Turbo Equalization Scheme between Partial Response Maximum Likelihood Detector and Viterbi Decoder for 2/4 Modulation Code in Holographic Data Storage Systems

Abstract

A turbo equalization scheme for holographic data storage (HDS) systems is proposed. The proposed turbo equalization procedure is conducted between a one-dimensional (1D) partial response maximum likelihood (PRML) detector and the joint Viterbi decoder by exchanging a priori and extrinsic information. In the joint Viterbi decoder, the modulation and convolutional decoding is performed simultaneously by mapping a 2/4 modulation symbol onto the trellis of the convolutional code to reduce the complexity of the decoding procedure and improve the decoding capability for the iterative equalization and decoding. In addition, since the channel model is described as the two-dimensional convolution in HDS systems, the 1D PRML detector is performed in the vertical direction and the joint Viterbi decoder is performed in the horizontal direction to maximize the performance gains. The simulation result shows that the proposed turbo equalization scheme has the better bit error rate performances as the number of iterations increases.

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.…”