R&D: Multitrack Detection With 2D Iterative Soft Estimate Aided Neural Network Equalizer for Heat Assisted Interlaced Magnetic Recording
For low temperature written track, it provides 3.1dB and 4dB signal to noise ratio gains compared to conventional 2D NNE and 2D linear equalizer, respectively.
This is a Press Release edited by StorageNewsletter.com on October 26, 2020 at 10:09 amIEEE 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 200240 China, Lei Chen, Key Laboratory of Computer Vision and Intelligent Information System, Chongqing University of Arts and Sciences, Chongqing 402160 China, Yumei Wen, and Ping Li, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240 China.
Abstract: “Heat assisted interlaced magnetic recording (HIMR) with interlaced track layout architecture enables the further increased areal density compared to conventional heat assisted magnetic recording. However, the severe transition curvatures of low temperature written tracks cause noticeable nonlinear distortions of readback signal, and the 2D inter-symbol interference (ISI), media noise and thermal jitter also bring the challenges for data recovery. Correspondingly a multitrack detection scheme with 2D 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 iterative soft estimate aided NNE is implemented to recover the sidetracks’ data. It is found that the proposed 2D-ISA NNE algorithm mitigates the 2D ISI and nonlinear distortion more effectively compared to the conventional 2D linear equalizer and neural network equalizer (NNE). For HIMR at the channel bit density of 3.51 Tb/in2 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 dB and 4 dB signal to noise ratio (SNR) gains compared to the conventional 2D NNE and 2D linear equalizer, respectively.“
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