不规则裁剪稀疏回归码
Irregularly Clipped Sparse Regression Codes
摘要：
近年来研究发现，如果选择一个最佳的限幅门限，限幅可以显著改善稀疏回归码的部分出错率性能。在本文中，我们提出了不规则限幅SR码，其中多个限幅阈值应用于符号根据一个分布，以进一步提高SR码的SER性能。解码采用正交近似消息传递（OAMP）算法。利用状态演化优化不规则限幅阈值的分布，以最小化OAMP解码的误码率性能。因此，优化的不规则削波SR码比规则削波SR码在削波失真和噪声失真之间实现了更好的折衷。数值结果表明，在码长为$\,\approx2.5\!\times\! 10^4$和SER为$\,\approx10^{-5}$的情况下，不规则裁剪SR码的信噪比（SNR）比规则裁剪SR码提高了0.4 dB。我们进一步表明，不规则裁剪SR码在很宽的码率范围内是鲁棒的。
英文摘要：
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.
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