Papers Beam Prediction
“Beam Prediction” 태그가 달린 논문 69편 · 필터 해제
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 PredictionStructure-Aware Multimodal LLM Framework for Trustworthy Near-Field Beam Prediction
In near-field extremely large-scale multiple-input multiple-output (XL-MIMO) systems, spherical wavefront propagation expands the traditional beam codebook into the joint angular-distance domain, rendering conventional b…
Beam PredictionAgentic AI for Embodied-enhanced Beam Prediction in Low-Altitude Economy Networks
Millimeter-wave or terahertz communications can meet demands of low-altitude economy networks for high-throughput sensing and real-time decision making. However, high-frequency characteristics of wireless channels result…
Beam PredictionDecision MakingFederated Learning-driven Beam Management in LEO 6G Non-Terrestrial Networks
Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) require efficient beam management under dynamic propagation conditions. This work investigates Federated Learning (FL)-based beam selection in LEO satellite constella…
Graph Neural NetworkFederated LearningBeam PredictionKnowledge Distillation for mmWave Beam Prediction Using Sub-6 GHz Channels
Beamforming in millimeter-wave (mmWave) high-mobility environments typically incurs substantial training overhead. While prior studies suggest that sub-6 GHz channels can be exploited to predict optimal mmWave beams, exi…
Knowledge DistillationBeam PredictionWireless Dataset Similarity: Measuring Distances in Supervised and Unsupervised Machine Learning
This paper introduces a task- and model-aware framework for measuring similarity between wireless datasets, enabling applications such as dataset selection/augmentation, simulation-to-real (sim2real) comparison, task-spe…
Synthetic Data GenerationBeam PredictionEmpower Low-Altitude Economy: A Reliability-Aware Dynamic Weighting Allocation for Multi-modal UAV Beam Prediction
The low-altitude economy (LAE) is rapidly expanding driven by urban air mobility, logistics drones, and aerial sensing, while fast and accurate beam prediction in uncrewed aerial vehicles (UAVs) communications is crucial…
Contrastive LearningBeam PredictionQuantum Intelligence Meets BD-RIS-Enabled AmBC: Challenges, Opportunities, and Practical Insights
A beyond-diagonal reconfigurable intelligent surface (BD-RIS) is an innovative type of reconfigurable intelligent surface (RIS) that has recently been proposed and is considered a revolutionary advancement in wave manipu…
Beam PredictionAutoencoder for Position-Assisted Beam Prediction in mmWave ISAC Systems
Integrated sensing and communication and millimeter wave (mmWave) have emerged as pivotal technologies for 6G networks. However, the narrow nature of mmWave beams requires precise alignments that typically necessitate la…
Dimensionality ReductionBeam PredictionCAR-BRAINet: Sub-6GHz Aided Spatial Adaptive Beam Prediction with Multi Head Attention for Heterogeneous Vehicular Networks
Heterogeneous Vehicular Networks (HetVNets) play a key role by stacking different communication technologies such as sub-6GHz, mm-wave and DSRC to meet diverse connectivity needs of 5G/B5G vehicular networks. HetVNet hel…
Beam PredictionCausal Beam Selection for Reliable Initial Access in AI-driven Beam Management
Efficient and reliable beam alignment is a critical requirement for mmWave multiple-input multiple-output (MIMO) systems, especially in 6G and beyond, where communication must be fast, adaptive, and resilient to real-wor…
Beam PredictionDigital Twin-Assisted Explainable AI for Robust Beam Prediction in mmWave MIMO Systems
In line with the AI-native 6G vision, explainability and robustness are crucial for building trust and ensuring reliable performance in millimeter-wave (mmWave) systems. Efficient beam alignment is essential for initial …
Transfer LearningOutlier DetectionDecision MakingBeam PredictionOut-of-Band Modality Synergy Based Multi-User Beam Prediction and Proactive BS Selection with Zero Pilot Overhead
Multi-user millimeter-wave communication relies on narrow beams and dense cell deployments to ensure reliable connectivity. However, tracking optimal beams for multiple mobile users across multiple base stations (BSs) re…
Beam PredictionManagementM2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models
This paper introduces a novel neural network framework called M2BeamLLM for beam prediction in millimeter-wave (mmWave) massive multi-input multi-output (mMIMO) communication systems. M2BeamLLM integrates multi-modal sen…
Beam PredictionDiversityPredictionIQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G
Foundational models have shown remarkable potential in natural language processing and computer vision, yet remain in their infancy in wireless communications. While a few efforts have explored image-based modalities suc…
Beam PredictionMulti-Task LearningSelf-Supervised Learning