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

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Abstract

As the optical communication technology advances, vortex beam with orbital angular momentum (OAM) has gained wide attention due to its potential to significantly increase the channel capacity. Under the influence of atmospheric turbulence, there are still challenging problems in the OAM multiplexing system. To the best of our knowledge, in this paper one multiple-input-multiple-output (MIMO) detection technology named K-best detection, is first applied to the OAM multiplexing system. Numerical simulation results indicate the proposed solution enhances the performance of the optical communication system compared with data-aided least mean square (DA-LMS) and minimum mean squared error (MMSE) detection. Furthermore, with MMSE sorted QR decomposition (MMSE-SQRD) preprocessing, the performance of K-best detection can be further improved. When C 2n = 1×10−14, about 4.4 dB signal-to-noise ratio (SNR) gain can be obtained by preprocessing at k = 2 while the complexity is not significantly increased. Computational complexity is also analyzed in this paper, results show that K-best detection with winner path extension (WPE) algorithm can achieve 43% system complexity reduction, achieving a compromise between performance and complexity in K-best detection.

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Acknowledgements

This work was supported in part by National Key R&D 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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Correspondence to Chuan Zhang or Zaichen Zhang.

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Ge, Y., Wu, L., Zhang, C. et al. Orbital angular momentum multiplexing communication system over atmospheric turbulence with K-best detection. Sci. China Inf. Sci. 64, 192302 (2021). https://doi.org/10.1007/s11432-019-2918-7

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  • DOI: https://doi.org/10.1007/s11432-019-2918-7

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