en Machine Learning Machine Learning Research Paper Research Paper <span style="font-size:12pt"><span style="text-justify:inter-ideograph"><span new="" roman="" style="font-family:" times=""><span style="font-size:9.0pt">High peak-to-average power ratio (PAPR) has been a major drawback of Filter bank Multicarrier (FBMC) in the 5G system. This research aims to calculate the&nbsp;</span></span></span></span>PAPR<span style="font-size:12pt"><span style="text-justify:inter-ideograph"><span new="" roman="" style="font-family:" times=""><span style="font-size:9.0pt"> reduction associated with the FBMC system. This research uses four techniques to reduce PAPR. They are classical tone reservation (TR). It combines tone reservation with sliding window (SW-TR). It also combines them with active constellation extension (TRACE) and with deep learning (TR-Net). TR-net decreases the greatest PAPR reduction by around 8.6 dB compared to the original value.&nbsp;</span></span></span></span>This work significantly advances PAPR reduction in FBMC systems by proposing three hybrid methods, emphasizing the deep learning-based TRNet technique as a groundbreaking solution for efficient, distortion-free signal processing. Filter Bank Multi-Carrier (FBMC), Peak-to-Average Power Ratio (PAPR), Tone Reservation (TR), Sliding Window Tone Reservation (SW-TR), Offset Quadrature Amplitude Modulation (OQAM), Trace Detection (TRACE), Tone Reservation Neural Network (TRNet), Deep Lea 115 125 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-5356-2&slc_lang=en&sid=1 Mohamed Hussien Moharam mohamed.moharem@must.edu.eg 1800319475328460014914 1800319475328460014914 Yes Assistant Professor at Misr University for Science and Technology, Electronics and Communications Engineering Department, Giza, Egypt AYA W. wafik ayawaelwafik@gmail.com 1800319475328460014915 1800319475328460014915 No Cyber Security Engineer graduate from Misr University for Science and Technology, Electronics and Communications Engineering Department, Giza, Egypt.