Flexible optical network time domain equalization method and system based on composite neural network

Abstract

The invention discloses a flexible optical network time domain equalization method and system based on a composite neural network, and belongs to the field of optical fiber communication systems, andthe method comprises the steps: (1) preprocessing a received signal transmitted by a flexible optical network; (2) calculating an amplitude distribution histogram of the preprocessed received signal;(3) inputting the amplitude distribution histogram into a first-stage multi-task neural network classifier, and outputting transmission parameters of the flexible optical network; (4) setting a weightand an offset parameter of a second-stage neural network regression device according to the transmission parameter of the flexible optical network; (5) carrying out time domain equalization on the preprocessed received signal by adopting a second-stage neural network regression device, wherein the number of input neurons of the first-stage multi-task neural network classifier is the same as the number of groups of amplitude histograms, and the number of output neurons of the first-stage multi-task neural network classifier is the same as transmission parameters of the flexible optical network. The time domain equalization method and system disclosed by the invention are wider in application range.

Description

technical field [0001] The invention belongs to the field of optical fiber communication systems, and more specifically relates to a flexible optical network time domain equalization method and system based on a compound neural network. Background technique [0002] In recent years, with the popularization of smart terminals and the development of new network services, network traffic has grown explosively, which has brought enormous pressure on the capacity of communication systems. In order to meet the demand for massive data transmission, on the one hand, it is also necessary to overcome various transmission impairments in the optical fiber communication system and improve the single-fiber transmission capacity; on the other hand, it is also necessary to dynamically allocate network resources according to actual needs, and the corresponding transmission impairment compensation method also needs Adjust accordingly. [0003] In order to improve transmission efficiency, fle...

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Problems solved by technology

[0005] Aiming at the defects of the prior art, the object of the present invention is to provide a flexible optical network time-domain equalization method and system based on a composite neural network. The existing equalization methods can only perform equalization compensation for a certain channel condition. Therefore, It aims to solve the problem that the existing time-domain equalization method has a narrow application range in flexible optical networks

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