CN114584212B - Modulation format and optical signal to noise ratio monitoring method for feature similarity analysis - Google Patents
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- H—ELECTRICITY
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- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
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- H04B10/516—Details of coding or modulation
- H04B10/548—Phase or frequency modulation
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Abstract
The invention discloses a modulation format and optical signal to noise ratio monitoring method for feature similarity analysis, which comprises the following steps ofEThrough preprocessing, power signals are calculatedPAcquiring intensity characteristics and constructing an intensity histogram; extracting the outer envelope of the histogram to obtain a smoothed envelope, comparing the smoothed envelope with the intensity envelopes of different modulation formats in a signal monitoring original library from low signal to noise ratio to high signal to noise ratio in sequence according to 5dB intervals, and determining the modulation format corresponding to the maximum degree of identity as the signalECompleting modulation format monitoring operation; according to the determined modulation format information, further comparing the intensity envelope with the intensity envelope of the modulation format corresponding to the signal monitoring original library from low signal to noise ratio to high signal to noise ratio according to the interval of 1dB, and determining the optical signal to noise ratio corresponding to the maximum discrimination as the signalEAnd (3) optical signal-to-noise ratio, and finishing optical signal-to-noise ratio monitoring. The invention can realize the monitoring of various modulation formats and the monitoring of the optical signal to noise ratio in a large range.
Description
Technical Field
The invention relates to the technical field of optical transmission networks, in particular to a modulation format and optical signal to noise ratio monitoring method for feature similarity analysis.
Background
Currently, the age of rapid development of information technology has been entered, and various emerging network services including wide-ranging applications of internet+, cloud computing, telemedicine and the like have led to a rapid increase in global traffic. The next generation optical network is expected to have larger transmission capacity and more flexible resource scheduling capability to meet the requirement of rapid increase of data traffic. The focus of the next generation optical network is to dynamically change the characteristics of the signal at the transmitting end according to different service requirements of the transmission link, such as: modulation format, transmission baud rate, number of carriers, center wavelength of transmission channel, etc. Therefore, it is important to autonomously monitor the correlation characteristics of the transmission signal at the receiving end. The modulation format identification is the most important performance characteristic, and the correct acquisition of the modulation format information can help the subsequent digital signal processing module to select the corresponding optimal algorithm, so that the demodulation performance of the system is further improved. In addition, the optical signal to noise ratio of another important parameter in the transmission link plays a vital role in automatic fault detection and diagnosis of transmission service quality. The osnr is directly related to the bit error rate of the transmitted signal and to the signal quality. Therefore, the intelligent receiver of the next generation optical network is expected to be able to intelligently and autonomously identify various modulation formats and osnr information of unknown signals without any a priori information.
Recently, various modulation format monitoring techniques have been proposed. In 2010, researchers at the university of Danish technology proposed using the Kmeans algorithm to identify the cluster point corresponding to the modulation format constellation, which required the constellation after compensating the frequency offset and the laser phase noise after the carrier phase recovery algorithm. Since the carrier phase recovery algorithm is also a modulation format related algorithm, this method has certain limitations. In 2014, researchers at the university of Zhongshan propose to use the histogram feature information of the signals to perform modulation format recognition, and mainly calculate the average power of the received signals, so that the method is simple in calculation, but the judgment is troublesome, and most importantly, the premise of applying the method is that the method must be applied after polarization demultiplexing; in 2017, researchers at the university of Beijing mail have proposed using coherent receivers to obtain eye diagrams of different modulation formats, using artificial neural networks to extract features from the eye diagrams, and then identifying and judging the 6 modulation formats to obtain the corresponding modulation formats. However, the artificial neural network must train the eye-diagram features in advance. In 2018, researchers at southwest university of traffic put forward a modulation format identification method based on a stokes space two-dimensional plane, and the method can identify various modulation formats and has a certain anti-interference performance on various effects at the same time. In 2018, researchers at the university of Beijing post electronics proposed stokes 2-dimensional plane based recognition, three-dimensional stokes space was projected onto a plane, and features were automatically extracted and recognized using convolutional neural networks.
