Constellation shaping for non-uniform signals based on truncated Gaussian distribution

We study the signal shaping based on the truncated Gaussian distribution. Since the possibility of reducing peak-to-average power ratio (PAPR) by the previous study with clipped Gaussian signal constellation is limited, we study PAPR reduction for one-dimensional signal constellation using the truncated Gaussian distribution. From the numerical results, we show that achievable rate of the truncated Gaussian distribution is larger than that of the clipped Gaussian signal constellation for wide range of SNR, while keeping the expansion of PAPR small. Moreover it is quite close to the uniform signal constellation for high SNR.