Jaekyun Moon
Korea Advanced Institute of Science and Technology · Computer Science
About the Lab
Professor Jaekyun Moon's research lab specializes in signal processing and detection techniques for high-density magnetic recording systems. The lab focuses on advanced equalization, sequence detection, and noise modeling in channels dominated by transition jitter and signal-dependent noise. Key research directions include the design of efficient maximum-likelihood sequence detectors, optimization of signal-to-noise ratio metrics, and development of coding schemes that enhance detection performance under severe intersymbol interference and noise correlation.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15In this paper, the minimum mean-square error (MMSE) technique has been used to equalize the recording channel in order to facilitate the application of the Viterbi detector. The resulting performance has been compared with that of the optimal equalization system which yields the minimum probability of error at the output of the Viterbi detector. The results indicate that depending on the constraint used in the MMSE design, the amount of noise correlation varies significantly at the equalizer out
Various detection schemes suitable for magnetic recording are compared in terms of their effective signal-to-noise ratios. It is shown that at high densities the performance of conventional detectors such as a peak detector, a threshold detector with partial response equalization, a decision feedback equalizer, and a Viterbi algorithm detector tuned to a linearly truncated channel fall far below the optimum performance that can be achieved by the maximum-likelihood sequence detector (MLSD). It i
Maximum and near-maximum likelihood sequence detectors in signal-dependent noise are discussed. It is shown that the linear prediction viewpoint allows a very simple derivation of the branch metric expression that has previously been shown as optimum for signal-dependent Markov noise. The resulting detector architecture is viewed as a noise predictive maximum likelihood detector that operates on an expanded trellis and relies on computation of branch-specific, pattern-dependent noise predictor t
A new code is presented which improves the minimum distance properties of sequence detectors operating at high linear densities. This code, which is called the maximum transition run code, eliminates data patterns producing three or more consecutive transitions while imposing the usual k-constraint necessary for timing recovery. The code possesses the similar distance-gaining property of the (1,k) code, but can be implemented with considerably higher rates. Bit error rate simulations on fixed de
Discrete-time modeling of transition-noise-dominant channels is considered which facilitates performance analysis of various sample-data detection schemes. Based on the proposed channel description method in the presence of transition noise, expressions for signal-to-total-noise-power ratios associated with a few selected detection schemes are derived. Under the assumption of a Lorentzian step response and perfect equalization, a comparison is made among different detectors based on the signal-t
This paper proposes a new signal-to-noise ratio (SNR) definition for magnetic recording channels with both additive and medium noise components. The proposed SNR is a generalized version of E/sub b//M/sub 0/, the information bit energy to noise spectral height ratio, widely used in average-power-constrained communication channels with additive white noise. The goal is to facilitate comparison of efficiencies of read channels that may operate at different symbol densities because of varying code
This paper addresses the data detection problem of intersymbol interference (ISI) channels with a specific modulation code-constraint known as the (d, k) run-length-limited (RLL) constraint, a popular modulation code-constraint for data storage channels as well as certain communication channels. A computationally efficient sequence detection algorithm is proposed which yields a performance close to that of the maximum likelihood sequence detector when applied to such ISI channels. The proposed d
The dependence of noise in thin metallic longitudinal disks on the transition density is investigated. The medium noise is modeled in the time domain by assuming that the recorded transitions are subject to random variations in width as well as in position. A time domain measurement technique is developed to estimate the second order statistics of transition width and transition position as a function of recording density. The results indicate that the noise due to the transition width variation
Among the key components in the development of a successful storage system are heads, media, and signal processing. In the past, major breakthroughs in the heads and media technologies have been mainly responsible for the spectacular growth in storage capacity, but signal processing is increasingly recognized as a cost-efficient means of improving density. This article addresses the issues relevant to signal processing. While the focus is on magnetic storage, most of the signal-processing strate
Given the limited set of empirical input/output data from flash memory cells, we describe a technique to statistically analyze different sources that cause the mean-shifts and random fluctuations in the read values of the cells. In particular, for a given victim cell, we are able to quantify the amount of interference coming from any arbitrarily chosen set of potentially influencing cells. The effect of noise and interference on the victim cell after repeated program/erase cycles as well as baki
We discuss an error detection technique geared to a prescribed set of error events. The traditional method of error detection and correction attempts to detect/correct as many erroneous bits as possible within a codeword, irrespective of the pattern of the error events. The proposed approach, on the other hand, is less concerned about the total number of erroneous bits it can detect, but focuses on specific error events of known types. We take perpendicular recording systems as an application ex
We present a particular generator polynomial for a cyclic redundancy check (CRC) code that can be used to detect all dominant error events in perpendicular recording over a broad range of densities. This polynomial is also effective in detecting error events that occur at codeword boundaries. The bit-error-rate and the sector-error-rate performances are validated that result from the use of the corresponding CRC code in conjunction with the well-known post-Viterbi error correction method.
Nonlinear broadening of closely spaced transitions has been studied using micromagnetics simulations. Results show a large increase in the width of a transition due to the demagnetizing field effect of earlier transitions. Based on this observation, a simple recording channel model is developed to investigate the effects of nonlinear transition broadening on detection performance. This analysis shows that the conventional peak detector is much less sensitive to the detrimental effects of nonline
The performance of various detector/RLL (run-length-limited) code combinations was investigated assuming the presence of both additive white noise and transition noise. The results indicate that for detectors relying heavily on linear suppression of ISI (intersymbol interference), the transition-noise effect does not show up at high densities because of relatively severe enhancement of the additive-noise component. However, transition noise degrades performance of FDTS/DF (fixed delay tree searc
Research Areas
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