Deep Learning Based Decentralized Beamforming Methods for Multi-Antenna Interference Channels
Author:
Affiliation:
1. School of Electrical Engineering, Korea University, Seoul, South Korea
2. Department of Electrical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
Funder
National Research Foundation of Korea
Ministry of Science and ICT (MSIT), Korea Government
Institute of Information and Communications Technology Planning and Evaluation
MSIT
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10347192.pdf?arnumber=10347192
Reference42 articles.
1. An introduction to the multi-user MIMO downlink
2. Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design
3. Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure [Lecture Notes]
4. Competition Versus Cooperation on the MISO Interference Channel
5. Distributed Beamforming Techniques for Weighted Sum-Rate Maximization in MISO Interference Channels
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