5 papers
Large AI Model for Delay-Doppler Domain Channel Prediction in 6G OTFS-Based Vehicular Networks
Jianzhe Xue, Dongcheng Yuan, Zhanxi Ma +4
Channel prediction is crucial for high-mobility vehicular networks, as it enables the anticipation of future channel conditions and the proactive adjustment of communication strate…
Hyper-parameter Optimization for Wireless Network Traffic Prediction Models with A Novel Meta-Learning Framework
Liangzhi Wang, Jie Zhang, Yuan Gao +5
This paper proposes a novel meta-learning based hyper-parameter optimization framework for wireless network traffic prediction (NTP) models. The primary objective is to accumulate…
Spatial-Temporal Attention Model for Traffic State Estimation with Sparse Internet of Vehicles
Jianzhe Xue, Dongcheng Yuan, Yu Sun +5
The growing number of connected vehicles offers an opportunity to leverage internet of vehicles (IoV) data for traffic state estimation (TSE) which plays a crucial role in intellig…
ST-Mamba: Spatial-Temporal Mamba for Traffic Flow Estimation Recovery using Limited Data
Doncheng Yuan, Jianzhe Xue, Jinshan Su +2
Traffic flow estimation (TFE) is crucial for urban intelligent traffic systems. While traditional on-road detectors are hindered by limited coverage and high costs, cloud computing…
Spatial-Temporal Generative AI for Traffic Flow Estimation with Sparse Data of Connected Vehicles
Jianzhe Xue, Yunting Xu, Dongcheng Yuan +4
Traffic flow estimation (TFE) is crucial for intelligent transportation systems. Traditional TFE methods rely on extensive road sensor networks and typically incur significant cost…