@article{Zhang_Gadekallu_2022, title={Digital interference signal filtering on laser interface for optical fiber communication }, volume={10}, url={https://publications.eai.eu/index.php/sis/article/view/2589}, DOI={10.4108/eetsis.v10i1.2589}, abstractNote={<p>INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output</p><p>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.</p><p>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.</p><p>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.</p><p>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.</p>}, number={2}, journal={EAI Endorsed Transactions on Scalable Information Systems}, author={Zhang, Shengnan and Gadekallu, Thippa Reddy}, year={2022}, month={Nov.}, pages={e14} }