Continuous-Time mmWave Beam Prediction With ODE-LSTM Learning Architecture-Reference-Cited by-同舟云学术

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Continuous-Time mmWave Beam Prediction With ODE-LSTM Learning Architecture

Published:2023-01 Issue:1 Volume:12 Page:187-191
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Ma Ke¹^ORCID,Zhang Fan¹^ORCID,Tian Wenqiang²^ORCID,Wang Zhaocheng¹^ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University, Beijing, China

2. Department of Standardization, OPPO Research Institute, Beijing, China

Funder

National Key Research and Development Program of China

OPPO Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/10008400/09944873.pdf?arnumber=9944873

Reference19 articles.

1. Learning long-term dependencies in irregularly-sampled time series;lechner;arXiv 2006 04418,2020

2. Latent ODEs for irregularly-sampled time series;rubanova;Proc NeurIPS,2019

3. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc ICML,2015

4. A Statistical Model for Indoor Multipath Propagation

5. Neural ordinary differential equations;chen;Proc NeurIPS,2018

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Low Overhead Beam Alignment for Mobile Millimeter Channel Based on Continuous-Time Prediction;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

2. Beam prediction and tracking mechanism with enhanced LSTM for mmWave aerial base station;Wireless Networks;2024-02-16

3. Multimodal Fusion Assisted Mmwave Beam Training in Dual-Model Networks;IEEE Transactions on Vehicular Technology;2024-01

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