Exploiting Extrinsic Information for Serial MAP Detection by Utilizing Estimator in Holographic Data Storage Systems

In the big data era, data are created in huge volume. This leads to the development of storage devices. Many technologies are proposed for the next generation of storage fields. However, among them, holographic data storage (HDS) has attracted much attention and has been introduced as the promising candidate to meet the increasing demand for capacity and speed. For signal processing, HDS faces two major challenges: inter-page interference (IPI) and two-dimensional (2D) interference. To access the IPI problem, we can use balanced coding, which converts user data into an intensity level with uniformly distributed values for each page. For 2D interference, we can use the equalizer and detection to mitigate the 2D interference. However, the often-used equalizer and detection are methods in wireless communication and only handle the one-dimensional (1D) signal. Thus, we can combine the equalizer, detection, and estimator to reduce 2D interference into 1D interference. In this paper, we proposed a combined model using serial maximum a posteriori (MAP) detection and estimator to improve the detection of HDS systems. In our proposed model, instead of using an estimator with the Viterbi algorithm to predict the upper–lower interference (UPI) or left–right interference (LRI) and converting the received signal into 1D ISI, we used the estimator to predict the extrinsic information for serial MAP detection. This preserves the 2D information in the received signal in serial MAP detection and improves the detection of serial MAP detection by extrinsic information. The simulation results demonstrate that our proposed model significantly improves the bit-error rate (BER) performance compared to previous studies.