Date Approved

7-14-2025

Embargo Period

7-14-2026

Document Type

Dissertation

Degree Name

Ph.D. Electrical and Computer Engineering

Department

Electrical and Computer Engineering

College

Henry M. Rowan College of Engineering

Advisor

Ben Wu, Ph.D.

Committee Member 1

Jie Li, Ph.D.

Committee Member 2

Chen Shen, Ph.D.

Committee Member 3

Huaxia Wang, Ph.D.

Committee Member 4

Guimu Guo, Ph.D.

Abstract

This dissertation is centered on fast wideband interference management through advanced photonic signal processing and hybrid communication architectures. The core of this work is based on an optical pulse sampling technique proposed for photonic blind source separation (BSS) to recover wideband signals from their sub-Nyquist samples. With the use of ultra-short optical pulses to obtain statistically representative samples, this method retains important statistical properties of the signals while significantly reducing constraints imposed by analog to digital conversion and digital signal processing. Building on this foundation, we further apply the photonic BSS system within a hybrid free space optical (FSO) and radiofrequency (RF) multiple-input multiple-output (MIMO) communication platform for dynamic interference mitigation. The hybrid architecture dynamically switches between FSO and RF modes to adapt to varying environmental conditions. Additionally, this dissertation also leverages artificial intelligence algorithms in both optical communications and optical imaging area, combined with structured-light technology, galvo-mirror systems and passive sensing model to provide applications in medical and civil area, such as selective targeted ultraviolet disinfection system and microscopic three-dimensional reconstruction system.

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Available for download on Tuesday, July 14, 2026

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