Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Exponential growth in data rate demands has driven efforts to develop novel beamforming techniques for realizing massive multiple-input and multiple-output (MIMO) systems in sixth-generation (6G) terabits per second wireless communications. Existing beamforming techniques rely on conventional optimi...

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書目詳細資料
Main Authors:	Tan, Yi Ji, Zhu, Changyan, Tan, Thomas CaiWei, Kumar, Abhishek, Wong, Liang Jie, Chong, Yidong, Singh, Ranjan
其他作者:	School of Physical and Mathematical Sciences
格式:	Article
語言:	English
出版:	2022
主題:	Science::Physics Deep Reinforcement Learning Terahertz Beamforming Terahertz Time-Domain Spectroscopy
在線閱讀:	https://hdl.handle.net/10356/161695
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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