Woosik Moon

A Compressed Sensing Approach for Modeling the Super-Resolution Near-Field Structure Disc System With a Sparse Volterra Filter

In this paper, we investigate the compressed sensing (CS) algorithms for modeling a super-resolution near-field structure (super-RENS) disc system with a sparse Volterra filter. It is well known that the super-RENS disc system has severe nonlinear inter-symbol interference (ISI). A nonlinear system with memory can be well described with the Volterra series. Furthermore, CS can restore sparse or compressed signals from measurements. For these reasons, we employ the CS algorithms to estimate a sparse super-RENS read-out channel. The evaluation results show that the CS algorithms can efficiently construct a sparse Volterra model for the super-RENS read-out channel and that observable nonlinear interactions take place among restricted components in the read-out channel.

Performance of the Contraction Mapping-Based Iterative Two-Dimensional Equalizer for Bit-Patterned Media

Bit-patterned media (BPM) storage is one of the promising technologies to overcome the limitations of the conventional magnetic recording. However, a high-density BPM storage has intertrack interference, intersymbol interference and noise, which severely degrade the system performance. In this paper, we present a simple iterative two-dimensional (2-D) equalizer based on the contraction mapping theorem to mitigate these adverse effects. In the simulation, we demonstrate the bit separation characteristics of the one-dimensional (1-D) and proposed 2-D equalizers and evaluate the bit-error-rate (BER) performance of the proposed equalizer comparing with the conventional equalizers. According to the simulation results, the proposed equalizer is a promising candidate with maintaining proper complexity for a high-density BPM storage.

An iterative two-dimensional equalizer for bit patterned media based on contraction mapping

Patterned media storage (PMS) is one of the promising technologies to overcome the limitations of the conventional magnetic recording. For a high areal density PMS, both inter-track interference (ITI) and inter-symbol interference (ISI), and noise severely degrade the bit error rate (BER) performance of the system. In this paper, we present a simple iterative two-dimensional equalizer, which is based on the contraction mapping theorem, to mitigate these adverse effects. The performance of the proposed equalizer is evaluated using computer simulations for various conditions. Simulation results suggest that the proposed equalizer is a good candidate for ultra-high capacity PMS with a moderate complexity.

Performance evaluation on a polyphase filter bank structure based anti-jamming system

Satellite communication has a broadband property and wide area coverage. It is also vulnerable to jamming because of the utilization of open channels. In this paper, a satellite transponder adopts a polyphase filter bank structure, which allows flexible frequency management while a nulling scheme was applied to remove narrowband interference signal of a filter bank sub-channel. For this satellite transponder, jamming, polyphase filter bank and nulling scheme are introduced, and in the simulation, we evaluate the performance of the anti-jamming system in terms of BER and PSNR by transceiving random data and images under various jamming environments.

A contraction mapping based two-dimensional equalizer and its application to holographic data storage systems

As the limits of the magnetic storage systems appear, the holographic data storage (HDS) devices with high data transfer rate and high recording density are emerging as attractive candidates for next-generation optical storage devices. In this paper, to effectively improve the detection performance that is degraded by the two-dimensional inter-symbol interference under the HDS channel environment and the pixel misalignment, an iterative two-dimensional equalization scheme is proposed based on the contraction mapping. In order to evaluate the performance of the proposed scheme, for various holographic channel environments we measure the BER performance using computer simulation and compare the proposed one with the conventional threshold detection scheme, which verifies the superiority of the proposed scheme.

Application of an iterative 2D equalizer to holographic data storage systems

At the present time when the limits of the magnetic storage systems appear, the holographic data storage (HDS) devices with high data transfer rate and high recording density are emerging as attractive candidates for next-generation optical storage devices. In this paper, to effectively improve the detection performance that is degraded by the two-dimensional inter-symbol interference under the HDS channel environment and the pixel misalignment, an iterative two-dimensional equalization scheme is proposed based on the contraction mapping theorem. In order to evaluate the performance of the proposed scheme, for various holographic channel environments we measure the BER performance using computer simulation and compare the proposed one with the conventional threshold detection scheme, which verifies the superiority of the proposed scheme.