Wuhan University Journal of Natural Sciences

, Volume 24, Issue 5, pp 431–434 | Cite as

Low Complexity MMSE-SQRD Signal Detection Based on Iteration

  • Di Wu
  • Guobao RuEmail author
  • Liangcai Gan
  • Xuechun Yu
  • Qi Liu
Information Technology


Aiming at the problem of high computational complexity of Vertical-BLAST (V-BLAST) algorithm in Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system signal detection, this paper first uses Sorted QR Decomposition (SQRD) iterative operation instead of matrix inversion to reduce the computational complexity of the algorithm, and then considering that the algorithm is greatly affected by noise, Minimum Mean Square Error (MMSE) criterion is used to weaken the noise effect. At the same time, in order to reduce the noise and computational complexity, MMSE and SQRD are combined, which can not only reduce the noise and computational complexity, but also obtain the sub-optimal detection order, thus improving the detection performance of the MIMO-OFDM system. Finally, the numerical simulation of the MMSE-SQRD detection algorithm is carried out. The results show that the Eb/No of MMSE-SQRD algorithm is 2 dB greater than that of the MMSE algorithm and the computational complexity is O(N T 3 ) under the conditions that NT = NR = 2 and the BER is 10−2. The detection algorithm satisfies the demand of short wave and wideband wireless communication.

Key words

Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) Minimum Mean Square Error (MMSE) Sorting Orthogonal-Triangular Decoding (SQRD) algorithm the MMSE-SQRD algorithm 

CLC number

TP 911.3 


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  1. [1]
    Wang Y G, Zhou Y J, Gui T, et al. SEFDM based spectrum compressed VLC system using RLS time-domain channel estimation and ID-FSD hybrid decoder [C]// 42-nd European Conference on Optical Communication, ECOC 2016. Piscataway: IEEE, 2016: 18–22.Google Scholar
  2. [2]
    Huang X X, Shi J Y, Li J H, et al. 750 Mbit/s visible light communications employing 64 QAM-OFDM based on amplitude equalization circuit [C]// The Opt Fiber Commun Conf. Piscataway: IEEE, 2015: Tu2G.1.Google Scholar
  3. [3]
    Gamba M T, Masera G. Look-ahead sphere decoding: Algorithm and VLSI architecture [J]. IET Communications, 2011, 5(9): 1275–1285.CrossRefGoogle Scholar
  4. [4]
    Hoydis J, Ten Brink S, Debbah M. Massive mimo in the ul/dl of cellular networks: How many antennas do we need? [J]. IEEE J Sel Areas Commun, 2013, 31(2): 160–171.CrossRefGoogle Scholar
  5. [5]
    Schmitz A, Schinnenburg M, Gross J, et al. Channel Modeling [M]. Heidelberg: Springer-Verlag, 2010.CrossRefGoogle Scholar
  6. [6]
    Yue D W, Zhang Y, Jia Y N. Beamforming based on specular component for massive MIMO systems in Ricean fading [J]. IEEE Wireless Commun Letters, 2015, 4(2): 1–4.CrossRefGoogle Scholar
  7. [7]
    Rusek F, Persson D, Lau B K, et al. Scaling up MIMO: Opportunities and challenges with very large arrays [J]. IEEE Signal Process, 2013, 30(1): 40–60.CrossRefGoogle Scholar
  8. [8]
    Girnyk M, Vehkapera M, Rasmussen L. Large-system analysis of correlated MIMO multiple access channels with arbitrary signaling in the presence of interference [J]. IEEE Trans Wireless Commun, 2014, 13(4): 2060–2073.CrossRefGoogle Scholar
  9. [9]
    Zhong W, Lu A A, Gao X Q. Modified MMSE SQRD based detection for coded MIMO-OFDM systems [J]. IEICE Trans Commun, 2013, 96(3): 830–835.CrossRefGoogle Scholar
  10. [10]
    Liu Y S, Tan Z H, Hu H J, et al. Channel estimation for OFDM [J]. IEEE Commun Surveys Tuts, 2014, 16(4): 1891–1908.CrossRefGoogle Scholar

Copyright information

© Wuhan University and Springer-Verlag GmbH Germany 2019

Authors and Affiliations

  • Di Wu
    • 1
  • Guobao Ru
    • 1
    Email author
  • Liangcai Gan
    • 1
  • Xuechun Yu
    • 1
  • Qi Liu
    • 1
  1. 1.School of Electronic InformationWuhan UniversityWuhan, HubeiChina

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