Improving reliability using phase distribution aware LDPC code for holographic data storage

Abstract

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.