The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지
DOI QR코드

DOI QR Code

Soft-Decision Algorithm with Low Complexity for MIMO Systems Using High-Order Modulations

고차 변조 방식을 사용하는 MIMO 시스템을 위한 낮은 복잡도를 갖는 연판정 알고리즘

  • Received : 2015.04.07
  • Accepted : 2015.06.09
  • Published : 2015.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based $N_T{\times}N_R$ MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

최적 ML(Maximum Likelihood) 기법 및 sphere decoding(SD), QRM-MLD(QR decomposition with M-algorithm Maximum Likelihood Detection) 기반의 준 최적 검출 기법을 적용한 MIMO(Multiple-Input Multiple-Output) 시스템에서의 LLR(Log Likelihood Ratio) 계산은 변조 차수 및 송/수신 안테나의 수가 증가할수록 그 복잡도가 지수적으로 증가하여 구현 및 성능 면에서 큰 문제점을 야기한다. 본 논문에서는 고차 변조 방식 기반의 $N_T{\times}N_R$ MIMO시스템 수신기의 QRM-MLD 기반 MIMO 검출기에서 연판정 시 아주 낮은 복잡도로 1dB 이내의 ML 검출 기법에 대한 오류 성능 접근도를 갖는 LLR 계산 방법을 제시하고, 컴퓨터 시뮬레이션을 통해 여러 M 값에 대한 MIMO 시스템의 BER(Bit Error Rate) 결과를 도출하고 분석하여 제시된 방법의 유효성을 검증한다.

Keywords

References

  1. Y. S. Cho, J. Kim, W. Y. Yang, and C. G. Kang, MIMO-OFDM Wireless Communications with MATLAB, 1st Ed., Jone Wiley & Sons, 2010.
  2. B. Steingrimsson, Z. Q. Luo, and K. M. Wong, "Soft quasi-maximum-likelihood detection for multile-antenna wireless channels," IEEE Trans. Signal Process., vol. 51, no. 11, pp. 2710-2719, Nov. 2003. https://doi.org/10.1109/TSP.2003.818203
  3. J. Lee, Y. Jang, and D. Yoon, "Approximated soft-decision demapping algorithm for coded 4+12+16 APSK," J. KICS, vol. 37, no. 9, pp. 738-745, Sept. 2012.
  4. M. Zhang and S. Kim, "Performance enhancement by scaling soft bit information of APSK," J. KICS, vol. 38, no. 10, pp. 858-866, Oct. 2013.
  5. I. Kang, Y. Kim, J. Seo, H. Kim, and H. Kim, "Performance analysis of a bit mapper of the dual-polarized MIMO DVB-T2 system," J. KICS, vol. 38, no. 9, pp. 817-825, Sept. 2012.
  6. C. Studer, A. Burg, and H. Bolcskei, "Soft-output sphere decoding: algorithms and VLSI implementation," IEEE J. Select. Areas Commun., vol. 26, no. 2, pp. 290-300, Feb. 2008. https://doi.org/10.1109/JSAC.2008.080206
  7. C. Yoon and H. Lee, "Implementation of low-complexity MIMO detector and efficient soft-output demapper for MIMO-OFDM-based wireless LAN systems," EURASIP J. Wireless Commun. Netw., vol. 143, May 2013.
  8. X. F. Qi and K. Holt, "A lattice-reductionaided soft demapper for high-rate coded MIMO-OFDM systems," IEEE Signal Process. Lett., vol. 14, no. 5, pp. 305-308, May 2007. https://doi.org/10.1109/LSP.2006.888090
  9. B. Yang and J. F. Bohme, "Rotation-based RLS algorithms: Unified derivations, numerical properties, and parallel implementations," IEEE Trans. Signal Process., vol. 40, no. 5, pp. 1151-1167, May 1992. https://doi.org/10.1109/78.134478
  10. B. M. Hochwald and S. Brink, "Achieving near-capacity on a multiple-antenna channel," IEEE Trans. Commun., vol. 51, no. 3, pp. 389-399, Mar. 2003. https://doi.org/10.1109/TCOMM.2003.809789

Cited by

  1. 밀리미터파 5G 이동통신을 위한 물리계층 모뎀의 구현 vol.41, pp.1, 2015, https://doi.org/10.7840/kics.2015.41.1.51
  2. 중앙 집중형 밀리미터파 기반 다중 스팟 빔 셀룰러 시스템 vol.41, pp.3, 2015, https://doi.org/10.7840/kics.2016.41.3.285