High-density Recording Channels Research Articles

Improved 2-D Graph-Based Detectors for 2-D Interference Channels

The 2-D interference channels, which consist of intersymbol interference as well as intertrack interference (ITI), appear in high-density recording channels. A graph-based detector has received much attention since it is a real 2-D detector, which can recover data from multiple tracks or each 2-D page simultaneously. In this paper, we propose two approaches to improve the performances of graph-based detectors. For the first method (M1), which processes data on a 2-D page, the system equalizes 2-D interference channel into two 1-D targets, horizontal and vertical directions followed by two corresponding graph detectors. The second method (M2) is similar to the first one, but the 2-D channel is equalized into two 2-D targets with and without cornered ITIs, respectively, in order to better handle the effects of cornered ITIs. Compared with the full-graph detector, the method M1 offers reduced-complexity due the fewer number of edges from the factor nodes. The simulation results on the 3 × 3 channel matrix with 2% cornered ITI show that the proposed methods achieve the gains of about 1.0 and 1.7 dB, respectively, at the BER of 10 -5 over the full graph detector. As the cornered ITI levels increase, the method M2 gives the larger gains over the others. When the media noise is accounted for, the method M2 still gives the best performances. Finally, the mutual information of the three graph detectors for the 2-D channels is computed and compared.

신호패턴 종속잡음 채널을 위한 신호검출

고밀도의 저장기록장치 채널의 주요 신호검출 오류의 원인은 천이 지터잡음이다. 이러한 채널환경에서 최적의 신호검출기 구현을 위해서는 고도의 복잡도가 요구되는데 이는 지터잡음이 신호와 상관관계가 있고 잡음간에도 상관관계가 존재하기 때문이다. 본 논문에서는 계산량과 하드웨어 복잡도 관점에서 효율적인 두 가지 종류의 신호검출기에 대해서 설명한다. 이는 전통적인 비터비 복호기의 가지값을 변화시킨 형태이며 같은 이진데이터 값의 반복을 제한하는 부호와 함께 결합하여 일반적인 PR 채널에 적용된다 기존의 비터비 알고리즘의 복잡도와 비교하면 비터비 트렐리스에서 각각의 가지값을 계산할 때 추가적으로 하나의 곱셈기 혹은 덧셈기의 증가가 요구된다. Transition jitter noise is one of major sources of detection errors in high density recording channels. Implementation complexity of the optimal detector for such channels is high due to the data dependency and correlated nature of the jitter noise. In this paper, two types of hardware efficient sub-optimal detectors are derived by modifying branch metric of Viterbi algorithm and applied to partial response (PR) channels combined with run length limited modulation coding. The additional complexity over the conventional Viterbi algorithm to incorporate the modified branch metric is either a multiplication or an addition for each branch metric in the Viterbi trellis.

Alternating Coordinates Minimization Algorithm for Estimating Parameters of Partial Erasure Plus Transition Shift Model

The identification of model parameters of a high-density recording channel is usually difficult and complicated. In this paper, we successfully apply the alternating coordinates minimization (ACM) algorithm for estimating parameters of a partial erasure plus transition shift model (PETSM). The resulting algorithm turns out to iteratively solve two least square problems and is guaranteed to converge. Furthermore, the obtained model for a nonlinear partial response channel is more accurate than conventional models such that the maximum likelihood (ML) detector has better bit error rate (BER) performance without increasing its realization complexity. Computer simulations show that the ACM algorithm can accurately estimate the model parameters and the BER for the detector is significantly improved especially when the transition shift parameter is large.

Performance Analysis of Soft-Output Post-Processing Detection for Data-Dependent Media Noise Channels

A soft-output data-detection scheme optimized for data-dependent media-noise recording channels is investigated that uses signal-dependent correlation-sensitive (SDCS) metric computation for post-processing decoding. This media-noise soft-output (MNS) decoding scheme achieves suboptimal maximum-likelihood (ML) sequence detection in a nonstationary media-noise channel, while still using traditional Viterbi detection. Because it drastically reduces SDCS metric computation by focusing on correcting only the dominant error events in the ML detector, it is less complex than other suboptimal detection schemes. Moreover, the MNS decoding scheme provides parity-check-code decoding with more reliable soft-output information. Simulation showed that MNS decoding in conjunction with a conventional ME/sup 2/PRML system, provides an excellent tradeoff between data-detection performance and computation complexity for a jitter-noise dominant high-density recording channel.

