šØāš¬ Bio Summary:
Ahlem Arfaoui is a researcher specializing in Robotics, Computer Science, and Communication Systems. She holds a Master’s degree in Robotics, Computer Science, and Communication Systems from ISTIC, Borj Cedriya. Her research focuses on machine learning for improving the performance of massive MIMO systems in the presence of hardware imperfections. Ahlem has presented at conferences like IWCMC and ISCC and has published in journals like IEEE Systems Journal and IET Communications
š Education:
Ahlem Arfaoui holds a Master’s degree in Robotics, Computer Science, and Communication Systems from ISTIC, Borj Cedriya, which she completed in 2022. Prior to this, she earned her Bachelor’s degree in Computer Science from the same institution in 2019, preceded by a high school diploma in Computer Science from Hay Hayat, Sidi Bourouis Seliana in 2015.
š¼ Professional Experience:
Arfaoui has gained valuable teaching experience, having served as a teaching assistant at the Faculty of Sciences of Tunis (FST) and currently holding a teaching position at the private university of Technology and Engineering (TEK-UP). Her responsibilities include conducting courses on various subjects including C++, Java, UML, and Java Enterprise Edition (JEE). Additionally, she has completed internships at renowned companies such as ATB and SaGeMCOM, where she worked on mobile application development and gained exposure to real-world projects.
š Research Focus:
Arfaoui’s research interests lie in the intersection of machine learning and communication systems, particularly in the application of novel methods for improving the performance of massive MIMO systems in the presence of hardware imperfections. Her work involves developing end-to-end approaches and deep learning techniques to address challenges such as PA nonlinearities and DAC efficiency.
š Honors & Awards:
Arfaoui has received recognition for her contributions to the field, including presentations at prestigious conferences such as IWCMC and ISCC. Her research has been published in respected journals like IEEE Systems Journal and IET Communications, demonstrating her dedication to advancing knowledge in her field.
š Publications & Contributions:
End-to-End Deep Learning for Multipair Two-Way Massive MIMO with PA Impairments (IEEE Systems Journal, 2023): This paper explores the use of end-to-end deep learning techniques to improve the performance of multipair two-way massive MIMO systems in the presence of power amplifier impairments.
End-To-End Deep Learning assisted by Reconfigurable Intelligent Surface for uplink MU massive MIMO under PA Non-Linearities (Proceedings – IEEE Symposium on Computers and Communications, 2023): This paper discusses the application of deep learning assisted by reconfigurable intelligent surfaces to enhance the uplink performance of MU massive MIMO systems under power amplifier non-linearities.
Analysis of One-Bit DAC for RIS-Assisted MU Massive MIMO Systems with Efficient Autoencoder Based Deep Learning (Proceedings – IEEE Symposium on Computers and Communications, 2023): This paper presents an analysis of one-bit digital-to-analog converters (DACs) for RIS-assisted MU massive MIMO systems using efficient autoencoder-based deep learning techniques.
Autoencoder-based deep learning for massive multiple-input multiple-output uplink under high-power amplifier non-linearities (IET Communications, 2023): This article discusses the use of autoencoder-based deep learning methods to mitigate the effects of high-power amplifier non-linearities in massive MIMO uplink transmission.
End-to-end approach for MU massive MIMO uplink transmission under 1-bit ADC (2022 International Wireless Communications and Mobile Computing, IWCMC 2022): This paper presents an end-to-end approach for MU massive MIMO uplink transmission using 1-bit analog-to-digital converters (ADCs).
š Author Metrics:
Arfaoui’s research output is not only prolific but also impactful, as evidenced by her author metrics. Her papers have been cited in reputable journals and conferences, indicating the relevance and significance of her research within the academic community.
ā³ Research Timeline:
Arfaoui’s journey in research and academia has been marked by consistent growth and achievement. Starting from her undergraduate studies, she has steadily progressed through internships, teaching positions, and research projects, culminating in her current role as a respected researcher and educator in the field of robotics, computer science, and communication systems.