PhD in AI-Driven Power Amplifier Linearization on FPGA for 6G and Industrial Wireless

Explore AI-driven FPGA solutions for real-time power amplifier linearization to advance 6G and industrial wireless technologies.

Best for:Best for candidates with a strong background in RF engineering, AI, FPGA design, and digital signal processing, seeking to contribute to next-generation wireless communication technologies.

Technological University Dublin · Dublin, Ireland · R1 · First-stage researcher

More professors at Technological University Dublin

AI-driven power amplifier linearizationFPGA-based digital signal processingDigital Predistortion (DPD) algorithmsEnergy-efficient wireless communication systems6G and industrial wireless technologiesReal-time RF system optimization

Deadline

Dec 24, 2026

70 days

Funding

Stipend

Self-funded (fees and materials to be paid by the student)

Start date

Flexible (to be negotiated)

Temporary

Location

Dublin

Ireland

Overview

This PhD project at Technological University Dublin focuses on developing AI-driven techniques for real-time power amplifier linearization using FPGA platforms. The research aims to address nonlinear behavior in power amplifiers, which causes signal distortion, reduces spectral efficiency, and increases energy consumption in next-generation wireless systems. The successful candidate will model RF power amplifiers, design AI-based Digital Predistortion (DPD) algorithms, implement and optimize these algorithms on FPGAs, and evaluate performance using modern wireless communication signals. The project aligns with global priorities in energy-efficient electronics, intelligent RF systems, and industrial digitalization, with potential contributions to greener wireless networks and advanced industrial communication infrastructures.

AI in wireless communicationsFPGA implementationDigital PredistortionPower amplifier linearization6G technologyIndustrial wirelessEnergy-efficient electronicsMachine learning for RF systems

What you'll do

Develop AI-driven Digital Predistortion (DPD) algorithms to compensate for nonlinearities in power amplifiers under dynamic conditions.
Model and characterize RF power amplifiers to inform algorithm design and optimization.
Implement and optimize DPD algorithms on FPGA platforms for real-time performance evaluation.
Evaluate system performance using modern wireless communication signals relevant to 5G, 6G, and industrial wireless applications.
Investigate adaptive and self-learning architectures for operation in changing environments and cognitive radio systems.
Collaborate with academic and industrial research partners to advance the project outcomes.
Publish high-quality research findings in leading journals and conferences.

Requirements

Degree required: Bachelor's degree or equivalent in Electrical Engineering, Electronic Engineering, Computer Engineering, or a related field

Degree offered: PhD

Language: English; Good proficiency

Instruction: English

Required skills

Strong background in RF engineering and digital signal processing
Experience with FPGA design and implementation
Knowledge of machine learning and neural network algorithms
Proficiency in wireless communication systems and signal processing techniques

Nice to have

Experience with AI-driven hardware optimizationFamiliarity with 5G/6G wireless standards and industrial wireless technologiesProgramming skills in Python, MATLAB, or similar tools

Eligibility

No specific nationality or residency restrictions mentioned
No age or prior experience caps specified

Funding & terms

Type

Stipend

Amount

Self-funded (fees and materials to be paid by the student)

Duration

Unknown (typically 3-4 years for PhD)

Programme

Student self-funded

How to apply

Deadline: 2026-12-24 (Europe/Dublin)

Interested candidates must complete an Expression of Interest form available via the provided link. Ensure your application includes all necessary details and documents to be considered for this PhD project.

Documents required