Journal of the Institute of Electronics Engineers of Korea TC (대한전자공학회논문지TC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Neural Networks-Based Nonlinear Equalizer for Super-RENS Discs

Super-RENS 디스크를 위한 신경망 기반의 비선형 등화기

  • Seo, Man-Jung (School of Electronic Engineering, Soongsil University) ;
  • Im, Sung-Bin (School of Electronic Engineering, Soongsil University)
  • 서만중 (숭실대학교 정보통신전자공학부) ;
  • 임성빈 (숭실대학교 정보통신전자공학부)
  • Published : 2008.12.25
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Abstract

Recently, various recording technologies are studied for optical data storage. After standardization of BD (Blu-ray Disc) and HD-DVD (High-Definition Digital Versatile Disc), the industry is looking for a suitable technology for next generation optical data storage. Super-RENS (Super-Resolution Near Field Structure) technique, which is capable of compatibility with other systems, is one of next optical data storage. In this paper, we proposed a neural network-based nonlinear equalizer (NNEQ) for Super-RENS discs. To mitigate the nonlinear ISI (Inter-Symbol Interference), we applied NARX (Nonlinear AutoRegressive eXogenous) which is a kind of neural networks. Its validity is tested with the RF signal samples obtained from a Super-RENS disc. The performance of the proposed equalizer is superior to the one without equalization and that of the Limit-EQ in terms of BER (Bit Error Rate).

최근 들어, 광 기록 저장 시스템을 위한 다양한 기록 방식들이 연구되고 있다. BD (Blu-ray Disc)나 HD-DVD (High-Definition Digital Versatile Disc) 기록 방식의 표준화가 진행된 후에 차세대 광 기록 방식에 대한 관련 업계의 초점이 모아지고 있다. 이러한 차세대 광 기록 저장 시스템 가운데 기술의 호환성이 장점인 Super-RENS (Super-Resolution Near Field Structure) 기술이 유력한 후보 중 하나이다. 본 논문에서는 Super-RENS 디스크를 위한 신경망 기반의 비선형 등화기 (NNEQ)를 제안하였다. 비선형 심볼간 간섭 (Inter-Symbol Interference : ISI)을 제거하기 위해 신경망의 한 종류인 NARX (Nonlinear AutoRegressive eXogenous) 모델을 적용하였다. Super-RENS 디스크로부터 획득한 RF 신호 샘플들을 사용하여 모의실험을 수행한 결과, 제안된 비선형 등화기의 성능은 비트오율 측면에서 등화기가 없는 경우나 기존의 Limit-EQ 보다 우수한 성능을 나타내었다.

Keywords

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