CN109347775A - A kind of modulation format recognition methods of combined strength fluctuation and phase fluctuation feature - Google Patents
A kind of modulation format recognition methods of combined strength fluctuation and phase fluctuation feature Download PDFInfo
- Publication number
- CN109347775A CN109347775A CN201811226668.2A CN201811226668A CN109347775A CN 109347775 A CN109347775 A CN 109347775A CN 201811226668 A CN201811226668 A CN 201811226668A CN 109347775 A CN109347775 A CN 109347775A
- Authority
- CN
- China
- Prior art keywords
- signal
- phase
- modulation format
- fluctuation
- recognition methods
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0012—Modulated-carrier systems arrangements for identifying the type of modulation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- 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
- H04B10/50—Transmitters
- H04B10/516—Details of coding or modulation
- H04B10/54—Intensity modulation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- 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
- H04B10/50—Transmitters
- H04B10/516—Details of coding or modulation
- H04B10/548—Phase or frequency modulation
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Optical Communication System (AREA)
Abstract
The invention discloses the modulation format recognition methods of combined strength fluctuation and phase fluctuation feature, comprising the following steps: step 1: obtaining the polarization state signal that receiving end receivesE x WithE y , signal is obtained by pretreatmentD x WithD y ;Step 2: calculating standard deviation and intensity noise variance, and construct two-dimensional intensity noise fluctuations plane;Step 3: dividing phase modulated signal by two-dimensional intensity noise fluctuations plane areamPSK and quadrature amplitude modulation signalmQAM;Step 4: calculating signalD x WithD y Intensity noise variance, construct two-dimensional phase noise plane;Step 5: according to two-dimensional phase noise plane to phase modulated signalmPSK distinguishes its different rank;It determines the signal of modulation format, completes modulation format identification;The present invention does not need to predict that other information, complexity are low, performance is good in advance.
Description
Technical field
The present invention relates to Optical Transmission Network OTN technical fields, and in particular to a kind of tune of combined strength fluctuation and phase fluctuation feature
Format identification method processed.
Background technique
Next-generation optical-fiber network is expected to more flexible, the more adaptive various requirement for meeting network terminal user;Light
The transmitting terminal of network can be different according to transmission link demand for services, the dynamic characteristic for changing transmitting end signal;Such as: modulation
Format, transmission baud rate, variable number, central wavelength of transmission channel etc.;Therefore in order to make optical-fiber network it is more flexible, from
Main, receiving end needs autonomous identification to transmit signal correlation properties, and then can optimize, adaptive conciliation signal;Wherein,
Modulation format identification is that wherein most important performance characteristic, modulation format information are correctly known;It can make digital signal processing module
In modulation format related algorithm select more optimal algorithm, and then promote the performance reconciled.
Recently, it has already been proposed that 2010, the researcher of Technical University Of Denmark proposes to make various modulation format recognizers
Identification process is realized with the corresponding cluster point of Kmeans algorithm identification modulation format planisphere;This method need carrier phase recovery with
After obtain planisphere, in practical applications have certain limitation, carrier phase recovery algorithm is also the related calculation of modulation format
Method;2012, the researcher of The Hong Kong Polytechnic University proposed to identify the asynchronous of modulation format using the method for artificial neural network
Histogram realizes that identification process, this method need additional modulation format detecting devices, increases the cost of modulation format identification;
2013, the researcher of georgia ,U.S.A Polytechnics proposed the high-order statistic in Stokes Space and Jones space
Recognizer;The algorithm needs to predict approximate optical signal to noise ratio in advance, and receives the carrier frequency of signal;2014, Hong Kong
Polytechnics's proposition realizes that modulation format is related using signal power distribution, largely restricts its practical level, while only
It works to quadrature amplitude modulation;2016, Hong Kong Chinese University researcher was proposed to be realized using the method for image procossing and be adjusted
The identification of format processed, this method need to carry out denoising to the two-dimensional image obtained by Stokes Space;Then
Constellation point identification process is carried out again.2018, Southwest Jiaotong University Yan Lianshan professor team proposed a kind of empty based on Stokes
Between two-dimensional surface modulation format recognition methods, this method can identify more modulation format, while have one to a variety of effects
Fixed anti-interference, since Stokes Space may increase influence of the noise to signal during signal is converted.
