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The structure of polyolefin has an important influence on its performance and application. Ethylene/1-hexene copolymerization is one of the important ways to control the structure of the polyolefin. However, research on the ethylene/1-hexene copolymerization catalyzed by nickel complexes with different steric ligands remains to be refined. Here, three α-diimine nickel catalysts are used to study the ligand effect on catalytic performance in the ethylene/1-hexene copolymerization. Reaction activity, molecular weight, phase-transition temperature and branching density of the resultant copolymer are measured to evaluate the catalytic performance. The results indicate that the steric ligands could exert great effect on the copolymerization. As for the chemical valence of Ni species, detailed EPR demonstrate that the presence of excess co-catalyst can reduce Ni(II) to the lower valence and affect the catalytic performance.

In this paper, we propose a low-complexity ordered statistics decoding (OSD) algorithm called threshold-based OSD (TH-OSD) that uses a threshold on the discrepancy of the candidate codewords to speed up the decoding of short polar codes. To determine the threshold, we use the probability distribution of the discrepancy value of the maximal likelihood codeword with a predefined parameter controlling the trade-off between the error correction performance and the decoding complexity. We also derive an upper-bound of the word error rate (WER) for the proposed algorithm. The complexity analysis shows that our algorithm is faster than the conventional successive cancellation (SC) decoding algorithm in mid-to-high signal-to-noise ratio (SNR) situations and much faster than the SC list (SCL) decoding algorithm. Our addition of a list approach to our proposed algorithm further narrows the error correction performance gap between our TH-OSD and OSD. Our simulation results show that, with appropriate thresholds, our proposed algorithm achieves performance close to OSD’s while testing significantly fewer codewords than OSD, especially with low SNR values. Even a small list is sufficient for TH-OSD to match OSD’s error rate in short-code scenarios. The algorithm can be easily extended to longer code lengths.