Signal Processing And Coding For Two-Dimensional Magnetic Recording System

With the density of magnetic storage devices approaching to the superparamagnetic limits of 1 Tb/in²,there is an effort in the industry and academia to develop next-generation recording systems.Two-dimensional magnetic recording（TDMR）is one promising candidate for future ultrahigh density magnetic recording.Compared with other technology such as bit-patterned magnetic recording（BPMR）and energy-assisted magnetic recording（EAMR）,TDMR relies on the use of traditional recording media,while mainly relying on signal processing to make improvements in the recording density.The ultimate goal of TDMR is to store one bit on one magnetic grain,which means the bit area will become very small.On the other hand,the read head will be larger than a bit area.Hence,there will be severe 2D ISI during the readback process.Thus,2D signal processing algorithm is the nature of the TDMR.For the problem of density improved of conventional magnetic recording by two-dimensional signal processing,this paper mainly study on equalization and detection techniques in-depth.This paper builds a complete TDMR model firstly,and then deduces the design method for 2D GPR equalize target.According to the 2D ISI of TDMR channel,this paper provides a modified Viterbi detection algorithm.Simulation results show that2D GPR equalization can eliminate ITI effectively compared with conventional 1D GPR equalization.Also,the required SNR grows with a decrease of grain density to reach the target BER of 10^-4.Media noise in TDMR is data dependent according to research,which can be effectively handled by constrained coding.This research proposes a new two-dimensional constrained coding scheme which is easy to implement.This coding scheme is used to eliminate the most severe data dependent 2D pattern.Simulation results shows that proposed constrained coding algorithm can improve the BER performance with a high code rate of 0.95.