• Title/Summary/Keyword: 코딕

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A Low-complexity Mixed QR Decomposition Architecture for MIMO Detector (MIMO 검출기에 적용 가능한 저 복잡도 복합 QR 분해 구조)

  • Shin, Dongyeob;Kim, Chulwoo;Park, Jongsun
    • Journal of IKEEE
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    • v.18 no.1
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    • pp.165-171
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    • 2014
  • This paper presents a low complexity QR decomposition (QRD) architecture for MIMO detector. In the proposed approach, various CORDIC-based QRD algorithms are efficiently combined together to reduce the computational complexity of the QRD hardware. Based on the computational complexity analysis on various QRD algorithms, a low complexity approach is selected at each stage of QRD process. The proposed QRD architecture can be applied to any arbitrary dimension of channel matrix, and the complexity reduction grows with the increasing matrix dimension. Our QR decomposition hardware was implemented using Samsung $0.13{\mu}m$ technology. The numerical results show that the proposed architecture achieves 47% increase in the QAR (QRD Rate/Gate count) with 28.1% power savings over the conventional Householder CORDIC-based architecture for the $4{\times}4$ matrix decomposition.

High-Performance Givens Rotation-based QR Decomposition Architecture Applicable for MIMO Receiver (MIMO 수신기에 적용 가능한 고성능 기븐스 회전 기반의 QR 분해 하드웨어 구조)

  • Yoon, Ji-Hwan;Lee, Min-Woo;Park, Jong-Sun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.3
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    • pp.31-37
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    • 2012
  • This paper presents an efficient hardware architecture to enable the high-speed Givens rotation-based QR decomposition. The proposed architecture achieves a highly parallel givens rotation process by maximizing the number of pivots selected for parallel zero-insertions. Sign-select lookahed (SSL)-CORDIC is also efficiently used for the high-speed givens rotation. The performance of QR decomposition hardware considerably increases compared to the conventional triangular systolic array (TSA) architecture. Moreover, the circuit area of QR decomposition hardware was reduced by decreasing the number of flip-flops for holding the pre-computed results during the decomposition process. The proposed QR decomposition hardware was implemented using TSMC $0.25{\mu}m$ technology. The experimental results show that the proposed architecture achieves up to 70 % speed-up over the TACR/TSA-based architecture for the $8{\times}8$ matrix decomposition.