PhD project: AI-Driven Power Amplifier Linearization on FPGA for 6G and Industrial Wireless
The next generation of wireless communication systems, including 6G networks and Industrial Wireless technologies, will require highly efficient, intelligent, and energy-aware radio frequency (RF) hardware capable of supporting ultra-high data rates, massive connectivity, and low-latency communication. Power amplifiers (PAs) are among the most critical and power-hungry components in wireless transmitters. However, their nonlinear behaviour can introduce signal distortion, reduce spectral efficiency, and increase energy consumption.
This PhD project aims to investigate Artificial Intelligence (AI)-driven techniques for real-time power amplifier linearization using Field Programmable Gate Array (FPGA) platforms. The research will focus on the development of intelligent Digital Predistortion (DPD) algorithms capable of compensating for nonlinear PA characteristics under dynamic operating conditions. Advanced machine learning and neural network approaches will be explored to improve linearization performance while reducing computational complexity and power consumption.
The project will involve the modelling and characterization of RF power amplifiers, development of AI-based linearization algorithms, FPGA implementation and optimisation, and performance evaluation using modern wireless communication signals relevant to 5G, 6G, and industrial wireless applications. The research may also investigate adaptive and self-learning architectures capable of operating in changing environments and supporting future cognitive radio systems.
This project aligns with global research priorities in next-generation communications, energy-efficient electronics, intelligent RF systems, and industrial digitalisation. The outcomes are expected to contribute to the development of greener wireless networks and advanced industrial communication infrastructures.
The successful candidate will gain expertise in RF engineering, Artificial Intelligence, FPGA design, digital signal processing, wireless communications, and embedded systems. The project is expected to generate multiple high-quality journal and conference publications and provide opportunities for collaboration with academic and industrial research partners.
supervisor
https://www.tudublin.ie/explore/faculties-and-schools/engineering-built-environment/electrical-and-electronic-engineering/people/academic-staff/somayeh-mohammady.php
The next generation of wireless communication systems, including 6G networks and Industrial Wireless technologies, will require highly efficient, intelligent, and energy-aware radio frequency (RF) hardware capable of supporting ultra-high data rates, massive connectivity, and low-latency communication. Power amplifiers (PAs) are among the most critical and power-hungry components in wireless transmitters. However, their nonlinear behaviour can introduce signal distortion, reduce spectral efficiency, and increase energy consumption.
This PhD project aims to investigate Artificial Intelligence (AI)-driven techniques for real-time power amplifier linearization using Field Programmable Gate Array (FPGA) platforms. The research will focus on the development of intelligent Digital Predistortion (DPD) algorithms capable of compensating for nonlinear PA characteristics under dynamic operating conditions. Advanced machine learning and neural network approaches will be explored to improve linearization performance while reducing computational complexity and power consumption.
The project will involve the modelling and characterization of RF power amplifiers, development of AI-based linearization algorithms, FPGA implementation and optimisation, and performance evaluation using modern wireless communication signals relevant to 5G, 6G, and industrial wireless applications. The research may also investigate adaptive and self-learning architectures capable of operating in changing environments and supporting future cognitive radio systems.
This project aligns with global research priorities in next-generation communications, energy-efficient electronics, intelligent RF systems, and industrial digitalisation. The outcomes are expected to contribute to the development of greener wireless networks and advanced industrial communication infrastructures.
The successful candidate will gain expertise in RF engineering, Artificial Intelligence, FPGA design, digital signal processing, wireless communications, and embedded systems. The project is expected to generate multiple high-quality journal and conference publications and provide opportunities for collaboration with academic and industrial research partners.
supervisor
https://www.tudublin.ie/explore/faculties-and-schools/engineering-built-environment/electrical-and-electronic-engineering/people/academic-staff/somayeh-mohammady.php
