SCIENCE CHINA Information Sciences, Volume 64 , Issue 9 : 192302(2021) https://doi.org/10.1007/s11432-019-2918-7

Orbital angular momentum multiplexing communication system over atmospheric turbulence with K-best detection

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  • ReceivedOct 24, 2019
  • AcceptedMay 12, 2020
  • PublishedAug 9, 2021



This work was supported in part by National Key RD Program of China (Grant No. 2020YFB2205503), in part by National Natural Science Foundation of China (NSFC) (Grant Nos. 61871115, 61501116), in part by Jiangsu Provincial NSF for Excellent Young Scholars (Grant No. BK20180059), in part by Six Talent Peak Program of Jiangsu Province (Grant No. 2018-DZXX-001), and in part by Fundamental Research Funds for the Central Universities.


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  • Figure 1

    (Color online) Vortex optical multiplexing/demultiplexing model.

  • Figure 2

    Comparison of (a) crosstalk caused by atmospheric turbulence and (b) MIMO channel model.

  • Figure 3

    (Color online) Channel matrix of OAM-DM communication system with different $C_n^2$ values. (a) $C_n^2=1\times10^{-14}$;protect łinebreak (b) $C_n^2=1\times10^{-15}$; (c) $C_n^2=1\times10^{-16}$.

  • Figure 4

    (Color online) K-best algorithm tree search schematic.

  • Figure 5

    (Color online) Comparison of K-best detection, direct detection, DA-LMS and MMSE results under the conditions of (a) $C_n^2=1\times~10^{-14}$ (strong turbulence) and (b) $C_n^2=1\times~10^{-15}$ (weak turbulence).

  • Figure 6

    (Color online) Comparison of K-best detection with/without WPE results under the conditions of (a) $C_n^2=1\times~10^{-14}$(strong turbulence) and (b) $C_n^2=1\times~10^{-15}$(weak turbulence).

  • Figure 7

    (Color online) Comparison of K-best detection with/without MSP results under the conditions of (a) $C_n^2=1\times~10^{-14}$ (strong turbulence) and (b) $C_n^2=1\times~10^{-15}$ (weak turbulence).

  • Figure 8

    (Color online) Comparison of the trade-off between complexity and performance for different MIMO equalization algorithms. (a) $C_n^2=1\times10^{-14}$; (b) $C_n^2=1\times10^{-15}$.

  • Table 1  

    Table 1Comparison of computational complexity for different detection algorithms

    MethodComplexity order
    MMSE[30]CE $m^2~l_{\rm~pilot}$
    Detection $m^3+m^2~l_{\rm~data}$
    Traditional K-bestCE+QRD $m^2~l_{\rm~pilot}+m^3+m^2$
    Tree search $k\sqrt{q}(m^2+m\log_2~{k\sqrt{q}})l_{\rm~data}$
    K-best with MSPCE+MSP $m^2~l_{\rm~pilot}+m^3+m^2+m\log_{2}~m$
    Tree search $k\sqrt{q}(m^2+m\log_2~{k\sqrt{q}})l_{\rm~data}$
    K-best with WPECE+QRD $m^2~l_{\rm~pilot}+m^3+m^2$
    Tree search $k(m^2+mk\log_2~k)l_{\rm~data}$

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