Summary of the invention
The present invention provides a kind of identification of achievable more modulation format, does not need the relevant information for additionally predicting signal,
The modulation format recognition methods of complexity lower combined strength fluctuation and phase fluctuation feature.
The technical solution adopted by the present invention is that: a kind of modulation format identification side of combined strength fluctuation and phase fluctuation feature
Method, comprising the following steps:
Step 1: obtaining the polarization state signal E that receiving end receivesxAnd Ey, signal D is obtained by pretreatmentxAnd Dy;
Step 2: the signal D obtained according to step 1xAnd DyGodard ' s standard deviation and intensity noise variance are calculated, according to
Godard ' s standard deviation and intensity noise difference construct two-dimensional intensity noise fluctuations plane;
Step 3: the two-dimensional intensity noise fluctuations plane area constructed by step 2 divides phase modulated signal mPSK and its difference
The quadrature amplitude modulation signal mQAM of order;
Step 4: calculating signal DxAnd DyPhase noise variance, according to Godard ' s standard deviation and phase noise variance structure
Build two-dimensional phase noise plane;
Step 5: the two-dimensional phase noise plane obtained according to step 4 distinguishes obtained phase modulated signal to step 3
MPSK distinguishes its different rank;It determines the modulation format of signal, completes modulation format identification.
Further, the pretreatment in the step 1 is pre- including dispersion compensation, clock recovery and the constant mould successively carried out
It is balanced.
Further, Godard ' s standard deviation calculation method is as follows in the step 2:
In formula: εGodardFor Godard ' s standard deviation, N is data sample points, Dx, for X after pretreatment polarization letter
Number, Dx, (n) it is Dx, nth symbol, RxFor Dx, firm power, DyFor Y polarization signal after pretreatment, Dy, (n) it is
DyNth symbol, RyFor DyFirm power, E { } be signal expectation, | |4For 4 powers of signal amplitude, | |2For
Signal power, | | it is signal amplitude.
Further, intensity noise variance calculation method is as follows in the step 2:
εInt_Var=Var (| | Dx(n)|2-E{|Dx(n)|2}|2)+Var(||Dy(n)|2-E{|Dy(n)|2}|2)
In formula: εInt_VarFor intensity noise variance, Var is variance, Dx, it is X polarization signal after pretreatment, Dx,(n)
For Dx, nth symbol, DyFor Y polarization signal after pretreatment, Dy, (n) it is DyNth symbol, E { } is signal
It is expected that | |2For signal power.
Further, it also needs to distinguish obtained phase-modulation to step 3 before calculating phase noise variance in the step 4
Signal mPSK carries out carrier phase recovery.
Further, the calculation method of the phase noise variance in the step 4 is as follows:
εphase_Var=Var (∠ [(Dp(n))4]/4)
In formula: εphase_VarFor phase noise variance, ∠ is the phase angle operation for extracting signal, Dp(n) extensive for carrier phase
Modulated signal after double calculation method, ()4It is operated for 4 powers of signal.
Further, the two-dimensional phase noise that the two-dimensional intensity noise fluctuations plane and step 5 obtained to step 3 obtains is flat
Face passes through machine learning method supplementary globe.
Further, the machine learning method is support vector machines, Kmeans algorithm, KNN algorithm, neural network algorithm
One of.
It further, further include successively being carried out the following processing to after the signal for determining modulation format, polarization demultiplexing, frequency
Estimation and carrier phase recovery partially, realize the final conciliation of signal.
The beneficial effects of the present invention are:
(1) identification of the achievable more modulation format modulation signal of the present invention, including a variety of phase modulation formats, Duo Zhongzheng
Hand over amplitude modulation format etc.;
(2) present invention does not need additional ancillary equipment, and letter directly can be mediated using the receiver of Transmission system
Number;
(3) present invention does not need the relevant information for additionally predicting signal, can be with direct estimation modulation format information;
(4) present invention only needs to calculate the intensity and phase fluctuation feature of signal, therefore complexity is low;
(5) present invention can be in a variety of transmission services, multiple transmission wavelengths, multiple fibre cores, multiple modes, multiple polarizations
State, more modulation format optical transmission system in realize modulation format information identification.
Detailed description of the invention
Fig. 1 is the identification process of signal in the embodiment of the present invention 1.
