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

대한전자공학회 (The Institute of Electronics and Information Engineers)
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피드백 에러가 있는 빔포밍 시스템에서 개선된 인덱스 배치기법

Enhanced Index Assignment for Beamforming with Limited-rate Imperfect Feedback

  • 박노윤 (충북대학교 정보통신공학과) ;
  • 김영주 (충북대학교 전자정보대학 컴퓨터정보통신연구소)
  • Park, Noe-Yoon (School of Information and Communication Engineering, Chungbuk National University) ;
  • Kim, Young-Ju (Research Institute for Computer and Information Communication, College of Electrical & Computer Engineering, Chungbuk National University)
  • 투고 : 2012.03.19
  • 심사 : 2012.05.12
  • 발행 : 2012.05.25
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초록

양자화된 빔포밍 시스템은 정확한 채널 상태 정보를 특정 벡터로 구성된 유한 집합, 즉 코드북으로 양자화하여 원하는 벡터에 대응되는 인덱스만을 송신단으로 피드백함으로써 피드백 오버헤드 및 지연 등에 의해 발생되는 영향을 최소화한다. 이와 관련하여 전역 (exhaustive) 및 그룹화 (group-based)를 이용한 탐색 기반의 인덱스 재배치 기법을 통해 추가적인 비트의 요구없이 피드백 에러에 의한 성능저하의 최소화 기법에 대한 연구가 수행되었다. 본 논문에서는 기존에 연구되었던 인덱스 재배치 기법에 코드북 내 벡터간의 chordal 거리에 따른 최적 코드북 설계기법 통해 적응적 특성을 갖는 개선된 그룹화 기반의 코드북 인덱스 배치 기법을 제안한다. Monte-Carlo 기반의 모의실험에 의해 제안하는 기법은 송신 안테나 수가 4이고 LTE 코드북을 이용할 경우 인덱스 재배치 기법을 사용하지 않을 때보다 동일한 비트 에러율을 얻기 위해 0.5~1dB 성능이 향상되며, 기존 그룹화 기반의 인덱스 배치 기법보다는 동일 환경에서 0.1~0.2dB 성능이 향상된다.

The quantized beamforming systems always need the channel state information, which must be quantized into a finite set of vectors (named codebook), and feedback only sends the index representing the desired vector. Thereby it minimized the impact of feedback errors, caused by feedback overhead and delay. In this regard, index assignment (IA) methods, an exhaustive-search and group-based schemes, have been presented for minimizes the performance degradation without additional feedback bits. In this paper, we proposed enhanced group-based IA method, which used the optimal codebook design with chordal distance, having the adaptive properties in application of the existing IA methods. When the number of transmit antennas is 4 and LTE codebook is used, Monte-Carlo simulations verify that the proposed scheme has a power advantage of 0.5~1dB to obtain the same bit error rate than methods without IA, and it has 0.1~0.2 dB better performance compared with the existing IA methods over same environment.

키워드

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