collaborators

7 papers

eess.SP2026

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…

eess.SP2026

JEPA-MSAC: A Joint-Embedding Predictive Architecture for Multimodal Sensing-Assisted Communications

Can Zheng, Jiguang He, Guofa Cai +4

Future wireless systems increasingly require predictive and transferable representations that can support multiple physical-layer (PHY) tasks under dynamic environments. However, m…

cs.IT2025

Dual-Domain Deep Learning-Assisted NOMA-CSK Systems for Secure and Efficient Vehicular Communications

Tingting Huang, Jundong Chen, Huanqiang Zeng +2

Ensuring secure and efficient multi-user (MU) transmission is critical for vehicular communication systems. Chaos-based modulation schemes have garnered considerable interest due t…

eess.SP2025

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…

eess.SP2025

Design of A New Multiple-Chirp-Rate Index Modulation for LoRa Networks

Xiaobin Zhu, Minling Zhang, Guofa Cai +2

We propose a multiple chirp rate index modulation (MCR-IM) system based on Zadoff-Chu (ZC) sequences that overcomes the problems of low transmission rate and large-scale access in…

cs.LG2025

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…