Fig. 2 is flowage structure schematic diagram of the present invention.
Fig. 3 is the intensity noise wave level (a) and phase noise wave level (b) constructed in the present invention.
Fig. 4 is the correct identification of the discrimination (a) and phase-modulation of quadrature amplitude modulation under the different training points of the present invention
Rate (b).
Specific embodiment
The present invention will be further described in the following with reference to the drawings and specific embodiments.
A kind of modulation format recognition methods of combined strength fluctuation and phase fluctuation feature, comprising the following steps:
Step 1: obtaining the polarization state signal E that receiving end receivesxAnd Ey, signal D is obtained by pretreatmentxAnd Dy;Including
Dispersion compensation, clock recovery, constant mould preequalization;Wherein ExFor X-direction polarization state signal, EyFor Y-direction polarization signal.
Wherein constant mould preequalization can play very well phase modulated signal mPSK (the constant amplitude mould of level-one is presented)
Portfolio effect;Preliminary equilibrium can only be played to quadrature amplitude modulation signal mQAM (having the effect of multistage amplitude mould);At this time
Obtained signal DxAnd DyDifferent strength characteristic can be showed;So phase modulated signal can be distinguished by strength characteristic
MPSK and quadrature amplitude modulation signal mQAM.
Step 2: the signal D obtained according to step 1xAnd DyGodard ' s standard deviation and intensity noise variance are calculated, according to
Godard ' s standard deviation and intensity noise difference construct two-dimensional intensity noise fluctuations plane.
Godard ' s standard deviation calculation method is as follows:
In formula: εGodardFor Godard ' s standard deviation, N is data sample points, Dx, for X after pretreatment polarization letter
Number, Dx, (n) it is Dx, nth symbol, RxFor Dx, firm power, DyFor Y polarization signal after pretreatment, Dy, (n) it is
DyNth symbol, RyFor DyFirm power, E { } be signal expectation, | |4For 4 powers of signal amplitude, | |2For
Signal power, | | it is signal amplitude.
Intensity noise variance calculation method is as follows:
εInt_Var=Var (| | Dx(n)|2-E{|Dx(n)|2}|2)+Var(||Dy(n)|2-E{|Dy(n)|2}|2)
In formula: εInt_VarFor intensity noise variance, Var is variance, Dx, it is X polarization signal after pretreatment, Dx,(n)
For Dx, nth symbol, DyFor Y polarization signal after pretreatment, Dy, (n) it is DyNth symbol, E { } is signal
It is expected that | |2For signal power.
Step 3: the two-dimensional intensity noise fluctuations plane area constructed by step 2 divides phase modulated signal mPSK and orthogonal width
Spend modulated signal mQAM;
In two-dimensional intensity noise fluctuations plane, it is special that same strength fluctuation is presented in all phase modulated signal mPSK
Sign, appears in the same region;It is special that different strength fluctuations is presented in the quadrature amplitude modulation signal mQAM of various order of modulation
Sign, appears in different regions;Therefore the mQAM of mPSK and various order of modulation can be distinguished by intensity noise wave level
(such as: 8QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM, mQAM);The strength characteristic for distinguishing different zones can pass through
Machine learning method (such as: support vector machines (SVM), Kmeans algorithm, KNN algorithm, neural network algorithm etc.;Do not limit to
In above-mentioned algorithm) carry out supplementary globe.
Step 4: calculating signal DxAnd DyPhase noise variance, according to Godard ' s standard deviation and phase noise variance structure
Build two-dimensional phase noise plane;
The calculation method of phase noise variance is as follows:
εphase_Var=Var (∠ [(Dp(n))4]/4)
In formula: εphase_VarFor phase noise variance, ∠ is the phase angle operation for extracting signal, Dp(n) extensive for carrier phase
Modulated signal after double calculation method, ()4It is operated for 4 powers of signal.
Because specific mPSK modulation format can not directly use intensity fluctuation characteristic be distinguished, it is therefore desirable to use phase
Feature further discriminates between mPSK signal;It also needs to distinguish obtained phase tune to step 3 before calculating phase noise variance
Signal mPSK processed carries out carrier phase recovery.
