  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.