Expectation and maximization algorithm for estimating parameters of a simple partial erasure model

The identification of the model parameters of a high-density recording channel generally requires solution of nonlinear equations. In this paper, we apply the expectation and maximization (EM) algorithm to realize the maximum likelihood estimation of the parameters of a simple partial erasure model, including the reduction parameters and the isolated transition response. The algorithm that results from this approach iteratively solves two least-squares problems and, thus, realization is simple. Computer simulations verify the feasibility of the EM algorithm, and show that the proposed algorithm has fast convergence and the resulting estimator is asymptotically efficient.

Improved distance M-ary (d,k) codes for high density recording

We consider the problem of coding for a high density recording channel. New recording media have been developed that support unsaturated, M-ary (M/spl ges/3) signaling. This paper is concerned with the analysis and design of M-ary runlength limited (RLL) codes for multi-amplitude, linear recording AWGN channels. The codes achieve the largest known coding density and have improved minimum distance over an ordinary Adler-Coppersmith-Hassner code designed via the state splitting algorithm. Comparisons are made with Ungerboeck-style trellis codes with comparable complexity.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Performance analysis of decision-feedback equalization with maximum-likelihood detector in high-density recording channels

The performance of decision-feedback equalization combined with maximum-likelihood detection (DFE/ML) using the FDTS/DF algorithm was estimated analytically in terms of the length of the feedback-filter and the depth of the ML-detector. Performance degradation due to error propagation in the feed-back loop and in the ML-detector was taken into account. It was quantitatively shown that signal-to-noise-ratio performance in high-density magnetic recording channels can be improved by combining an ML-detector and a feedback-filter. In particular, it was found that near-optimum performance can be achieved over the channel density range from 2 to 3 by increasing the total of the feedback-filter length and the ML-detector depth to six bits.

Adaptive reduced-state sequence estimation for linearly and nonlinearly distorted signals in magnetic recording channels

An adaptive reduced-state sequence estimation (RSSE) is described, which uses a memory table to equalize both nonlinear distortion, a particular problem in high density recording channels, and linear distortion. Time-variant factors contributing to both types of distortion can be handled by updating the memory table. RSSE is far less complicated than MLSE, whose complexity results from long channel memory. Error probability analysis accomplished with computer simulation confirms the potential for excellent performance in high density magnetic recording systems. >

Media selection for high density recording channels

The implementation of high-density partial response channels in disk drives has been hampered by nonlinear interactions between transitions occurring in the write process. It is shown that the degree of nonlinearity is not characterized by the density relative to the isolated transition pulse width, but rather by the transition spacing in relation to the transition width. Factors that determine the transition width are examined. In particular, the potential gains from using low moment media are investigated. A nonlinear model of the disk channel is discussed. The dependence of partial response signaling on linear superposition is discussed. Eye patterns are shown revealing the effects of nonlinearities on a partial response system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modulation noise measurements of high density recording channels using MR heads

Modulation noise measurements were made on several tape samples using an unshielded magnetoresistive (MR) head. The very high sensitivity of the MR head makes possible the detection of the media noise above other noise sources not associated with the recording medium, such as head resistance and preamplifier noise. The effect of track width on modulation noise was investigated. It has been shown previously that modulation noise, which is multiplicative in nature, is not purely Gaussian but also contains a significant exponential component. The implications of the non-Gaussian nature of this noise for amplitude qualifier level setting and for error rates in peak-detecting and partial-response channels are discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A general solution of write equalization for digital magnetic tape recording

A general solution of digital recursive filters which produce two-level output is given. To give a rough idea of the performance of write equalizers, a high-density recording channel corrupted by additive noise is appraised, and the signal-to-noise ratio with and without a write equalizer is compared. Calculations show that a small gain can be expected in using some of the write equalizers. The linearity of the channel was tested using some of the write equalizers. >