5 papers
Segment-Wise Flow Matching for Vision-Aided mmWave V2I Beam Prediction
Can Zheng, Jiguang He, Chung G. Kang +3
This paper proposes a vision-conditioned flow matching (FM) framework for beam prediction in millimeter-wave vehicle-to-infrastructure links. Instead of modeling discrete beam-inde…
Multimodal Radio and Vision Fusion for Robust Localization in Urban V2I Communications
Can Zheng, Jiguang He, Chung G. Kang +2
Accurate localization is critical for vehicle-to-infrastructure (V2I) communication systems, especially in urban areas where GPS signals are often obstructed by tall buildings, lea…
A Variational Bayesian Detector for Affine Frequency Division Multiplexing
Can Zheng, Chung G. Kang
This paper proposes a variational Bayesian (VB) detector for affine frequency division multiplexing (AFDM) systems. The proposed method estimates the symbol probability distributio…
BeamLLM: Vision-Empowered mmWave Beam Prediction with Large Language Models
Can Zheng, Jiguang He, Guofa Cai +2
In this paper, we propose BeamLLM, a vision-aided millimeter-wave (mmWave) beam prediction framework leveraging large language models (LLMs) to address the challenges of high train…
M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models
Can Zheng, Jiguang He, Chung G. Kang +3
This paper introduces a novel neural network framework called M2BeamLLM for beam prediction in millimeter-wave (mmWave) massive multi-input multi-output (mMIMO) communication syste…