Step 5: the two-dimensional phase noise plane obtained according to step 4 distinguishes obtained phase modulated signal to step 3
MPSK distinguishes its different rank;It determines the signal of modulation format, completes modulation format identification.
By two-dimensional phase noise fluctuations plane be used for distinguish different rank mPSK (such as: QPSK, 8PSK, 16PSK,
32PSK, mPSK) signal;In two-dimensional phase noise fluctuations plane, the phase modulation format of different rank appears in not same district
Domain;Distinguish simultaneously different zones phase fluctuation feature can by the method for machine learning (such as: support vector machines (SVM),
Kmeans algorithm, KNN algorithm, neural network algorithm etc., but be not limited to that above-mentioned algorithm) carry out supplementary globe.
Further include to determine modulation format signal after successively carry out the following processing, polarization demultiplexing, offset estimation and
Carrier phase recovery realizes the final conciliation of signal.
Embodiment
As shown in Figure 1, by all the way or the transmitter 101 of the road N wavelength (business)1~101NModulate phase-modulation/orthogonal width
The signal of degree modulation mPSK/mQAM;The transmitting signal of multiple wavelength (business) is coupled together by wavelength division multiplexer 102;
Pass through one section or N sections of optical fiber 1031~103NIt is transmitted, corresponding transmission loss is by one or N number of image intensifer 1041~
104NIt compensates;Since image intensifer will bring spontaneous emission noise, image intensifer 104 into1~104NRear end uses band logical
Filter 1051~105NFilter out the outer spontaneous emission noise of frequency band;Finally transmission signal will be multiple by Wave decomposing multiplexer (106)
The signal of wavelength separates, subsequently into receiver 1071~107NCarry out the behaviour such as corresponding digital-to-analogue conversion and Digital Signal Processing
Make;The present invention is modulated format identification in receivers.
Detailed process is as shown in Fig. 2, in receiver 1071~107NIn, after signal passes through photoelectric conversion, carry out digital-to-analogue conversion
Obtain digital signal.The digital signal received passes through dispersion compensation, clock recovery, constant mould preequalization.After preequalization
Data calculate two kinds of strength characteristic Godard ' s standard deviations and intensity noise variance first, and construct two-dimensional intensity noise waves
Dynamic plane.Distinguished by intensity noise wave level mPSK and various order of modulation mQAM (such as: 8QAM, 16QAM,
32QAM, 64QAM, 128QAM, 256QAM, mQAM etc.).Using machine learning method (such as: support vector machines (SVM),
Kmeans algorithm, KNN algorithm, neural network algorithm etc. can be used but do not limit to these algorithms) carry out supplementary globe.Due to strong
The mPSK of specific order of modulation cannot be distinguished in degree noise fluctuations plane, and Godard ' s standard deviation and phase noise variance is used to construct
One two-dimensional phase noise fluctuations plane, for distinguish different orders mPSK (such as: QPSK, 8PSK, 16PSK, 32PSK,
MPSK) signal.It is same using machine learning method (such as: support vector machines (SVM), Kmeans algorithm, KNN algorithm, nerve
Network algorithm etc. can be used but not limit to these algorithms) carry out supplementary globe.After end of identification, modulation lattice will be had determined
The signal of formula carries out polarization demultiplexing, offset estimation and carrier phase recovery, realizes the final demodulation of signal.
As shown in figure 3, being the present invention according to the intensity noise wave level (a) and phase noise of the building of example in detail below
Wave level (b);In order to verify feasibility of the invention, by taking several simple modulation formats as an example (such as: QPSK, 8PSK,
8QAM,16QAM,32QAM);It can be seen that, the strength fluctuation feature of different modulation formats goes out in intensity noise wave level
The different zones of present plane;Pass through the method for the support vector machines characteristic area different come supplementary globe;QPSK and 8PSK, by
In itself all be an intense level, therefore in the intensity noise wave level cannot be distinguished;It is fluctuated by phase noise
Plane distinguishes the mPSK signal of specific order, and discovery QPSK and 8PSK appears in different zones, use the side of support vector machines
Method carrys out the different characteristic area of supplementary globe.
