Progress on intelligent metasurfaces for signal relay, transmitter, and processor

Area of Science:

• Electrical Engineering
• Computer Science
• Materials Science

Background:

• High data rates in wireless communication strain limited spectral resources.
• Active node deployment for signal compensation incurs high costs and interference.
• Conventional methods passively adapt to the wireless environment.

Purpose of the Study:

• To provide a unified perspective on intelligent metasurfaces in wireless communication.
• To explore how intelligent metasurfaces can reshape the wireless environment.
• To review advancements and future directions of intelligent metasurfaces.

Main Methods:

• Modeling of wireless channels and metasurface evolution (passive, active, intelligent).
• Integration of deep learning algorithms for environmental adaptation.
• Overview of experimental advancements and practical implementation challenges.

Main Results:

• Intelligent metasurfaces can function as signal relays, transmitters, and processors.
• Deep learning enables autonomous adaptation to dynamic wireless environments.
• Experimental progress demonstrates the potential of intelligent metasurfaces.

Conclusions:

• Intelligent metasurfaces present a novel, energy-efficient paradigm for wireless communication.
• Key challenges in practical implementation include.
• Future research directions include gain metasurfaces and knowledge migration.