A Versatile PAPR Reduction Algorithm for 5G Waveforms with Guaranteed Performance

摘要

Peak-to-Average Power Ratio is a known issue of multicarrier waveforms. As the research on waveform design beyond OFDM is boosted, the PAPR problem has regained attention as a major bottleneck, particularly in spatial multiplexing schemes. In this paper a high-performance and flexible algorithm is proposed inspired by concentration of measure concept. The algorithm is analytically tractable thanks to concentration inequalities as a key element in this work. The performance is guaranteed with rather sharp bounds in a novel way. The PAPR reduction performance of the method for FBMC-OQAM signal model has no degradation comparing to OFDM.