SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 21–30 of 52 papers

TitleStatusHype
Illuminating the Path: Attention-Assisted Beamforming and Predictive Insights in 5G NR Systems—0
IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G—0
Joint Sensing and Communication Optimization in Target-Mounted STARS-Assisted Vehicular Networks: A MADRL Approach—0
M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models—0
Millimeter Wave Drones with Cameras: Computer Vision Aided Wireless Beam Prediction—0
Model-based Deep Learning for Beam Prediction based on a Channel Chart—0
Multi-Modal Beam Prediction Challenge 2022: Towards Generalization—0
Multimodal Deep Learning-Empowered Beam Prediction in Future THz ISAC Systems—0
Multi-Modal Large Models Based Beam Prediction: An Example Empowered by DeepSeek—0
Multi-Modal Transformer and Reinforcement Learning-based Beam Management—0
Show:102550
← PrevPage 3 of 6Next →

No leaderboard results yet.