In addition, the optical signal to noise ratio monitoring technology is also widely focused and researched by researchers at home and abroad. Researchers at the karl schiryurt institute of technology in 2012 put forward based on the error vector magnitude and monitor the osnr by calculating the EVM of the constellation after carrier phase recovery. Researchers at Beijing university of post and email utilize the second order statistical moment and the fourth order statistical moment of the received signal to separate the signal power and the noise power to obtain the optical signal to noise ratio, but the scheme cannot finish the monitoring of the optical signal to noise ratio in a nonlinear environment. In 2018, researchers at Beijing university of science industry monitor the original two paths of IQ signals as characteristics by using an LSTM neural network, and the scheme is simple and convenient to realize without any signal processing. In 2019, researchers at southwest university of traffic put forward a stokes amplitude distribution-based scheme, which takes amplitude histograms on the S1 and S2 axes in stokes space as features, and inputs the amplitude histograms into a DNN neural network to monitor the osnr, and achieves higher accuracy.
Disclosure of Invention
The invention provides a modulation format and optical signal to noise ratio monitoring method capable of realizing identification of multiple modulation formats and monitoring of a larger range of optical signal to noise ratio based on a feature similarity analysis idea.
The technical scheme adopted by the invention is as follows:
a modulation format and optical signal to noise ratio monitoring method for feature similarity analysis comprises the following steps:
step 1: after the signal is transmitted through the optical fiber, a receiving end receives the signal E, and a signal D is obtained through pretreatment;
step 2: calculating a power signal P according to the signal D obtained in the step 1, obtaining an intensity characteristic and constructing an intensity histogram;
step 3: extracting an outer envelope of the intensity histogram according to the intensity histogram constructed in the step 2, and reducing noise jitter on the envelope by a smoothing filtering method to obtain a smoothed intensity envelope;
step 4: repeating the steps 1, 2 and 3, sequentially storing the intensity envelopes of the signals with different modulation formats from low signal to noise ratio to high signal to noise ratio, and constructing a complete signal monitoring original library;
step 5: comparing the intensity envelopes obtained in the step 3 with the intensity envelopes of different modulation formats in the signal monitoring original library constructed in the step 4 from low signal to noise ratio to high signal to noise ratio according to coarse steps of 5dB intervals, determining the modulation format corresponding to the obtained maximum similarity as the modulation format of the signal E, and completing the modulation format monitoring operation;
step 6: according to the modulation format information determined in the step 5, sequentially comparing the intensity envelope of the step 3 with the intensity envelope of the modulation format corresponding to the signal monitoring original library constructed in the step 4 from a low signal to noise ratio to a high signal to noise ratio according to the fine step length of 1dB, determining the optical signal to noise ratio corresponding to the obtained maximum similarity as the optical signal to noise ratio of the signal E, and completing the optical signal to noise ratio monitoring;
further, the preprocessing in step 1 includes resampling, IQ mismatch equalization, dispersion compensation, and clock recovery performed sequentially.
Further, the power signal P calculation method in step 2 is as follows:
P＝|D| 2
wherein: d 2 Is a power calculation for signal D.
Further, the method for calculating the outer envelope of the extracted intensity histogram in the step 3 is as follows:
[a，b]＝hist(P，bins)
wherein: a is the intensity histogram envelope of the power signal P; b is the group distance value of the intensity histogram; p is a power signal; bin is the group pitch number of the intensity histogram.
Further, the smoothing filtering method in the step 3 is one of fourier series fitting, polynomial fitting and moving average.
Furthermore, the modulation format monitoring required to be realized in the step 5 and the optical signal to noise ratio monitoring required to be realized in the step 6 are required to be realized in an auxiliary way through a feature similarity comparison method;
the similarity comparison method is one of Euclidean distance, manhattan distance and Chebyshev distance;
the similarity calculation formula is as follows:
wherein: d, d ts The similarity of the intensity envelope in the original library is monitored for the test signal intensity envelope and the signal; x is x tk Kth data that is a test signal strength envelope; x is x sk Monitoring the kth data of the intensity envelope in the raw library for the signal; m is a variable parameter, expressed as Manhattan distance when m is 1, as Euclidean distance when m is 2, and as Chebyshev distance when m tends to infinity.
