Beam Prediction
1개 벤치마크 · 논문 69편 · 이 태스크의 논문 보기 →
Benchmarks
MVX
Most implemented
GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication
ProtoBeam: Generalizing Deep Beam Prediction to Unseen Antennas using Prototypical Networks
Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration
MVX-ViT: Multimodal Collaborative Perception for 6G V2X Network Management Decisions Using Vision Transformer.
Papers
Robust Beam Prediction for V2X Networks with Multi-Modal Sensing
Integrated sensing and communication (ISAC) provides a promising foundation for beam prediction in future vehicle-to-everything (V2X) networks. However, existing sensing-assisted beamforming methods still rely heavily on…
Beam PredictionWALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders
This paper proposes a multitask wireless foundation model via adaptive low-rank masked autoencoders (WALoMA), a unified multi-task foundation model for sixth-generation (6G) wireless physical layer architectures, to addr…
parameter-efficient fine-tuningBeam PredictionCFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models
Channel foundation models (CFMs) are commonly evaluated in model-specific pipelines that differ in data, radio configurations, partitions, adaptation procedures, task definitions, and metrics, preventing reproducible com…
Beam PredictionMeta-Transfer Learning for mmWave Beam Alignment
Millimeter-wave (mmWave) beam alignment plays a critical role in next-generation wireless systems, yet its efficient implementation remains challenging. Meta-learning and transfer learning have been explored to enable de…
Transfer LearningBeam PredictionQuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks
Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-assisted beam prediction is also limited because a beam index discards…
Beam PredictionLatentWave: JEPA Pretraining for Wireless Foundation Models
Wireless foundation models have emerged as a promising alternative to building separate models for each wireless task. However, existing approaches rely on masked input reconstruction, which can bias representations towa…
Beam Prediction