Journal of Signal Processing Systems
Selected mapping without side information for PAPR reduction in OFDM
IEEE Transactions on Wireless Communications
Scaled SLM for PAPR reduction of OFDM signal in impulsive noise channel
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 1
Asymptotic performance analysis and successive selected mapping for PAR reduction in OFDM
IEEE Transactions on Signal Processing
A polynomial phasing scheme to realize minimum crest factor for multicarrier transmission
WTS'10 Proceedings of the 9th conference on Wireless telecommunications symposium
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
PAPR reduction of OFDM using PTS and error-correcting code subblocking
IEEE Transactions on Wireless Communications
Comparison of selected mapping and partial transmit sequence for crest factor reduction in OFDM
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
IEEE Communications Letters
Two new phase sequence sets for PAPR reduction in SLM-OFDM systems without side information
Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief
SER analysis of PTS based techniques for PAPR reduction in OFDM systems
Digital Signal Processing
International Journal of Wireless and Mobile Computing
Generalized M-2M Mapping Scheme for SLM and PTS Based OFDM Systems Without Side-Information
Wireless Personal Communications: An International Journal
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Selected mapping (SLM) and partial transmit sequence (PTS) are well-known techniques for peak-power reduction in orthogonal frequency-division multiplexing (OFDM). We derive a simplified maximum likelihood (ML) decoder for SLM and PTS that operates without side information. This decoder exploits the fact that the modulation symbols belong to a given constellation and that the multiple signals generated by the PTS or SLM processes are widely different in a Hamming distance sense. Pairwise error probability (PEP) analysis suggests how SLM and PTS vectors should be chosen. The decoder performs well over additive white Gaussian noise (AWGN) channels, fading channels, and amplifier nonlinearities.