Furthermore, the method for monitoring the modulation format and the optical signal to noise ratio of the feature similarity analysis further comprises the steps of sequentially carrying out frequency offset estimation and carrier phase recovery after determining the modulation format and the optical signal to noise ratio of the signals, so as to realize final mediation of the signals.
The beneficial effects of the invention are as follows:
(1) The invention can realize the monitoring of various modulation formats of the modulation signals, including various phase modulation formats, various quadrature amplitude modulation formats and the like;
(2) Aiming at each modulation format signal, the invention can realize the monitoring of the optical signal to noise ratio in a large range;
(3) The invention can directly use the receiver of the transmission system to modulate signals without additional auxiliary equipment;
(4) The method only needs to calculate the intensity envelope characteristics of the signals and calculate the similarity with the envelope characteristics in the original library, so that the complexity is low;
(5) The invention can realize the monitoring of modulation format information and optical signal to noise ratio in the optical transmission system with various transmission services, various transmission wavelengths, various fiber cores, various modes, various polarization states and various modulation formats.
Drawings
Fig. 1 is a signal modulation format and osnr monitoring process in embodiment 1 of the present invention.
FIG. 2 is a flow chart of the monitoring method of the present invention.
Fig. 3 is a histogram of the intensity of different modulation format signals under different osnr conditions in the present invention.
FIG. 4 illustrates different modulation format recognition rates according to the present invention.
Fig. 5 is a diagram showing the osnr monitoring results of signals with different modulation formats according to the present invention: (a) monitoring results of osnr of QPSK; (b) 16QAM osnr monitoring results; (c) monitoring the optical signal-to-noise ratio of 64 QAM.
Detailed Description
The present invention will now be further described with reference to the accompanying drawings and specific examples, which are not intended to limit the scope of the invention.
A modulation format and optical signal to noise ratio monitoring method for feature similarity analysis comprises the following steps: step 1: after the signal is transmitted through an optical fiber, a receiving end receives the signal E, and pre-processes such as resampling, IQ mismatch equalization, dispersion compensation, clock recovery and the like are sequentially carried out to obtain a signal D;
step 2: calculating a power signal P according to the signal D obtained in the step 1, obtaining an intensity characteristic and constructing an intensity histogram;
the power signal P has the following calculation formula:
P＝|D| 2
wherein: d 2 A power calculation formula for signal D;
step 3: extracting an outer envelope of the intensity histogram according to the intensity histogram constructed in the step 2, and adopting a Fourier series fitting, polynomial fitting, sliding average and other smoothing filtering methods to reduce noise jitter on the envelope so as to obtain a smoothed intensity envelope;
the calculation formula of the extracted intensity histogram envelope is as follows:
[a，b]＝hist(P，bins)
wherein: a is the intensity histogram envelope of the power signal P; b is the group distance value of the intensity histogram; p is a power signal; bin is the group distance number of the intensity histogram;
step 4: repeating the steps 1, 2 and 3, sequentially storing the intensity envelopes of the signals with different modulation formats from low signal to noise ratio to high signal to noise ratio, and constructing a complete signal monitoring original library;
step 5: comparing the intensity envelopes obtained in the step 3 with the intensity envelopes of different modulation formats in the signal monitoring original library constructed in the step 4 from low signal to noise ratio to high signal to noise ratio according to coarse steps of 5dB intervals, determining the modulation format corresponding to the obtained maximum similarity as the modulation format of the signal E, and completing the modulation format monitoring operation;
the similarity comparison method can be one of Euclidean distance, manhattan distance and Chebyshev distance; the similarity calculation formula is as follows:
wherein: d, d ts The similarity of the intensity envelope in the original library is monitored for the test signal intensity envelope and the signal; x is x tk Kth data that is a test signal strength envelope; x is x sk Monitoring the kth data of the intensity envelope in the raw library for the signal; m is a variable parameter, expressed as Manhattan distance when m is 1, as Euclidean distance when m is 2, and as Chebyshev distance when m tends to infinity;
step 6: according to the modulation format information determined in the step 5, sequentially comparing the intensity envelope of the step 3 with the intensity envelope of the modulation format corresponding to the signal monitoring original library constructed in the step 4 from a low signal to noise ratio to a high signal to noise ratio according to the fine step length of 1dB, determining the optical signal to noise ratio corresponding to the obtained maximum similarity as the optical signal to noise ratio of the signal E, and completing the optical signal to noise ratio monitoring;
and after the modulation format and the optical signal to noise ratio of the signal are determined, frequency offset estimation and carrier phase recovery are sequentially carried out, so that final modulation of the signal is realized.
