Modified Viterbi Algorithm with Feedback Using a Two-Dimensional 3-Way Generalized Partial Response Target for Bit-Patterned Media Recording Systems

Abstract

The ever-increasing demand for data in recent times has led to the emergence of big data and cloud data. The growth in these fields has necessitated that data be centrally stored in data centers. To meet the need for large-scale storage systems at data centers, innovative technology such as bit-pattern media recording (BPMR) has been developed. With BPMR technology, we are able to achieve significant improvements in high areal density (AD) of magnetic data storage systems. However, two-dimensional (2D) interference is a common issue faced with high AD. Intersymbol interference and intertrack interference occur when the distance between the islands is decreased in the down-track and cross-track, respectively. 2D interference adversely affects the performance of BPMR. In this paper, we propose an improved modified Viterbi algorithm (MVA) exploiting a feedback and a new 2D three-way form of a generalized partial response (GPR) target. The proposed MVA with feedback is superior to the previous MVA by eliminating intertrack interference (ITI) more effectively. With the three-way GPR target, the proposed algorithm achieves more stable performance compared to the previous detection algorithms for the track misregistration effect.

Estimating Interference with a Two-Dimensional Viterbi Algorithm for Bit-Patterned Media Recording

“…Our proposed model estimates both the upper and lower interference. Thus, our proposed model can achieve higher performance compared to the model in [18]. Comparing the serial soft output [24], our proposed model removes the interference from the equalized signal.…”

“…Figure 4 shows that the proposed model with the optimal structure can improve the gain from 0.5 to 2.5 dB at a BER of 10 −4 . For the three-way GPR target with feedback [18], the model estimates either the upper or lower interference. Our proposed model estimates both the upper and lower interference.…”

“…We assumed that our model suffers from a 10% TMR. We compared the proposed model with serial detection [24] and the model used in [18]. The results are shown in Figure 5.…”

“…GPR and MVA were used by Wang and Kumar to design a hybrid 2D equalizer [17]. Nguyen and Lee developed a feedback scheme for MVA to improve ITI prediction [18]. To combat ITI with a low implementation cost, Sadeghian and Barry proposed an effective detection technique in [19].…”

“…To remove the ITI effect from the desired track, an ITI cancellation model using the feedback of sidetrack information was proposed by Koonkarnkhai, Warisarn, and Kovintavewat [26]. In [18], owing to the asymmetrical target, the authors were able to extract the ITI information. To improve detection on the center track, Chang and Cruz designed a multitrack detection technique to estimate the interference from the sidetrack [27].…”