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SDR 시스템에서 GPU를 사용한 Lattice Reduction-aided 검출기 구현

mplementation of Lattice Reduction-aided Detector using GPU on SDR System

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초록

This paper presents an implementation of Lattice Reduction (LR)-aided detector for Multiple-Input Multiple-Output (MIMO) system using Graphics Processing Unit (GPU). GPU is a parallel processor which has a number of Arithmetic Logic Units (ALUs), thus, it can minimize the operation time of LR algorithm through the parallelization using multiple threads in the GPU. Through the implemented LR-aided detector, we verify that the LR-aided detector operates a lot faster than Maximum Likelihood (ML) detector. The implemented LR-aided detector has been applied to WiMAX system to show the feasibility of its real-time processing. In addition, we demonstrate that the processing time can be reduced at the cost of 3dB SNR loss by limiting the repeating loop in Lenstra-Lenstra-Lovasz (LLL)algorithm which is frequently used in LR-aided detector.

Abstract

This paper presents an implementation of Lattice Reduction (LR)-aided detector for Multiple-Input Multiple-Output (MIMO) system using Graphics Processing Unit (GPU). GPU is a parallel processor which has a number of Arithmetic Logic Units (ALUs), thus, it can minimize the operation time of LR algorithm through the parallelization using multiple threads in the GPU. Through the implemented LR-aided detector, we verify that the LR-aided detector operates a lot faster than Maximum Likelihood (ML) detector. The implemented LR-aided detector has been applied to WiMAX system to show the feasibility of its real-time processing. In addition, we demonstrate that the processing time can be reduced at the cost of 3dB SNR loss by limiting the repeating loop in Lenstra-Lenstra-Lovasz (LLL)algorithm which is frequently used in LR-aided detector.

참고문헌 (11)

  1. M. Mueck, "ETSI Reconfigurable Radio Systems: Status and Future Directions on Software Defined Radio and Cognitive Radio Standards", IEEE Communications Magazine, pp.78~86 (2010)
  2. S. Haykin, "Modern Wireless Communications" (2005), Pearson Prentice Hall
  3. S. Verdu, "Multiuser Detection" (1998), Cambridge Univ
  4. 홍경화, "WiBro 다운링크 환경에서 여러 가지 MIMO 기법의 성능 및 연산량에 대한 비교 연구", (사)디지털산업정보학회 논문지, 4(2), pp.49~55 (2008), (사)디지털산업정보학회
  5. John Proakis, "Digital communications" (2000), McGraw- Hill
  6. Drink Wübben, "Near-Maximum- Likelihood Detection of MIMO Systems using MMSE-based Lattice-Reduction", IEEE International Conference on Communications, pp.798~802 (2004)
  7. Huan Yao, "Lattice-Reduction- Aided Detectors for MIMO Communication Systems", Global Telecommunication Conference, 통권 : 1, pp.424~428 (2002)
  8. A. K. Lenstra, "Factoring Polynomials with Rational Coefficients", Math. Ann, 261, pp.515~534 (1982)
  9. June Kim, "Implementation of an SDR System Using Graphics Processing Unit", Communications Magazine of the IEEE, 48 (2010)
  10. Jaehyuk Ju, "Implementation of an SDR platform using GPU and its application to 2x2 MIMO WiMax system", Wireless Innovation Forum, pp.341~345 (2010)
  11. NVIDIA Corporation, "CUDA C Programming Guide" (2010)

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