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Related Experiment Video

Updated: Sep 11, 2025

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

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Heterogeneous-IRS-Assisted Millimeter-Wave Systems: Element Position and Phase Shift Optimization.

Weibiao Zhao¹, Qiucen Wu¹, Hao Wei²

¹Key Laboratory for Information Science of Electromagnetic Waves (MoE), School of Information Science and Technology, Fudan University, Shanghai 200433, China.

Sensors (Basel, Switzerland)

|August 14, 2025

Summary

This summary is machine-generated.

This study introduces a green heterogeneous intelligent reflecting surface (HE-IRS) with tunable elements. Optimized element placement and phase shifts enable competitive performance with significantly reduced power consumption for future networks.

Keywords:

Cauchy–Schwarz bound heterogeneous intelligent reflecting surface manifold optimization millimeter-wave system particle swarm optimization

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Last Updated: Sep 11, 2025

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Area of Science:

Wireless Communication
Metamaterials
Optimization Algorithms

Background:

Intelligent Reflecting Surfaces (IRSs) are crucial for future networks but face challenges in power consumption and cost due to numerous elements.
A novel green heterogeneous IRS (HE-IRS) integrates dynamically tunable elements (DTEs) and statically tunable elements (STEs) to mitigate these issues.
The unique HE-IRS structure necessitates new optimization strategies for element positioning and phase shifts.

Purpose of the Study:

To investigate and solve the element position and phase shift optimization problems in HE-IRS-assisted millimeter-wave systems.
To develop efficient algorithms for optimizing the configuration of DTEs and STEs within HE-IRS.
To demonstrate the performance benefits of the optimized HE-IRS compared to conventional IRS.

Main Methods:

Particle Swarm Optimization (PSO) algorithm for determining optimal DTE and STE positions.
Manifold optimization for phase shift optimization of STEs, coupled with a closed-form solution for DTE phase shifts.
A low-complexity phase shift optimization algorithm for both DTEs and STEs utilizing the Cauchy-Schwarz bound.

Main Results:

The proposed PSO algorithm effectively determines the optimal positions for DTEs and STEs.
The developed phase shift optimization methods achieve efficient configuration of the HE-IRS.
Simulation results confirm that the optimized HE-IRS achieves performance comparable to conventional IRS with substantially lower power consumption.

Conclusions:

The tailored element position and phase shift optimization algorithms are effective for HE-IRS.
HE-IRS offers a promising solution for energy-efficient communication networks.
This research contributes to the advancement of green communication technologies through optimized intelligent reflecting surfaces.