Elastic optical network modulation format identification method based on KNN

A technology of elastic optical network and modulation format, which is applied in the direction of modulation type recognition, character and pattern recognition, modulation carrier system, etc. It can solve problems such as complex expression and difficult optimization process, and achieve simple and easy-to-implement effects

Active Publication Date: 2019-04-12
上海天域光联通信科技有限公司
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Problems solved by technology

However, the maximum likelihood method requires a complete mathematical description of the opt

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  • Elastic optical network modulation format identification method based on KNN
  • Elastic optical network modulation format identification method based on KNN
  • Elastic optical network modulation format identification method based on KNN

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example 1

[0037] Step 1: Construct training data, send the training data from the sending end of the OFDM signal, and receive the signal at the receiving end of the OFDM signal after being transmitted by the OFDM transmission system;

[0038] Specifically, the construction of training data includes the following steps:

[0039] Carrying out bit loading to each subcarrier of the OFDM signal, wherein the OFDM signal is an OFDM signal of a known modulation format;

[0040] The modulation format of each subcarrier is used as the label of each subcarrier training data, and each subcarrier data and its subcarrier label at the receiving end are used as training samples to obtain training data.

[0041] The obtained training data is sent from the sending end of the OFDM signal, and after being transmitted by the OFDM transmission system, the signal is received at the receiving end of the OFDM signal.

[0042] The data of each sub-carrier is received by the receiving end and used as training da...

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Abstract

The invention relates to an elastic optical network modulation format identification method based on KNN. The method comprises the specific steps of (1), constructing training data, sending the training data from a sending end, and through transmission of an OFDM (Orthogonal Frequency Division Multiplexing) transmission system, receiving signals at a receiving end; (2), carrying out FFT on received signals and carrying out channel estimation and channel balancing, thereby obtaining a series of complex data; (3), extracting real parts of the complex data, thereby obtaining a real part histogram, and preprocessing the histogram, thereby obtaining feature vectors; (4), modeling features through utilization of a KNN algorithm and obtaining a classifier; (5), for newly received data, obtainingdata features of each subcarrier, and carrying out prediction classification on the feature vectors through utilization of a KNN classifier, thereby obtaining a modulation format of the subcarrier; and (6), demapping respective carrier data through utilization of the obtained modulation format, and obtaining original data.

Description

technical field [0001] The invention provides a method for identifying the modulation format of a signal transmitted by O-OFDM using a statistical machine learning method-KNN algorithm, and proposes a low-cost format identification solution for intelligent transmission of an elastic optical network. Background technique [0002] With the rapid development of Internet technology, multimedia services such as voice, video, and high-definition television continue to emerge, and people's demand for network bandwidth capacity has increased dramatically. Orthogonal Frequency Division Multiplexing (OFDM) is a very mature technology in wireless communication. It is applied to such as IEEE802.11G, IEEE802.16, etc. It is a modulation technology with the highest spectrum utilization rate at present. It has high The advantages of data transmission rate, high spectrum utilization and high robustness to spectral dispersion. The basic principle is to divide the high-speed data information ...

Claims

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Application Information

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IPC IPC(8): H04L27/00H04L27/26G06K9/62
CPCH04L27/0012H04L27/2647G06F18/24147G06F18/214
Inventor 张倩武
Owner 上海天域光联通信科技有限公司
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