R&D: Multitrack Detection With 2D Iterative Soft Estimate Aided Neural Network Equalizer for Heat-Assisted Interlaced Magnetic Recording
For low temperature written track, provides 3.1 and 4dB signal-to-noise ratio gains compared to conventional 2D NNE and 2D LE.
This is a Press Release edited by StorageNewsletter.com on March 31, 2021 at 2:30 pmIEEE Transactions on Magnetics has published an article written by Yuan Li, Yao Wang, Yushu Xu, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China, Lei Chen, Key Laboratory of Computer Vision and Intelligent Information System, Chongqing University of Arts and Sciences, Chongqing, China, Yumei Wen, and Ping Li, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Abstract: “Heat-assisted interlaced magnetic recording (HIMR) with interlaced track layout architecture enables the further increased areal density compared to the conventional heat-assisted magnetic recording. However, the severe transition curvatures of low temperature written tracks cause noticeable nonlinear distortions of readback signal, and the 2-D intersymbol interference (ISI), media noise, and thermal jitter also bring the challenges for data recovery. Correspondingly, a multitrack detection scheme with 2-D iterative soft estimate aided neural network equalizer (2D-ISA NNE) is proposed for the HIMR system, which iteratively feeds back the soft estimate of reliable sidetracks’ information (e.g., high temperature written tracks) during the neural network equalization (NNE) of middle track (e.g., low temperature written track). Here, the Bahl–Cocke–Jelinek–Raviv (BCJR) detector and low-density parity-check (LDPC) decoder are utilized for the following data detection and error corrections. Then, the similar ISA NNE is implemented to recover the sidetracks’ data. It is found that the proposed 2D-ISA NNE algorithm mitigates the 2-D ISI and nonlinear distortion more effectively compared to the conventional 2-D linear equalizer (LE) and neural network equalizer (NNE). For HIMR at the channel bit density of 3.51 Tb/in 2 and overlapping ratio of 0.46, the proposed 2D-ISA NNE algorithm significantly decreases the bit error rate gap between the low temperature and high temperature written tracks. For the low temperature written track, it provides 3.1 and 4 dB signal-to-noise ratio (SNR) gains compared to the conventional 2-D NNE and 2-D LE, respectively.“
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