DOI
https://doi.org/10.25772/CV5W-7C45
Defense Date
2025
Document Type
Thesis
Degree Name
Master of Science
Department
Electrical & Computer Engineering
First Advisor
Dr. Yanxiao Zhao
Second Advisor
Dr. Ruixin Niu
Third Advisor
Dr. Changqing Luo
Abstract
Intelligent Reflecting Surfaces (IRSs) are transforming next-generation wireless networks by enabling dynamic control of the propagation environment for improved localization and security. This thesis advances Angle-of-Arrival (AoA) and distance estimation in IRS-assisted systems using a hybrid architecture with active sensing and passive reflecting elements. A modified MUSIC algorithm, optimized for near-field localization, decouples 2‑D AoA and 1‑D range estimation using a grid-and-peak pseudo-spectrum scan, achieving sub-degree AoA (0.003 rad) and sub-meter range (0.05 m) accuracy with over 100× lower complexity than classical 3D MUSIC.
The study further applies the algorithm to the DeepMIMO dataset (O1_28 scenario, 3.5 GHz) using hybrid IRSs with varying active elements (M = 10×10, 15×15, 18×18), achieving improved accuracy (0.06 rad AoA, ≃0.03 m range) and 90% signal classification. Phase shifts of the 25×25 passive arrays are optimized to maximize SINR (20 dB), enhancing secure communication.
To refine estimates, two Convolutional Neural Networks (CNNs) are developed: RefineNet, which improves MUSIC-based AoA and range estimation to achieve centimeter-level accuracy, and ElementNet, which optimizes the number and placement of active IRS elements (M = 4), reducing hardware costs while maintaining high accuracy. These methods enable 100% classification of legitimate versus malicious signals using the Hungarian algorithm.
In summary, this work validates the modified MUSIC algorithm, extends its application to realistic channels, and integrates deep learning to achieve high-precision localization, secure communication, and cost-efficient IRS configurations.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
8-4-2025