Optimization of Transmit Beamforming Using Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces-Reference-Cited by-同舟云学术

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Optimization of Transmit Beamforming Using Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces

Published:2024-05-27 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 21st International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)
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Author:

Kyaw Khin Thandar¹,Santipach Wiroonsak¹,Mamat Kritsada²,Kaemarungsi Kamol²,Fukawa Kazuhiko³

Affiliation:

1. Kasetsart University,Department of Electrical Engineering Faculty of Engineering,Bangkok,Thailand

2. National Science and Technology Development Agency,National Electronics and Computer Technology Center,Pathumthani,Thailand

3. School of Engineering Tokyo Institute of Technology,Department of Information and Communications Engineering,Tokyo,Japan

Funder

National Research Council of Thailand (NRCT)

National Science and Technology Development Agency (NSTDA)

Tokyo Institute of Technology

Faculty of Engineering, Kasetsart University (KU)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10594802/10594778/10595028.pdf?arnumber=10595028

Reference13 articles.

1. A Deep Learning Framework for Optimization of MISO Downlink Beamforming

2. Deep Learning Enabled Optimization of Downlink Beamforming Under Per-Antenna Power Constraints: Algorithms and Experimental Demonstration

3. Randomly-Directional Beamforming in Millimeter-Wave Multiuser MISO Downlink

4. Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

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

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