Lattice-Reduction-Aided Detection based Extended Noise Variance Matrix using Semidefinite Relaxation in MIMO Systems

MIMO시스템에서 Semidefinite Relaxation을 이용한 잡음 분산 행렬 기반의 Lattice-Reduction-Aided 검출기

  • 이동진 (시립인천대학교 전자공학과 신호처리연구실) ;
  • 박수빈 (시립인천대학교 전자공학과 신호처리연구실) ;
  • 변윤식 (시립인천대학교 전자공학과)
  • Published : 2008.11.30

Abstract

Recently lattice-reduction (LR) has been used in signal detection for multiple-input multiple-output (MIMO) systems. The conventional LR aided detection schemes are combinations of LR and signal detection methods such as zero-forcing (ZF) and minimum mean square error (MMSE) detection. In this paper, we propose the Lattice-Reduction-aided scheme based on extended noise variance matrix to search good candidate symbol set in quantization step. Then this scheme estimates transmitted symbol with Semidefinite Relaxation by candidate symbol set. Simulation results in a random MIMO system show that the proposed scheme exhibits improved performance and a slight increase in complexity.

공간 다중화 방식의 MIMO(Multiple-Input Multiple-Output) 시스템에서 MLD(Maximum-Likelihood Detector)는 최적의 성능을 보이지만, 그 복잡성이 상당히 큰 단점이 있다. 이를 보완하기 위해 여러 가지 기법들이 제안되었으며, Lattice-reduction(LR) 검출기 또한 MIMO 시스템의 성능을 개선하기 위해 제안되었다. 본 논문에서는 확장된 잡음분산 행렬을 이용해 rounding operation 과정에서 발생하는 양자화 오류를 이용해 송신 신호 벡터에 근접한 candidate symbol set을 찾고, 여기서 Semidefinite Relaxation을 이용해 최대 우도 symbol을 검출한다. 그러나 그 복잡도는 MLD의 복잡도 보다 현저히 작고, LR 검출기의 복잡도에 근접한다.

Keywords

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