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 41–50 of 52 papers

TitleStatusHype
5G-Advanced AI/ML Beam Management: Performance Evaluation with Integrated ML Models—0
ViT LoS V2X: Vision Transformers for Environment-aware LoS Blockage Prediction for 6G Vehicular Networks—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
AI-Driven Mobility Management for High-Speed Railway Communications: Compressed Measurements and Proactive Handover—0
A Low-Complexity Machine Learning Design for mmWave Beam Prediction—0
BeamLLM: Vision-Empowered mmWave Beam Prediction with Large Language Models—0
Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systems—0
Beam Prediction based on Large Language Models—0
Beam Selection in ISAC using Contextual Bandit with Multi-modal Transformer and Transfer Learning—0
Show:102550
← PrevPage 5 of 6Next →

No leaderboard results yet.