Incident Power and Relative Phase Distribution Mapping in Reconfigurable Intelligent Surfaces Using Energy Harvesting

Overview

Drexel researchers have developed an innovative method for obtaining incident power and relative phase distribution across Reconfigurable Intelligent Surfaces (RISs). Four versions of a novel energy harvesting circuit have been developed to trade-off sensitivity versus circuit complexity. The sensitivity of these circuits can be greatly increased through the inclusion of direct current (DC) bias and radio frequency (RF) amplifiers. This technology holds potential to simplify the state-selection process and improve the real-time programmability of RISs.

This novel approach addresses several challenges facing RIS development and deployment. In addition to simplifying the state-selection problem in RISs, it facilitates faster processing as well as real-time programmability. It also eliminates the need for complicated radios and sensors across the RIS, reducing system cost and complexity.

Category:

Wireless Communications, Energy Harvesting, 6G Technologies

Applications

Enhanced wireless network performance with RISs
Improved energy efficiency and sensitivity of RF-DC conversion circuits for RIS applications
Next-generation 6G wireless systems
Advanced state-selection algorithms implementing machine learning

Advantages

Novel method for obtaining incident power and phase distribution
Integration of energy harvesting circuits simplifies the RIS state-selection process
Increased sensitivity of circuits through DC bias and RF amplifiers
Elevation of overall system sensitivity through a combination of DC and RF enhancements