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

Research article (Journal of Communications and Information Networks, 2022) · cited 24× · AI/ML
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Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks

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Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks is a scholarly article[1].

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  • Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-clstm-for-predictive-beamforming-in-integrated-sensing-and-communication-enabled-vehicular-networks
MLA “Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-clstm-for-predictive-beamforming-in-integrated-sensing-and-communication-enabled-vehicular-networks.
BibTeX @misc{4ortxyz_deep-clstm-for-predictive-beamforming-in-integrated-sensing-and-communication-enabled-vehicular-networks_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks}}, year = {2026}, url = {https://4ort.xyz/entity/deep-clstm-for-predictive-beamforming-in-integrated-sensing-and-communication-enabled-vehicular-networks}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks — https://4ort.xyz/entity/deep-clstm-for-predictive-beamforming-in-integrated-sensing-and-communication-enabled-vehicular-networks (retrieved 2026-05-24)

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