Zobrazeno 1 - 10
of 2 321
pro vyhledávání: '"ZHOU, Haibo"'
Autor:
Wang, Liangzhi, Zhang, Jie, Gao, Yuan, Zhang, Jiliang, Wei, Guiyi, Zhou, Haibo, Zhuge, Bin, Zhang, Zitian
In this paper, we propose a novel meta-learning based hyper-parameter optimization framework for wireless network traffic prediction models. An attention-based deep neural network (ADNN) is adopted as the prediction model, i.e., base-learner, for eac
Externí odkaz:
http://arxiv.org/abs/2409.14535
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 and data mining of vehicular network data, such as driving speeds and
Externí odkaz:
http://arxiv.org/abs/2407.08558
Autor:
Xue, Jianzhe, Yuan, Dongcheng, Sun, Yu, Zhang, Tianqi, Xu, Wenchao, Zhou, Haibo, Xuemin, Shen
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 intelligent transportation systems (ITS). By utilizing only a portion of IoV d
Externí odkaz:
http://arxiv.org/abs/2407.08047
Autor:
Xue, Jianzhe, Xu, Yunting, Yuan, Dongcheng, Zha, Caoyi, Du, Hongyang, Zhou, Haibo, Niyato, Dusit
Traffic flow estimation (TFE) is crucial for intelligent transportation systems. Traditional TFE methods rely on extensive road sensor networks and typically incur significant costs. Sparse mobile crowdsensing enables a cost-effective alternative by
Externí odkaz:
http://arxiv.org/abs/2407.08034
Autor:
Wang, Jiacheng, Du, Hongyang, Sun, Geng, Kang, Jiawen, Zhou, Haibo, Niyato, Dusit, Chen, Jiming
Integrated Sensing and Communications (ISAC) is one of the core technologies of 6G, which combines sensing and communication functions into a single system. However, limited computing and storage resources make it impractical to combine multiple sens
Externí odkaz:
http://arxiv.org/abs/2406.00408
Publikováno v:
2023 International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2023: 815-820
With the increasing of connected vehicles in the fifth-generation mobile communication networks (5G) and beyond 5G (B5G), ensuring the reliable and high-speed cellular vehicle-to-everything (C-V2X) communication has posed significant challenges due t
Externí odkaz:
http://arxiv.org/abs/2405.16777
In communications theory, the capacity of multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems is fundamentally determined by wireless channels, which exhibit both diversity and correlation in spatial, frequen
Externí odkaz:
http://arxiv.org/abs/2407.07702
Publikováno v:
Jiao L, Yu K, Chen J, et al. Performance Analysis of Uplink/Downlink Decoupled Access in Cellular-V2X Networks[J]. IEEE Transactions on Mobile Computing, 2023
This paper firstly develops an analytical framework to investigate the performance of uplink (UL) / downlink (DL) decoupled access in cellular vehicle-to-everything (C-V2X) networks, in which a vehicle's UL/DL can be connected to different macro/smal
Externí odkaz:
http://arxiv.org/abs/2405.06339
Autor:
Wang, Jiacheng, Liu, Yinqiu, Du, Hongyang, Niyato, Dusit, Kang, Jiawen, Zhou, Haibo, Kim, Dong In
In wireless communications, transforming network into graphs and processing them using deep learning models, such as Graph Neural Networks (GNNs), is one of the mainstream network optimization approaches. While effective, the generative AI (GAI) show
Externí odkaz:
http://arxiv.org/abs/2405.04907
Autor:
Zheng, Chunyan, Sun, Keke, Zhao, Wenhao, Zhou, Haibo, Jiang, Lixin, Song, Shaoyang, Zhou, Chunlai
Large pretrained language models (LLMs) have shown surprising In-Context Learning (ICL) ability. An important application in deploying large language models is to augment LLMs with a private database for some specific task. The main problem with this
Externí odkaz:
http://arxiv.org/abs/2405.04032