Data Detection Methods for Holographic Data Storage Systems

Abstract

We suggest a new method for data detection based on direct data identification and compare this new method with three commonly used methods based on decimation using linear transformations. To compare these methods, the complete procedure from data page creation, sending data through an optical channel, and data detection is simulated numerically. This is performed by varying the noise level, sampling factor, and spatial filter. The proposed method requires a higher computational complexity, but for a broad range of realistic system parameters, it enables lower symbol error ratios.

Two-Dimensional Soft Output Viterbi Algorithm with a Variable Reliability Factor for Holographic Data Storage

“…2) In particular, the 2D ISI greatly degrades quality of the image. Considering the influence of the 2D ISI, several new approaches have been proposed for the data page reconstruction in recent years: a 2D equalizer, [3][4][5] 2D partial response maximum likelihood (PRML), 6,7) 2D PRML using constant-weight constraint, 8,9) 2D PRML based on 2D soft output Viterbi algorithm (SOVA), [10][11][12] decoding scheme based on turbo equalizer, 13,14) decoding scheme based on 2D modulation code, [15][16][17][18] decoding scheme based on tone controllable code, 19,20) correlation-based detection method, 21) 2D modulation code, [22][23][24] and tone controllable code. 25,26) In this paper, we focus on 2D PRML based on the 2D SOVA satisfying both superior performance and low computational complexity.…”