Attention-Aided Autoencoder-Based Channel Prediction for Intelligent Reflecting Surface-Assisted Millimeter-Wave Communications-Reference-Cited by-同舟云学术

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Attention-Aided Autoencoder-Based Channel Prediction for Intelligent Reflecting Surface-Assisted Millimeter-Wave Communications

Published:2023-12 Issue:4 Volume:7 Page:1906-1919
ISSN:2473-2400
Container-title:IEEE Transactions on Green Communications and Networking
language:
Short-container-title:IEEE Trans. on Green Commun. Netw.

Author:

Chen Hong-Yunn¹^ORCID,Wu Meng-Hsun²,Yang Ta-Wei¹^ORCID,Huang Chih-Wei³^ORCID,Chou Cheng-Fu¹^ORCID

Affiliation:

1. Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan

2. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

3. Department of Communication Engineering, National Central University, Taoyuan, Taiwan

Funder

National Science and Technology Council, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Renewable Energy, Sustainability and the Environment

Link

http://xplorestaging.ieee.org/ielx7/7511293/10325381/10120965.pdf?arnumber=10120965

Reference47 articles.

1. Time-Varying Channel Prediction for RIS-Assisted MU-MISO Networks via Deep Learning

2. Autoregressive modeling for fading channel simulation

3. Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces

4. Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design

5. Autoencoder Neural Network Based Intelligent Hybrid Beamforming Design for mmWave Massive MIMO Systems

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1. Intelligent Reflecting Surface Enhanced Wireless Communications With MultiHead-Attention Sparse Autoencoder-Based Channel Prediction;IEEE Communications Letters;2023-10

2. Optimizing Mobility-Aware Task Offloading in Smart Healthcare for Internet of Medical Things Through Multi-Agent Reinforcement Learning;IEEE Internet of Things Journal;2023

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