Article

Minimum-Latency Tracking of Rapid Variations in Two-Dimensional Storage Systems

IEEE Transactions on Magnetics (Impact Factor: 1.21). 02/2007; DOI: 10.1109/TMAG.2006.886844
Source: IEEE Xplore

ABSTRACT The trend of increasing storage densities results in growing sensitivity of system performance to variations of storage channel parameters. To counteract these variations, more adaptivity is needed in the data receiver. Accurate tracking of rapid variations is limited by latencies in the adaptation loops. These latencies are largely governed by delays of the bit detector. In two-dimensional storage systems, data are packaged in a group of adjacent tracks or rows, and for some of the rows the detection delays can increase dramatically with respect to one-dimensional systems. As a result, the effective latencies in the adaptation loops preclude the tracking of rapid variations and really limit the performance of the system. In this paper, a scheme is proposed that overcomes this problem and that can be used for timing recovery, automatic gain control, and other adaptive circuits. Rapid variations for all the rows are tracked using control information from rows for which detector latency is smallest. This works properly if rapid variations are common across the rows as is the case, for example, for the two-dimensional optical storage (TwoDOS) system. Experimental results for TwoDOS confirm that the scheme yields improved performance with respect to conventional adaptation schemes

0 Bookmarks
 · 
120 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper describes an architecture for a read channel which can be used to recover data from a multi-track optical medium. The multi-track format allows for a higher density of data storage as well as a higher data transfer rate for applications such as high density DVDs. The proposed channel is based on a 2D partial response over a hexagonal lattice and employs a 2D nonlinear equalizer and 2D data detection. Bit error measurements based on sampled data from a prototype disc and optics, and offline software read channel are presented and show satisfactory performance.
    IEEE Transactions on Consumer Electronics 12/2004; · 1.16 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we consider the problem of modeling the timing error process in magnetic recording systems. We propose a discrete-valued Markov model for the timing error process, and design two methods (data-aided and nondata-aided), based on the Baum-Welch algorithm, to extract the model parameters from the readback waveforms. The channel model we consider is an intersymbol interference (ISI) channel with additive Gaussian noise. The continuous-time readback signal at the output of the channel is sampled at baud-rate. Simulation results show that the estimated parameters are close to the actual values and the convergence is attained in a few iterations of the Baum-Welch algorithm. We also demonstrate the usefulness of the accurate model extraction by comparing a fine-tuned Markov timing recovery loop to the standard Mueller and Muller detector with a tuned second-order loop filter.
    IEEE Transactions on Magnetics 03/2006; · 1.21 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In high-density data storage systems, noise becomes highly correlated and data dependent as a result of media noise, channel nonlinearities, and front-end filters. In such environments, conventional timing recovery schemes will exhibit large residual timing jitter and, especially, data-dependent timing jitter. This paper presents a new data-aided timing recovery algorithm for data storage systems with data-dependent noise. We derive a maximum-likelihood timing recovery scheme based on a data-dependent Gauss-Markov model of the noise. The timing recovery algorithm incorporates data-dependent noise prediction parameters in the form of linear prediction filters and prediction error variances. Moreover, because noise can be nonstationary in practice, we propose an adaptive algorithm to estimate and track the noise prediction parameters. Simulation results, for an idealized optical storage channel incorporating a simple model of media noise, illustrate the merits of our algorithm
    IEEE Transactions on Magnetics 12/2006; · 1.21 Impact Factor

Preview

Download
0 Downloads
Available from