• Title/Summary/Keyword: QR Decomposition Method

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A Study on Eigen-properties of a 3-Dim. Resonant Cavity by Krylov-Schur Iteration Method (Krylov-Schur 순환법을 이용한 3-차원 원통구조 도파관의 고유특성 연구)

  • Kim, Yeong Min;Lim, Jong Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.7
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    • pp.142-148
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    • 2014
  • Krylov-Schur iteration method has been applied to the 3-Dim. resonant cavity of a cylindrical form. The vector Helmholtz equation has been analysed for the resonant field strength in homogeneous media by FEM. An eigen-equation has been constructed from element equations basing on tangential edges of the tetrahedra element. This equation made up of two square matrices associated with the curl-curl form of the Helmholtz operator. By performing Krylov-Schur iteration loops on them, Eigen-values and their modes have been determined from the diagonal components of the Schur matrices and its transforming matrices. Eigen-pairs as a result have been revealed visually in the schematic representations. The spectra have been compared with each other to identify the effect of boundary conditions.

An Improved Search Space for QRM-MLD Signal Detection for Spatially Multiplexed MIMO Systems (공간다중화 MIMO 시스템의 QRM-MLD 신호검출을 위한 개선된 탐색공간)

  • Hur, Hoon;Woo, Hyun-Myung;Yang, Won-Young;Bahng, Seung-Jae;Park, Youn-Ok;Kim, Jae-Kwon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.4A
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    • pp.403-410
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    • 2008
  • In this paper, we propose a variant of the QRM-MLD signal detection method that is used for spatially multiplexed multiple antenna system. The original QRM-MLD signal detection method combines the QR decomposition with the M-algorithm, thereby significantly reduces the prohibitive hardware complexity of the ML signal detection method, still achieving a near ML performance. When the number of transmitter antennas and/or constellation size are increased to achieve higher bit rate, however, its increased complexity makes the hardware implementation challenging. In an effort to overcome this drawback of the original QRM-MLD, a number of variants were proposed. A most strong variant among them, in our opinion, is the ranking method, in which the constellation points are ranked and computation is performed for only highly ranked constellation points, thereby reducing the required complexity. However, the variant using the ranking method experiences a significant performance degradation, when compared with the original QRM-MLD. In this paper, we point out the reasons of the performance degradation, and we propose a novel variant that overcomes the drawbacks. We perform a set of computer simulations to show that the proposed method achieves a near performance of the original QRM-MLD, while its computational complexity is near to that of the QRM-MLD with ranking method.