Recently, it was found that clipping can significantly improve the section error rate (SER) performance of sparse regression (SR) codes if an optimal clipping threshold is chosen. In this paper, we propose irregularly clipped SR codes, where multiple clipping thresholds are applied to symbols according to a distribution, to further improve the SER performance of SR codes. Orthogonal approximate message passing (OAMP) algorithm is used for decoding. Using state evolution, the distribution of irregular clipping thresholds is optimized to minimize the SER of OAMP decoding. As a result, optimized irregularly clipped SR codes achieve a better tradeoff between clipping distortion and noise distortion than regularly clipped SR codes. Numerical results demonstrate that irregularly clipped SR codes achieve 0.4 dB gain in signal-to-noise-ratio (SNR) over regularly clipped SR codes at code length$\,\approx2.5\!\times\! 10^4$ and SER$\,\approx10^{-5}$. We further show that irregularly clipped SR codes are robust over a wide range of code rates.

翻译：最近,人们发现,如果选择了最佳剪切阈值,剪切可显著提高稀释回归码的节误率(SER)性能。在本文中,我们建议不定期剪切SR码,根据分布对符号适用多剪切阈值,以进一步改进SR码的SER性能。使用OAMP(OAMP)光学近似电文传递算法解码。使用国家演进,不规则剪切阈值的分布最优化,以尽量减少OAMP解码的SER性能。因此,不定期剪切开的SR码在剪切除扭曲和噪声扭曲之间实现比定期剪切除SR码更好的交易。数字结果显示,不定期剪切的SR码在信号到噪音拉皮(SNRR)中取得0.4 dB收益,以代码的代码长度为0.4,\ approx2.5\\!\\time\! 10美元和SER$\\\ approx10-5美元。我们进一步表明,不定期剪剪切的SR码率超过宽的代码。