Examples
As shown in fig. 1, by a transmitter 101 of one or N wavelengths (traffic) 1 ～101 N Modulating an intensity modulation/quadrature amplitude modulation (mPAM/mQAM) signal; through one or N wavelength division multiplexer 102 1 ～102 N Coupling the transmitted signals of multiple wavelengths (traffic) into a mode division multiplexer 103 through one or N lengths of optical fiber 104 1 ～104 N Transmitting, the corresponding transmission loss being determined by one or N optical amplifiers 105 1 ～105 N Compensating; the final transmission signal is passed through a mode de-multiplexer (106) to separate the multiple mode signals, and then through one or N wave de-multiplexers 107 1 ～107 N Signals of multiple wavelengths are split and then enter the receiver 108 1 ～108 N Performing corresponding digital-to-analog conversion, digital signal processing and other operations; the invention monitors modulation format and optical signal to noise ratio in the receiver.
The detailed process is shown in fig. 2, at the receiver 107 1 ～107 N The signal is digital-to-analog converted to a digital signal. The received digital signal is subjected to signal preprocessing such as resampling, IQ mismatch equalization, dispersion compensation, clock recovery and the like. And calculating a power signal P by using the preprocessed signal D, acquiring an intensity characteristic and constructing an intensity histogram. Extracting an outer envelope of the intensity histogram, and reducing noise jitter on the envelope by adopting a smoothing filtering method to obtain a smoothed intensity envelope; intensity envelope from low signal-to-noise ratio to different modulation formats in signal monitoring raw libraryAnd (3) sequentially comparing the characteristic similarity according to the coarse step length (5 dB intervals) by the high signal-to-noise ratio, determining the modulation format corresponding to the acquired maximum similarity as the modulation format of the signal E, and completing the modulation format monitoring operation. And according to the determined modulation format information, further comparing the intensity envelope with the intensity envelope of the modulation format corresponding to the signal monitoring original library from low signal to noise ratio to high signal to noise ratio according to the fine step length (1 dB interval), determining the optical signal to noise ratio corresponding to the obtained maximum similarity as the optical signal to noise ratio of the signal E, and completing the optical signal to noise ratio monitoring.
Fig. 3 shows intensity histograms for different modulation format signals under different osnr conditions in the embodiment. The intensity histograms of the three modulation format signals of QPSK, 16QAM, and 64QAM are illustrated as different, and as the osnr increases, the intensity histogram envelope of the same modulation format signal also varies. Therefore, the invention can realize the distinction between the optical signal-to-noise ratio and the modulation format signal by comparing the difference of the outer envelopes of the intensity histograms.
The correct recognition rate of the modulation formats QPSK, 16QAM and 64QAM under different signal-to-noise ratio conditions is shown in fig. 4. It can be found that QPSK can achieve 100% recognition rate within the range of 10 dB-30 dB, 16QAM can achieve 100% recognition rate within the range of not less than 17dB of optical signal to noise ratio, and 64QAM can achieve 100% recognition rate within the range of not less than 22dB of optical signal to noise ratio. The osnr required for proper identification of all three modulation formats is less than or close to the osnr corresponding to the 7% fec threshold.
