An Improved SLM Scheme with Superimposed Training Sequence for PAPR Reduction in OFDM System

Orthogonal Frequency Division Multiplexing (OFDM) technology has high spectrum efficiency and good anti-multipath interference capacity, but it has an inherent shortcoming that high peak-average power ratio (PAPR). Select Mapping (SLM) method is an effective algorithm to reduce Peak to Average Power Ratio (PAPR) of OFDM (Orthogonal Frequency Division Multiplexing) signal, and does not bring about any distortion of the signal. However, the biggest disadvantage of SLM method is that computational complexity is very large. In this paper, we propose a kind of improved SLM scheme which combines superimposed training sequence method, which using the a pre-set threshold method to select sub-optimization phase sequence as the phase factor in the procession of SLM method on signals. The simulation results show that the proposed scheme can not only effectively reduce the PAPR of system, not only reduce the computational complexity of the system, at the same time, there is no significant effect on system performance.