-Modal Beam Prediction Challenge 2022: Towards Generalization—0
Towards Real-World 6G Drone Communication: Position and Camera Aided Beam Prediction—0
Position Aided Beam Prediction in the Real World: How Useful GPS Locations Actually Are?Code1
LiDAR Aided Future Beam Prediction in Real-World Millimeter Wave V2I CommunicationsCode1
Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systems—0
Radar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World DemonstrationCode1
Vision-Position Multi-Modal Beam Prediction Using Real Millimeter Wave DatasetsCode1
Vision-Aided Beam Tracking: Explore the Proper Use of Camera Images with Deep Learning—0
Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction—0
Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G and Beyond—0
Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case—0
Deep Learning for Fast and Reliable Initial Access in AI-Driven 6G mmWave Networks—0
Deep Learning Assisted mmWave Beam Prediction with Prior Low-frequency Information—0
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