Fig. 5 shows the osnr monitoring results of signals of different modulation formats according to the embodiment: the optical signal-to-noise ratio monitoring result of QPSK in the figure (a); (b) 16QAM osnr monitoring results; (c) monitoring the optical signal-to-noise ratio of 64 QAM. The monitoring method can realize that the average error of optical signal to noise ratio monitoring is lower than 2dB in all three modulation format signals, and can be proved to have certain practicability.
The monitoring method can be suitable for optical transmission systems with various transmission services, various transmission wavelengths, various fiber cores, various modes, various polarization states and various modulation formats, and can realize the monitoring of modulation format information and optical signal to noise ratio.
Claims (8)
1. The method for monitoring the modulation format and the optical signal to noise ratio of the feature similarity analysis is characterized by comprising the following steps of:
step 1: after the signal is transmitted through the optical fiber, a receiving end receives the signal E, and a signal D is obtained through pretreatment;
step 2: calculating a power signal P according to the signal D obtained in the step 1, obtaining an intensity characteristic and constructing an intensity histogram;
step 3: extracting an outer envelope of the intensity histogram according to the intensity histogram constructed in the step 2, and reducing noise jitter on the envelope by a smoothing filtering method to obtain a smoothed intensity envelope;
step 4: repeating the steps 1, 2 and 3, sequentially storing the intensity envelopes of the signals with different modulation formats from low signal to noise ratio to high signal to noise ratio, and constructing a complete signal monitoring original library;
step 5: comparing the intensity envelopes obtained in the step 3 with the intensity envelopes of different modulation formats in the signal monitoring original library constructed in the step 4 from low signal to noise ratio to high signal to noise ratio according to coarse steps of 5dB intervals, determining the modulation format corresponding to the obtained maximum similarity as the modulation format of the signal E, and completing the modulation format monitoring operation;
step 6: and (3) according to the modulation format information determined in the step (5), sequentially comparing the intensity envelope of the step (3) with the intensity envelope of the modulation format corresponding to the signal monitoring original library constructed in the step (4) from a low signal to noise ratio to a high signal to noise ratio according to the fine step length of 1dB intervals, determining the optical signal to noise ratio corresponding to the obtained maximum similarity as the optical signal to noise ratio of the signal E, and completing the optical signal to noise ratio monitoring.
2. The method for monitoring modulation format and osnr according to claim 1, wherein the preprocessing in step 1 comprises resampling, IQ mismatch equalization, dispersion compensation, and clock recovery performed sequentially.
3. The method for monitoring modulation format and osnr according to claim 1, wherein the power signal P in step 2 has the following calculation formula:
P＝|D| 2
wherein: d 2 Is a power calculation for signal D.
4. The method for monitoring modulation format and osnr according to claim 1, wherein the extracting intensity histogram envelope calculation formula in step 3 is as follows:
[a，b]＝hist(P，bins)
wherein: a is the intensity histogram envelope of the power signal P; b is the group distance value of the intensity histogram; p is a power signal; bin is the group pitch number of the intensity histogram.
5. The method for monitoring modulation format and osnr according to claim 1, wherein the smoothing filtering method in step 3 is one of fourier series fitting, polynomial fitting, and moving average.
6. The method for monitoring the modulation format and the osnr according to claim 1, wherein the modulation format monitoring required to be implemented in step 5 and the osnr monitoring required to be implemented in step 6 are implemented in an auxiliary manner by using a feature similarity comparison method.
7. The method for monitoring the modulation format and the osnr according to claim 6, wherein the similarity comparison method is one of euclidean distance, manhattan distance, chebyshev distance;
the similarity calculation formula is as follows:
wherein: d, d ts The similarity of the intensity envelope in the original library is monitored for the test signal intensity envelope and the signal; x is x tk Kth data that is a test signal strength envelope; x is x sk Monitoring the kth data of the intensity envelope in the raw library for the signal; m is a variable parameter, expressed as Manhattan distance when m is 1, as Euclidean distance when m is 2, and as Chebyshev distance when m tends to infinity.
8. The method for monitoring the modulation format and the optical signal to noise ratio according to claim 1, further comprising sequentially performing frequency offset estimation and carrier phase recovery after determining the modulation format and the optical signal to noise ratio of the signal, so as to realize final mediation of the signal.
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