PAPR Analysis of 5G and B5G Waveforms Using Advanced PAPR Algorithms

The implementation of advanced waveforms will play an important role in enhancing the throughput, spectrum access, data rate, and capacity of the 5G and beyond 5G systems. High peak-to-average power ratio (PAPR) is a serious concern in advanced waveforms, which can drastically reduce the performance of the system. The primary objective of the proposed article is to analyze PAPR algorithms when applied to advanced waveforms. In this article, we analyze and compare the bit error rate (BER) and PAPR performance of advanced waveforms for different PAPR algorithms. The computer simulation results reveal that the deep learning method for nonorthogonal multiple access obtained a significant BER gain of 3.1 and 1.5 dB and a PAPR gain of 3.2 and 1.2 dB as compared with contemporary advanced waveforms.