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Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks

Chang Liu Xuemeng Liu Shuangyang Li Weijie Yuan Derrick Wing Kwan Ng

通信与信息网络学报（英文）2022，Vol.7Issue(3)：P.269-277,9.

Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks

Chang Liu ¹Xuemeng Liu ²Shuangyang Li ³Weijie Yuan ⁴Derrick Wing Kwan Ng¹

作者信息

1. School of Electrical Engineering and Telecommunications,the University of New South Wales,Sydney,NSW 2052,Australia
2. School of Electrical and Information Engineering,the University of Sydney,Sydney,NSW 2006,Australia
3. Department of Electrical,Electronic and Computer Engineering,the University of Western Australia,Perth WA 6009,Australia
4. Department of Electrical and Electronic Engineering,Southern University of Science and Technology,Shenzhen 518055,China
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摘要

关键词

integrated sensing and communication/predictive beamforming/deep learning/convolutional longshort term neural network/vehicular networks

分类

信息技术与安全科学

引用本文复制引用

Chang Liu,Xuemeng Liu,Shuangyang Li,Weijie Yuan,Derrick Wing Kwan Ng..Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks[J].通信与信息网络学报（英文）,2022,7(3):P.269-277,9.

基金项目

supported by the National Natural Science Foundation of China under Grant 61801082 （）

supported in part by the National Natural Science Foundation of China under Grant 62101232 （）

in part by the Guangdong Provincial Natural Science Foundation under Grant 2022A1515011257. （）

通信与信息网络学报（英文）

OACSCDEI

ISSN：2096-1081

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