Yu Qin, Wu Fei, Zhang Meng, Zhao Yahui, Xie Changsheng
Appl Opt. 2022 Jul 20;61(21):6119-6127. doi: 10.1364/AO.463930.
The iterative Fourier transform (IFT) algorithm is an effective solution for phase retrieval in phase-type holographic data storage systems, but introduces a higher phase error rate. As a result, data reliability becomes a significant issue. In this paper, to improve reliability and decrease decoding latency, we propose a phase distribution aware low-density parity-check (LDPC) code [called point data abstraction library (PDAL)] with outstanding error correcting capability. After experiencing IFT, we first investigate the phase distribution characteristics and find that the adjacent phase distribution is more likely to cross, resulting in higher phase shift percentages. Then, using phase distribution, PDAL optimizes LDPC codes with higher precision decoding information by dynamically applying the phase threshold based on the phase error rate. When the phase error rate is 0.04, the bit error rate, decoding iteration times, and decoding failure rate are all reduced by 51.5%, 26.9%, and 51.8% on average, respectively, compared with traditional LDPC code without exploiting phase distribution. PDAL, which is an efficient and practical error correction approach for phase-modulated holographic data storage, can improve data reliability by boosting error correction performance.
迭代傅里叶变换（IFT）算法是解决相位型全息数据存储系统中相位恢复问题的一种有效方法，但会引入较高的相位错误率。因此，数据可靠性成为一个重要问题。在本文中，为了提高可靠性并减少解码延迟，我们提出了一种具有出色纠错能力的相位分布感知低密度奇偶校验（LDPC）码[称为点数据抽象库（PDAL）]。在经历IFT之后，我们首先研究相位分布特性，发现相邻相位分布更容易交叉，从而导致更高的相移百分比。然后，利用相位分布，PDAL通过基于相位错误率动态应用相位阈值，以更高精度的解码信息优化LDPC码。当相位错误率为0.04时，与未利用相位分布的传统LDPC码相比，误码率、解码迭代次数和解码失败率平均分别降低了51.5%、26.9%和51.8%。PDAL是一种用于相位调制全息数据存储的高效实用的纠错方法，可通过提高纠错性能来提高数据可靠性。
