PAPR reduction for LDPC coded OFDM systems using binary masks and optimal LLR estimation

A probabilistic PAPR reduction method using binary masks is proposed for OFDM systems. The binary masks are used to generate multiple signal candidates containing the same information. The candidate with the lowest PAPR is selected for transmission. In the presence of a non-linear amplifier (soft limiter), as the number of candidates increases, the PAPR is reduced, resulting in the reduction of clipping distortion power. Taking into account both distortion and channel noise, we derive the analytical total noise power to estimate the log-likelihood ratio (LLR), which is then used to enhance the decoding performance. We derive a minimum achievable Eb/N0 and a decoding threshold for LDPC codes in the presence of the soft limiter. Simulation results show that our LLR estimation improves the error performance, and multiple candidate system lowers the error rate.

► We provide a probabilistic PAPR reduction technique using binary masks.
► Based on the CCDF curve, we derive the amplitude PDF of the selected symbol.
► This amplitude PDF is used to obtain the distortion power due to the soft limiter.
► Using the distortion power, we calculate the optimal LLR.
► The optimal LLR enhances the soft decoding process and improves the error rates.