By different training points, correctness of the invention is verified;As shown in figure 4, a is the correct of quadrature amplitude modulation
Discrimination, b are the correct recognition rata of phase-modulation;In fig.4 it can be seen that training points are more, the essence of modulation format identification
It spends higher;When rising to 10000 training samples, the correct recognition rata of mPSK, 8QAM, 16QAM, 32QAM are distinguished
It is 100%, 100%, 97.17%, and 97.18%.In fig. 4b it can be seen that phase-modulation discrimination is in training points very little
When i.e. can reach 100% discrimination, wherein the correct recognition rata of QPSK, 8PSK are respectively 100%, 100%;It is specific to know
Not rate is as shown in table 1.
As it can be seen from table 1 the modulation format tested in the case where lower signal-to-noise ratio, still can be identified correctly
Modulation format.
1. modulation format discrimination of table
In order to verify the validity of the method for the present invention, it is different in long distance transmission link also to calculate different modulating format
Influence of the transmission power to discrimination;From calculated result it can be seen that the method for the present invention can be to linear damage and nonlinear impairments
With certain redundancy;It can adapt to a variety of transmission services, multiple transmission wavelengths, multiple fibre cores, multiple modes, multiple polarizations
State, dynamic, a large amount of Optical Transmission Network OTN field.
The identification of more modulation format can be achieved in the present invention, does not need the relevant information for additionally predicting signal;Volume is not needed
Outer ancillary equipment, it is only necessary to calculate the intensity and phase fluctuation feature of signal, therefore complexity is lower.
Claims (9)
1. a kind of modulation format recognition methods of combined strength fluctuation and phase fluctuation feature, which is characterized in that including following step
It is rapid:
Step 1: obtaining the polarization state signal E that receiving end receivesxAnd Ey, signal D is obtained by pretreatmentxAnd Dy;
Step 2: the signal D obtained according to step 1xAnd DyGodard ' s standard deviation and intensity noise variance are calculated, according to
Godard ' s standard deviation and intensity noise difference construct two-dimensional intensity noise fluctuations plane;
Step 3: the two-dimensional intensity noise fluctuations plane area constructed by step 2 divides phase modulated signal mPSK and its different rank
Quadrature amplitude modulation signal mQAM;
Step 4: calculating signal DxAnd DyPhase noise variance, according to Godard ' s standard deviation and phase noise variance building two
Tie up phase noise plane;
Step 5: the two-dimensional phase noise plane obtained according to step 4 distinguishes the obtained area phase modulated signal mPSK to step 3
Divide its different rank;It determines the modulation format of signal, completes modulation format identification.
2. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 1,
It is characterized in that, the pretreatment in the step 1 includes dispersion compensation, clock recovery and the constant mould preequalization successively carried out.
3. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 1,
It is characterized in that, Godard ' s standard deviation calculation method is as follows in the step 2:
In formula: εGodardFor Godard ' s standard deviation, N is data sample points, Dx, it is X polarization signal after pretreatment, Dx,
It (n) is Dx, nth symbol, RxFor Dx, firm power, DyFor Y polarization signal after pretreatment, Dy, (n) it is DyN-th
A symbol, RyFor DyFirm power, E { } be signal expectation, | |4For 4 powers of signal amplitude, | |2For signal function
Rate, | | it is signal amplitude.
4. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 1,
It is characterized in that, intensity noise variance calculation method is as follows in the step 2:
εInt_Var=Var (| | Dx(n)|2-E{|Dx(n)|2}|2)+Var(||Dy(n)|2-E{|Dy(n)|2}|2)
In formula: εInt_VarFor intensity noise variance, Var is variance, Dx, it is X polarization signal after pretreatment, Dx, (n) it is Dx,
Nth symbol, DyFor Y polarization signal after pretreatment, Dy, (n) it is DyNth symbol, E=be signal expectation,
|·|2For signal power.
5. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 1,
It is characterized in that, also needs to distinguish obtained phase modulated signal mPSK to step 3 before calculating phase noise variance in the step 4
Carry out carrier phase recovery.
6. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 5,
It is characterized in that, the calculation method of the phase noise variance in the step 4 is as follows:
εphase_Var=Var (∠ [(Dp(n))4]/4)
In formula: εphase_VarFor phase noise variance, ∠ is the phase angle operation for extracting signal, Dp(n) it is calculated for carrier phase recovery
Modulated signal after method, ()4It is operated for 4 powers of signal.
7. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 1,
It is characterized in that, the two-dimensional phase noise plane that the two-dimensional intensity noise fluctuations plane and step 5 obtain to step 3 obtains passes through machine
Device learning method supplementary globe.
8. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 7,
It is characterized in that, the machine learning method is support vector machines, Kmeans algorithm, KNN algorithm, one in neural network algorithm
Kind.
9. the modulation format recognition methods of a kind of combined strength fluctuation and phase fluctuation feature according to claim 1,
Be characterized in that, further include to determine signal modulation format after successively carry out the following processing, polarization demultiplexing, offset estimation and
Carrier phase recovery realizes the final conciliation of signal.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811226668.2A CN109347775B (en) | 2018-10-22 | 2018-10-22 | Modulation format identification method combining intensity fluctuation and phase fluctuation characteristics |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811226668.2A CN109347775B (en) | 2018-10-22 | 2018-10-22 | Modulation format identification method combining intensity fluctuation and phase fluctuation characteristics |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109347775A true CN109347775A (en) | 2019-02-15 |
CN109347775B CN109347775B (en) | 2020-12-18 |
Family
ID=65310738
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811226668.2A Active CN109347775B (en) | 2018-10-22 | 2018-10-22 | Modulation format identification method combining intensity fluctuation and phase fluctuation characteristics |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109347775B (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110048781A (en) * | 2019-04-17 | 2019-07-23 | 武汉邮电科学研究院有限公司 | A kind of recognition methods of optical signal modulation format and device |
CN110071885A (en) * | 2019-04-17 | 2019-07-30 | 成都华日通讯技术有限公司 | A kind of deep learning method of discrimination of PSK digital signal subclass Modulation Identification |
CN110247710A (en) * | 2019-05-10 | 2019-09-17 | 北京邮电大学 | Based on light OFDM zero load wave position encoded multi-dimensional modulation signal processing method and device |
CN111093123A (en) * | 2019-12-09 | 2020-05-01 | 华中科技大学 | Flexible optical network time domain equalization method and system based on composite neural network |
CN114584212A (en) * | 2022-04-15 | 2022-06-03 | 中国电子科技集团公司第三十四研究所 | Modulation format and optical signal-to-noise ratio monitoring method for characteristic similarity analysis |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1937008A (en) * | 2005-09-22 | 2007-03-28 | 富士通株式会社 | Encryption method, cryptogram decoding method, encryptor, cryptogram decoder, transmission/reception system, and communication system |
US7428270B1 (en) * | 1999-02-15 | 2008-09-23 | Christian Dubuc | Method and system for detecting and classifying the modulation of unknown analog and digital telecommunications signals |
CN102497343A (en) * | 2011-11-25 | 2012-06-13 | 南京邮电大学 | Combined modulation recognition method based on clustering and support vector machine |
CN104158633A (en) * | 2014-09-09 | 2014-11-19 | 电子科技大学 | Maximum likelihood modulation recognition method based on Gaussian mixture model |
CN105207965A (en) * | 2015-08-14 | 2015-12-30 | 成都中安频谱科技有限公司 | Automatic VHF/UHF frequency range modulation identification method |
CN108270703A (en) * | 2016-12-30 | 2018-07-10 | 中国航天科工集团八五研究所 | A kind of signal of communication digital modulation type recognition methods |
-
2018
- 2018-10-22 CN CN201811226668.2A patent/CN109347775B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7428270B1 (en) * | 1999-02-15 | 2008-09-23 | Christian Dubuc | Method and system for detecting and classifying the modulation of unknown analog and digital telecommunications signals |
CN1937008A (en) * | 2005-09-22 | 2007-03-28 | 富士通株式会社 | Encryption method, cryptogram decoding method, encryptor, cryptogram decoder, transmission/reception system, and communication system |
CN102497343A (en) * | 2011-11-25 | 2012-06-13 | 南京邮电大学 | Combined modulation recognition method based on clustering and support vector machine |
CN104158633A (en) * | 2014-09-09 | 2014-11-19 | 电子科技大学 | Maximum likelihood modulation recognition method based on Gaussian mixture model |
CN105207965A (en) * | 2015-08-14 | 2015-12-30 | 成都中安频谱科技有限公司 | Automatic VHF/UHF frequency range modulation identification method |
CN108270703A (en) * | 2016-12-30 | 2018-07-10 | 中国航天科工集团八五研究所 | A kind of signal of communication digital modulation type recognition methods |
