Digital interference signal filtering on laser interface for optical fiber communication

Shengnan Zhang; Thippa Reddy Gadekallu

doi:10.4108/eetsis.v10i1.2589

Authors

Shengnan Zhang Nanchang Jiao Tong Institute, Nanchang, China
Thippa Reddy Gadekallu Vellore Institute of Technology University

DOI:

https://doi.org/10.4108/eetsis.v10i1.2589

Keywords:

digital filtering technology, optical fiber communication, laser interface, interference signal filtering, wavelet denoising, least square algorithm

Abstract

INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output

OBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is designed.

METHODS: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be achieved.

RESULTS: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the network.

CONCLUSION: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.

References

He, Y., Li, M., Shu, Y., Ning, Q., & Luo, A. (2021). Generation of h-shaped pulse rains induced by intracavity fabry–perót filtering in a fiber laser. Optical Fiber Technology, 61(14), 102453.

Ghosh, S., Kumar, H., Mukhopadhyay, B., & Chang, G. E. (2021). Design and modeling of high-performance dbr-based resonant-cavity-enhanced gesn photodetector for fiber-optic telecommunication networks. IEEE Sensors Journal, 21(8), 9900-9908.

Son, V. V., Duong, D. T., Hoang, T. M., Quan, D. T., & Hiep, P. T. (2020). Analysing outage probability of linear and non-linear rf energy harvesting of cooperative communication networks. IET Signal Processing, 14(8), 541-550.

Gao, Q., Qaraqe, K., & Serpedin, E. (2020). Rotated color shift keying for visible light communications with signal-dependent noise. IEEE Communications Letters, 24(4), 844-848.

Kaliteevskiy, N. A., Ivanov, V., Sterlingov, P., Downie, J., & Hurley, J. (2020). Transponder implementation penalty-accounted gaussian-noise-based performance modeling of fiber-optic transmission systems. Journal of Lightwave Technology, 38(8), 2253-2261.

Pan, X., Wang, X., Tian, B., Wang, C., & Guizani, M. (2021). Machine-learning-aided optical fiber communication system. IEEE Network, 35(4), 136-142.

Li, G., Hu, F., Zou, P., Wang, C, Lin, G. R., & Chi, N. (2020). Advanced modulation format of probabilistic shaping bit loading for 450-nm gan laser diode based visible light communication. Sensors, 20(21), 1-12.

Verolet, T., Aubin, G., Lin, Y., Browning, C., & Ramdane, A. (2020). Mode locked laser phase noise reduction under optical feedback for coherent dwdm communication. Journal of Lightwave Technology, 38(20), 5708-5715.

Zhang N., Yang Y., Chen T., et al. (2021). Research on Optimization Policy Routing Technology of Optical Fiber Communication Network[J]. Journal of Physics: Conference Series, 1746(1):012084 .

Yu H., Li P., Zhang L., et al. (2020). Application of optical fiber nanotechnology in power communication transmission[J]. AEJ - Alexandria Engineering Journal, 59(6):5019-5030.

Zoofaghari, M., Arjmandi, H., Etemadi, A., & Balasingham, I. (2021). A semi-analytical method for channel modeling in diffusion-based molecular communication networks. IEEE Transactions on Communications, 69(6), 3957-3970.

Wang, F., & Li, H. (2021). Power allocation for coexisting multicarrier radar and communication systems in cluttered environments. IEEE Transactions on Signal Processing, 22(3), 1-10.

You S., Wang H., He Y., et al. Frequency Domain Design Method of Wavelet Basis Based on Pulsar Signal[J]. Journal of Navigation, 2020, 73(6):1223-1236.

Chen, G., Wang, J., Zuo, L., Zhao, D., & Wen, Y. (2020). Two-stage clutter and interference cancellation method in passive bistatic radar. IET Signal Processing, 14(6), 342-351.

Dehkordi, J. S., & Tralli, V. (2020). Interference analysis for optical wireless communications in network-on-chip (noc) scenarios. IEEE Transactions on Communications, 68(3), 1662-1674.

Wang Y., Jiang Z. (2020). Miniaturised multi‐channel millimetre wave filter bank[J]. Electronics Letters, 56(24):1328-1330.

Mohajer, S., Bergel, I., & Caire, G. (2020). Cooperative wireless mobile caching: a signal processing perspective. IEEE Signal Processing Magazine, 37(2), 18-38.

Lin, X., M., Liu, S.,Shi, Z., L. (2022).Multi-Sensor Signal Denoising Based on Adaptive Kalman Filter. Computer Simulation,39(2):507-511.

Yang J, Zhou C. A fault feature extraction method based on LMD and wavelet packet denoising[J]. Coatings, 2022, 12(2): 156.

Liu, S., Chen, P., Woźniak, M. (2022) Image Enhancement-Based Detection with Small Infrared Targets. Remote Sensing, 14, 3232.

Liu, S., Bai, W., Srivastava, G. et al. (2020) Property of Self-Similarity Between Baseband and Modulated Signals. Mobile Networks & Applications, 25(4): 1537-1547.