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Extrapolated projection methods for PAPR reduction

: Fink, J.; Cavalcante, R.L.G.; Jung, P.; Stanczak, S.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society; European Association for Speech, Signal and Image Processing -EURASIP-:
26th European Signal Processing Conference, EUSIPCO 2018 : 3-7 September 2018, Roma, Italy
Piscataway, NJ: IEEE, 2018
ISBN: 978-9-0827-9701-5
ISBN: 978-90-827970-0-8
ISBN: 978-1-5386-3736-4
ISBN: 978-90-827970-1-5
European Signal Processing Conference (EUSIPCO) <26, 2018, Roma>
Conference Paper
Fraunhofer HHI ()

Over more than the last decade, there has been a significant effort in research to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. This effort has been mainly driven by the need for enhancing the efficiency of power amplifiers. In this paper, we formulate the PAPR reduction problem as a feasibility problem in a real Hilbert space, and provide algorithmic solutions based on extrapolated projection methods with suitably constructed constraint sets. This set-theoretic approach provides a high flexibility and includes various existing PAPR reduction techniques as special cases. In particular, it allows for balancing between the spectral efficiency and signal distortion on a symbol-to-symbol basis, while supporting arbitrary combinations of quadrature amplitude modulation (QAM) constellations. Moreover, we extend the proposed approach to reuse the phase of pilot subcarriers that are simultaneously used for channel estimation. Simulations show remarkable performance gains resulting from extrapolation, which makes it possible to achieve a considerable PAPR reduction in just a few iterations with low computational cost.