Blind equalization and automatic modulation classification based on subspace for subcarrier MPSK optical communications

Abstract

Equalization can compensate channel distortion caused by channel multipath effects, and effectively improve convergent of modulation constellation diagram in optical wireless system. In this paper, the subspace blind equalization algorithm is used to preprocess M-ary phase shift keying (MPSK) subcarrier modulation signal in receiver. Mountain clustering is adopted to get the clustering centers of MPSK modulation constellation diagram, and the modulation order is automatically identified through the k-nearest neighbor (KNN) classifier. The experiment has been done under four different weather conditions. Experimental results show that the convergent of constellation diagram is improved effectively after using the subspace blind equalization algorithm, which means that the accuracy of modulation recognition is increased. The correct recognition rate of 16PSK can be up to 85% in any kind of weather condition which is mentioned in paper. Meanwhile, the correct recognition rate is the highest in cloudy and the lowest in heavy rain condition.

References

[1] PopoolaW. O., GhassemlooyZ., HaasH., LeitgebE., AhmadiV.. IET Communications, 2012, 6: 499

[2] Md. Zoheb Hassan, Md. Jahangir Hossain and Julian Cheng, Exact BER Analysis of Subcarrier QAM and PSK Intensity Modulations in Strong Turbulence, International Conference on Computing, Networking and Communications, Optical and Grid Networking Symposium, 478 (2014).

[3] W. Huang, J. Takayanagi, T. Sakanaka and M. Nakagawa, Atmospheric Optical Communication System Using Subcarrier PSK Modulation, IEEE International Conference on Communications, 1597 (1993).

[4] SongX., YangF., ChengJ., AlouiniM.-S.. Journal of Lightwave Technology, 2015, 33: 161

[5] GaoY. L., CartledgeJ. C., KashiA. S., YamS. S. -H., MatsuiY.. IEEE Photonics Technology Letters, 2017, 9: 35

[6] S. Hossein. Performance of Subcarrier Intensity Modulated FSO Systems over Gamma–Gamma Turbulence Channels with Pointing Errors, Wireless Personal Communications, 1 (2016).

[7] LiqiangH., YahuiY., XiangrongN., JiahuanH.. Journal of Optoelectronics·Laser, 2016, 27: 505

[8] H. Zhu, X. Chen, W. Q. Zhou, Z. Y. Li, X. Zhou and Z. G. Zhangl, A Modified CMA for Blind Equalization and Phase Recovery In Optical Coherent Receivers, Communications and Photonics Conference and Exhibition (ACP), 1 (2009).

[9] Sofien Mhatli; Bechir Nsiri, Mutsam A. Jarajreh, Malek Channoufi and Rabah Attia, Non Linearity Equalization for Coherent Optical OFDM Modem, Science and Information Conference, 660 (2014).

[10] H. Zhang, H. S. Liao and L. Gan, Robust Classification of Quadrature Amplitude Modulation Constellations Based on GMM., IEEE International Conference on Communication Problem–Solving, 546 (2014).

[11] LuS. S., WangW., WangG. Y.. Journal of National University of Defense Technology, 2016, 38: 130

[12] ShenJ. Q., DingZ.. IEEE Transactions on Communications, 2001, 49: 262

[13] M. S. Muhlhaus, M. Oner, O. A. Dobre, H. U. Jkel and F. K. Jondral, A Novel Algorithm for MIMO Signal Classification Using Higher-Order Cumulants, Radio and Wireless Symposium (RWS), 7 (2013).

[14] LinK. L., LinC. T., PalN. R.. IEEE Transactions on Nano-Bioscience, 2010, 9: 278

[15] B. Y. Pratama and R. Sarno, Personality Classification Based on Twitter Text Using Naive Bayes, KNN and SVM, International Conference on Data and Software Engineering, 170 (2015).

[16] BinW., FaliangC., ChunshengL.. Journal of Optoelectronics·Laser, 2016, 27: 625

[17] HarringtonP.Machine Learning in ActionManning Publications Co., 2012,