Intelligent metasurface system for automatic tracking of moving targets and wireless communications based on computer...

Area of Science:

• Electromagnetic Engineering
• Wireless Communication Systems
• Artificial Intelligence in Communications

Background:

• Fifth-generation (5G) wireless communication demands advanced target tracking capabilities.
• Traditional antenna arrays face limitations in cost, complexity, and size for 5G applications.
• Digital programmable metasurfaces (DPMs) offer flexible electromagnetic wave control, presenting a potential solution.

Purpose of the Study:

• To develop an intelligent metasurface system for integrated target tracking and wireless communication.
• To leverage computer vision and artificial intelligence for enhanced radio environment awareness.
• To demonstrate a novel approach for self-adaptive wireless networks.

Main Methods:

• Utilized computer vision integrated with a convolutional neural network (CNN) for automatic detection and location identification of moving targets.
• Employed a dual-polarized digital programmable metasurface (DPM) coupled with a pre-trained artificial neural network (ANN) for smart beam tracking.
• Conducted experiments for moving target detection, radio-frequency signal detection, and real-time wireless communication.

Main Results:

• Successfully demonstrated the detection and identification of moving targets in real-time.
• Validated the system's capability for detecting radio-frequency signals.
• Achieved real-time wireless communication through intelligent beam tracking.

Conclusions:

• The proposed intelligent metasurface system integrates target identification, radio environment tracking, and wireless communication.
• This approach paves the way for intelligent wireless networks and self-adaptive systems in 5G and beyond.
• The DPM-based system offers a cost-effective, less complex, and smaller alternative to traditional antenna arrays for advanced wireless applications.