Non-Patent Citations (1)
Title |
---|
LIN JIANG等: "Chromatic Dispersion, Nonlinear Parameter, and Modulation Format Monitoring Based on Godard"s Error for Coherent Optical Transmission Systems", 《IEEE》 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110048781A (en) * | 2019-04-17 | 2019-07-23 | 武汉邮电科学研究院有限公司 | A kind of recognition methods of optical signal modulation format and device |
CN110071885A (en) * | 2019-04-17 | 2019-07-30 | 成都华日通讯技术有限公司 | A kind of deep learning method of discrimination of PSK digital signal subclass Modulation Identification |
CN110247710A (en) * | 2019-05-10 | 2019-09-17 | 北京邮电大学 | Based on light OFDM zero load wave position encoded multi-dimensional modulation signal processing method and device |
CN110247710B (en) * | 2019-05-10 | 2020-07-31 | 北京邮电大学 | Multi-dimensional modulation signal processing method and device based on optical OFDM (orthogonal frequency division multiplexing) idler position coding |
CN111093123A (en) * | 2019-12-09 | 2020-05-01 | 华中科技大学 | Flexible optical network time domain equalization method and system based on composite neural network |
CN114584212A (en) * | 2022-04-15 | 2022-06-03 | 中国电子科技集团公司第三十四研究所 | Modulation format and optical signal-to-noise ratio monitoring method for characteristic similarity analysis |
CN114584212B (en) * | 2022-04-15 | 2023-12-08 | 中国电子科技集团公司第三十四研究所 | Modulation format and optical signal to noise ratio monitoring method for feature similarity analysis |
Also Published As
Publication number | Publication date |
---|---|
CN109347775B (en) | 2020-12-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109347775A (en) | A kind of modulation format recognition methods of combined strength fluctuation and phase fluctuation feature | |
CN108880692B (en) | Modulation format recognition and optical signal-to-noise ratio monitoring method for coherent optical communication system | |
Jiang et al. | Blind density-peak-based modulation format identification for elastic optical networks | |
CN107018108B (en) | Modulation format identification method for two-dimensional plane of Stokes space | |
CN105790849B (en) | A kind of modulation format recognition methods towards coherent optical communication system | |
CN108631879B (en) | A kind of light orthogonal frequency division multiplexing communication method and system based on probability shaping mapping | |
Bo et al. | Modulation format recognition for optical signals using connected component analysis | |
US10938500B2 (en) | Methods and apparatus for dual polarisation optical communication | |
CN102318306A (en) | Optical multi-level transmission system | |
US9794092B1 (en) | Systems and methods for identification and demodulation of complex signal formats | |
Jiang et al. | An effective modulation format identification based on intensity profile features for digital coherent receivers | |
Xu et al. | Blind and low-complexity modulation format identification scheme using principal component analysis of Stokes parameters for elastic optical networks | |
CN103329462A (en) | Frame formatting for high rate optical communications | |
CN109347776B (en) | Method for identifying modulation format of optical communication signal with differential phase-to-amplitude ratio | |
Zhao et al. | A modulation format identification method based on amplitude deviation analysis of received optical communication signal | |
CN103401829A (en) | IQ imbalance compensation method for coherent-light orthogonal frequency division multiplexing (OFDM) communication system | |
CN109150781A (en) | A kind of modulation format recognition methods based on K-K coherent reception | |
Yu et al. | A modified PSO assisted blind modulation format identification scheme for elastic optical networks | |
Hao et al. | Stokes space modulation format identification for optical signals using probabilistic neural network | |
Feng et al. | Intelligent optical performance monitoring based on intensity and differential-phase features for digital coherent receivers | |
Jiang et al. | Robust and blind modulation format identification for elastic optical networks | |
Huang et al. | Nonlinearity mitigation of RoF signal using machine learning based classifier | |
CN109587091A (en) | The coherent optical communication system modulation format recognition methods of logic-based regression algorithm | |
CN109525324A (en) | One kind being based on the molding novel photon probability mapping method of terraced fields | |
CN116389207A (en) | Modulation format identification method based on signal amplitude histogram |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |