Shafa Dahandeh

A Communication-Theoretic Framework for 2-DMR Channel Modeling: Performance Evaluation of Coding and Signal Processing Methods

We develop a communication theoretic framework for modeling 2-D magnetic recording channels. Using the model, we define the signal-to-noise ratio (SNR) for the channel considering several physical parameters, such as the channel bit density, code rate, bit aspect ratio, and noise parameters. We analyze the problem of optimizing the bit aspect ratio for maximizing SNR. The read channel architecture comprises a novel 2-D joint self-iterating equalizer and detection system with noise prediction capability. We evaluate the system performance based on our channel model through simulations. The coded performance with the 2-D equalizer detector indicates ~ 5.5 dB of SNR gain over uncoded data.

Hard disk drive suspension interconnect modeling

As hard disk drive write and read data rates become higher, careful modeling of suspension interconnects becomes more important to understanding and designing the write and read circuits. In the past, interconnect models have often ignored losses and included only one propagation mode. More complete models that avoid these limitations are reviewed here and illustrated with example simulations. Fast-executing, reliable models can be chosen by considering the interconnect and terminating circuits of interest.

Timing Recovery Algorithms and Architectures for 2-D Magnetic Recording Systems

We investigate the problem of timing recovery for 2-D magnetic recording (TDMR) channels. We develop a timing error model for TDMR channel considering the phase and frequency offsets with noise. We propose a 2-D data-aided phase-locked loop (PLL) architecture for tracking variations in the position and movement of the read head in the down-track and cross-track directions and analyze the convergence of the algorithm under non-separable timing errors. We further develop a 2-D interpolation-based timing recovery scheme that works in conjunction with the 2-D PLL. We quantify the efficiency of our proposed algorithms by simulations over a 2-D magnetic recording channel with timing errors.

Polar codes for magnetic recording channels

Polar codes provably achieve the capacity of binary memoryless symmetric (BMS) channels with low complexity encoding and decoding algorithms, and their finite-length performance on these channels, when combined with suitable decoding algorithms (such as list decoding) and code modifications (such as a concatenated CRC code), has been shown in simulation to be competitive with that of LDPC codes. However, magnetic recording channels are generally modeled as binary-input intersymbol interference (ISI) channels, and the design of polar coding schemes for these channels remains an important open problem. Current magnetic hard disk drives use LDPC codes incorporated into a turbo-equalization (TE) architecture that combines a soft-output channel detector with a soft-input, soft-output sum-product algorithm (SPA) decoder. An interleaved coding scheme with a multistage decoding (MSD) architecture with LDPC codes as component codes has been proposed as an alternative to TE for ISI channels. In this work, we investigate the use of polar codes as component codes in the TE and MSD architectures. It is shown that the achievable rate of the MSD scheme converges to the symmetric information rate of the ISI channel when the number of interleaves is large. Simulations results comparing the performance of LDPC codes and polar codes in TE and MSD architectures are presented.

Exploring Two-Dimensional Magnetic Recording Gain Constraints

Two-dimensional magnetic recording (TDMR) offers the opportunity to provide areal density (AD) gain, but questions were unanswered as to how the gain is achieved and what can be done to maximize the gain from this new technology. In this paper, we offer some reasons why different investigators might report different AD gain opportunities. We present data collected on a spin stand with two reader heads and processed with a commercially available field programmable gate array TDMR channel. The implications of this paper should provide guidelines on reader geometries, placement, and performance.

Self-Directed Equalization for Magnetic Recording Channels With Multi-Sensor Read Head

Today, adaptive equalization is generally used to capture the run-time read channel dynamics in the presence of a random read-head offset. An adaptive equalizer updates its coefficients using a certain adaptive signal-processing algorithm, e.g., least-mean-square algorithm. This paper proposes a self-directed equalization strategy for the emerging very high-density magnetic recording drives with a multi-sensor read head. The key idea is to exploit the spatial diversity of readback signals from different read sensors to accurately estimate run-time read-head offsets, based upon which the equalizer coefficients are accordingly self-configured in order to improve the equalization performance. This paper presents specific methods to practically implement this design strategy, and its effectiveness has been well demonstrated through the simulations with a Voronoi-based channel model.