Coding and signal processing for high density granular magnetic recording systems
Sari Shafidah Shafi'ee
Date of Issue2016
School of Electrical and Electronic Engineering
Data Storage Institute
The Hard Disk Drive (HDD) industry has, in recent years, struggled with attempting to attain continual growth in storage capacity to meet the needs of a rapidly growing storage demand in the information age. Conventional Perpendicular Magnetic Recording (PMR) is already hitting its limit with areal density growth slowing down considerably in recent years. In moving towards higher densities, PMR faces the problem of simultaneously shrinking the size of bits and ensuring the media remains writable without compromising the thermal stability of its magnetic grains. To overcome this, various novel recording architectures have been proposed, namely Heat Assisted Magnetic Recording (HAMR), Bit Patterned Magnetic Recording (BPMR), Shingled Magnetic Recording (SMR) and Two-Dimensional Magnetic Recording (TDMR). HAMR overcomes the trilemma by injecting thermal energy into a high coercivity and thermally stable media (needed for high density) that would otherwise require an excessively strong head field to write. BPMR organizes magnetic grains into a defined lattice and stores bit on single grains known as islands. SMR targets for a higher track density by writing data tracks using a shingling technique. TDMR uses the same writing mechanism as in SMR. In TDMR however, information is read simultaneously from multiple tracks through the use multiple reader heads. To attain massive storage improvements in the near future, the industry needs to invent new ideas across the entire HDD platform. Development of new recording architectures, concurrent with the development of new trends in signal processing are essential in paving the way to new and intriguing prospects of significant performance gains. As such, the first part of the thesis focuses on a system level study of the recently proposed SMR and HAMR channel. The formulation and evaluation of theoretical models for these emerging recording technologies is essential in enabling an accurate prediction of its feasibility. Magnetic researchers often employ micromagnetic channel models for this purpose. Despite its high accuracy, the micromagnetic model is computationally slow in reproducing the magnetization of grains. This renders it unsuitable for error performance studies. The thesis proposes a Grain Flipping Probability (GFP) channel model as an alternative to the micromagnetic model. The GFP consists of a multi-dimensional look-up table (LUT) that is characterized from micromagnetic simulations. It is highly accurate and is able to reproduce grain magnetizations multiple times faster than the micromagnetic model. With the GFP channel model developed, a novel study of the feasibility of SMR and HAMR is carried out in this thesis from a system’s perspective. Developments of new magnetic recording channels can be synergized with advancements in signal processing techniques to bring about an impactful gain in storage capacity in the near future. The remaining part of the thesis therefore focuses on novel signal processing schemes for magnetic recording channels. The iterative detector-decoder is the standard used in today’s HDD. It comprises of a detector block and decoder block that aims to recover the stored information on a media through repetitive exchange of mutual information between the blocks. The detector operates on a trellis structure while the decoder operates on a factor graph. As the iterative detection-decoding scheme is sub-optimal, recent trend in signal processing research is inclined towards the area of joint detection and decoding where the detector and decoder are regarded as one entity that simultaneously detects and decodes the stored information. In this thesis, two novel joint detection/decoding techniques are proposed – 1) Joint Viterbi Detector Decoder (JVDD) 2) Joint Factor Graph Detector Decoder (JFGDD). The JVDD performs detection and decoding jointly in a single step over a channel trellis that consists of pre-defined parity check nodes. While JVDD has shown to perform well in the simulations carried out in this PhD work, its computational complexity can be a drawback in some circumstances. To manage this, novel error-correction codes coined the JVDD class of codes are proposed for the JVDD. The proposed JVDD codes are analytically optimized in this thesis so as to attain the best performance and lowest complexity for the JVDD. The proposed JFGDD scheme on the other hand, operates on a super factor graph structure that is constructed from a combination of a channel factor graph and a code factor graph. As the conventional detection algorithm is executed on a channel trellis, the thesis proposes an alternative implementation of the algorithm on a channel factor graph instead. The performance of the proposed JFGDD is susceptible to the presence of short cycles in its graph. As such, two novel methods of mitigating short cycles are proposed in this thesis. The first method proposes a non-binary adaptation of the algorithm that will minimize the number of connections and thus cycles in the factor graph. The second method proposes the design of constrained General Partial Response (GPR) targets. Advances in signal processing for HDD should be made not only in the area of detection and decoding but also in the area of equalization. As such, the last part of the thesis proposes novel 2D equalization schemes for SMR and TDMR. The shingling technique of writing data in an SMR or TDMR channel causes the read-back signal to be severely corrupted with inter-track interference (ITI) that arises as a result of the overlapping of adjacent tracks. On the contrary, ITI in the existing PMR channel is negligible and are often ignored. To advance SMR/TDMR as a viable future recording architecture for the industry, equalization techniques should be formulated to exploit the ITI present and enhance the reliability of SMR/TDMR channels. The thesis therefore proposes novel 2D equalization schemes to manage the ITI in both channels.
DRNTU::Science::Mathematics::Applied mathematics::Signal processing