A Graded Precompensation Scheme by Pattern Classification on Nonlinear Transition Shift for Perpendicular Magnetic Recording

To achieve higher magnetic recording areal densities, signal distortions caused by the crosstalk among consecutive magnetized transitions that lead to nonlinear transition shifts (NLTS) must be eliminated. We calculated and sorted the transition shifts of different recorded patterns and classified corresponding patterns based on an analytical method. We proposed a graded write precompensation scheme according to the classified patterns and compared the detecting performance of a perpendicular magnetic recording system using the graded compensation and traditional pattern-aware compensation during the writing process. Simulation results show our proposed graded precompensation can effectively mitigate the nonlinear distortion effect caused by NLTS and outperforms the traditional pattern-aware compensation method. The detecting BER decreases by 14.7% when the SNR of electronic noise is only 20 dB and the bit length is 10 nm.