Energy-efficiency and sustainability are two important metrics for modern mobile communication technologies, and it is crucial to improve the power consumption of the components used in wireless communication hardware.
The power amplifier is one of the most power consuming components and its efficiency is essential to improve the overall energy consumption of the wireless communication hardware. The multicarrier waveforms utilized in modern networks are known to have high PAPR, which decreases the efficiency of the power amplifiers. Therefore, decreasing the PAPR of multicarrier waveforms is required to improve the energy-efficiency of the mobile networks.
Novel PAPR reduction solutions to exploit new features of 5G
Moreover, 5G technology has introduced some new features to improve the overall performance with respect to the older generations. Conventional PAPR reduction solutions are not compatible with these new 5G features, limiting the potential performance gains.
“In my thesis, I studied and designed novel PAPR reduction solutions exploiting new features of 5G to maximize the power amplifier efficiency. In addition, I investigated effective ways of utilizing machine learning techniques together with these new waveform solutions to further increase the performance gains", Gökceli says.
"As shown in the thesis with various performance results including real-world performance validation, these novel solutions promise important performance benefits for 5G and beyond mobile radio networks”, he continues.
Public defense on 24 May 2023
The doctoral dissertation of MSc. Selahattin Gökceli in the field of Communications Engineering entitled PAPR Reduction Solutions for 5G and Beyond will be publicly examined in the Faculty of Information Technology and Communication Sciences of Tampere University at Hervanta Campus, in the auditorium S2 of Sähkötalo building (Korkeakoulunkatu 3, Tampere) on Wednesday 24 of May 2023 at 12:15. The opponent will be Professor Antti Tölli from University of Oulu, Finland. The Custos will be Professor Mikko Valkama from Tampere University, Finland. The work has been co-supervised by Associate Professor Taneli Riihonen from Tampere University, and Doctor Toni Levanen from Tampere University.