Optimal unequal-interval phase encoding method for phase modulated holographic data storage

In phase-modulated holographic storage, unequal interval phase encoding provides distinct diffraction intensity distributions between adjacent phases, which offers more discriminative features for convolutional neural networks. Numerous combinations of unequal-interval encoding schemes exist, and there is a lack of effective guidelines for their optimization. To address this, we propose an encoding design method based on phase difference interval optimization, which systematically regulates the distribution of phase differences to improve reconstruction performance. Simulation and experimental results demonstrate that the designed three-level and four-level encoding methods achieve the lowest phase reconstruction errors. Compared to the equal-interval encoding, the BER of the optimal three-level phase encoding (0, 43, 128) decreased by about 59%, while the BER of the optimal four-level phase encoding (0, 21, 85, 127) decreased by about 38%, validating the effectiveness and superiority of the proposed method. Furthermore, this approach has the potential to be extended to higher-level encoding, providing new insights for the encoding design of high-capacity holographic storage systems.