5 papers
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…
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…
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…
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…
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…