CN106788708A - The OSNR computational methods of OTN networks - Google Patents
The OSNR computational methods of OTN networks Download PDFInfo
- Publication number
- CN106788708A CN106788708A CN201611197849.8A CN201611197849A CN106788708A CN 106788708 A CN106788708 A CN 106788708A CN 201611197849 A CN201611197849 A CN 201611197849A CN 106788708 A CN106788708 A CN 106788708A
- Authority
- CN
- China
- Prior art keywords
- osnr
- computation model
- node
- link
- otn networks
- 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.)
- Pending
Links
Classifications
-
- 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
- H04B10/07—Arrangements for monitoring or testing transmission systems; Arrangements for fault measurement of transmission systems
- H04B10/075—Arrangements for monitoring or testing transmission systems; Arrangements for fault measurement of transmission systems using an in-service signal
- H04B10/079—Arrangements for monitoring or testing transmission systems; Arrangements for fault measurement of transmission systems using an in-service signal using measurements of the data signal
- H04B10/0795—Performance monitoring; Measurement of transmission parameters
- H04B10/07953—Monitoring or measuring OSNR, BER or Q
Landscapes
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Telephonic Communication Services (AREA)
Abstract
The embodiment of the invention discloses a kind of OSNR computational methods of OTN networks, methods described includes：Cascaded link in OTN networks sets up OSNR computation model；Obtain the output parameter and link parameter of the computation model；Change the nodes in the computation model；Computation model after changing to node carries out OSNR calculating.The embodiment of the present invention sets up corresponding OSNR computation model, the output parameter and link parameter of the computation model by calculating, and obtains the OSNR of the computation model.The operation such as increase node, deletion of node is carried out based on the computation model afterwards, so that the network topology change of OTN networks, consider the problem that whether can also continue transmission after OTN network topology changes and change in topology, if judging that the OTN networks after change in topology meet the condition for continuing to transmit, completion is calculated the OSNR after network topology change.
Description
Technical field
The present invention relates to intelligent power grid technology field, more particularly to a kind of OSNR computational methods of OTN networks.
Background technology
Under the greatly developing of intelligent grid, the information work of power network generates substantial amounts of business datum, to original
The bandwidth of support system causes enormous pressure, to solve this problem, can be using all-optical cross, OTN (the light transmission of 10,000,000,000 interconnections
Net, OpticalTransportNetwork) technology carries out networking, further forms Optical Transmission Network OTN, to support electric network information
Produced mass data.OTN technologies are mainly used in operator in the past, and its network architecture is stable once design, but
In the actual moving process of power network, the continuous construction of power network will cause the change of OTN network structures, and the change of network structure is main
Influence bottom physical parameter, and in the OTN networks of all-optical cross, the most important parameter of physical layer is exactly OSNR, its value
Size directly determine whether light path can be opened, will influence the performance of whole net once can not meet and open index request,
Extreme influence is caused to electric network information process of construction.
Mainly include for the research of OSNR at present, a kind of is the characteristic according to OSNR, asks for being put comprising light
The OSNR of the dwdm system of big device；Another kind typically research determines letter by different measuring method or measuring system
The OSNR in road.But in the case that this lower method is all focused only in existing network topology, calculate or measure the light of channel
Signal to noise ratio, for the change of network topology, the situation of change of OSNR cannot be learnt by theory analysis.
In order to solve the above problems, the noise coefficient of the with good grounds image intensifer of method of solution and gain obtain method from spoke
Noise power is penetrated, the single channel input power of image intensifer is then calculated, according to single channel input power and input light noise
Than obtaining input noise power, output noise power is then obtained again, single pass output signal power is finally asked for, according to defeated
Go out signal power and output noise power obtains the output OSNR of signal.Although the above method overcomes OSNR estimation
Some defects of method, but still not in view of under the situation of change of network topology, can original system continue the problem of transmission.
The content of the invention
A kind of OSNR computational methods of OTN networks are provided in the embodiment of the present invention, it is of the prior art to solve
OSNR computational methods do not consider that the change of network topology causes the problem of system transfers state change.
In order to solve the above-mentioned technical problem, the embodiment of the invention discloses following technical scheme：
A kind of OSNR computational methods of OTN networks, methods described includes：
Cascaded link in OTN networks sets up OSNR computation model；
Obtain the output parameter and link parameter of the computation model；
Change the nodes in the computation model；
Computation model after changing to node carries out OSNR calculating.
Preferably, the cascaded link in the network according to OTN sets up OSNR computation model, including：
Obtain the number of the amplifier in OTN networks end cascaded link；
Number according to the amplifier determines the series of the OTN networks cascade link；
Set up the OSNR computation model of series identical with the series of the cascaded link.
Preferably, the output parameter and link parameter for obtaining the computation model, including：
Obtain the output power signal of the output end of the model and the ASE power of accumulation；
Calculate the amplifier gain in the computation model link and link load.
Preferably, the nodes changed in the computation model, including：
Increase or decrease the number of the amplifier in the computation model.
Preferably, also include：Judge whether the computation model after concept transfer meets the condition of transmission.
Preferably, whether the computation model judged after concept transfer meets the condition of transmission, including：
Judge the constraints and OSNR that whether meet optical signal power of the computation model after the concept transfer
Constraints；
If it is satisfied, then carrying out OSNR calculating.
Preferably, the computation model after the change to node carries out OSNR calculating, including：
Calculate node increase or decrease after computation model output end signal power and accumulation ASE power；
The output end signal power of the computation model after being increased or decreased according to the node and the ASE power of accumulation are obtained
Node increase or decrease after computation model OSNR.
From above technical scheme, a kind of OSNR computational methods of OTN networks provided in an embodiment of the present invention, institute
The method of stating includes：Cascaded link in OTN networks sets up OSNR computation model；Obtain the output of the computation model
Parameter and link parameter；Change the nodes in the computation model；Computation model after changing to node carries out OSNR
Calculate.The embodiment of the present invention sets up corresponding OSNR computation model, is joined by the output of the computation model for calculating
Number and link parameter, obtain the OSNR of the computation model.Increase node is carried out based on the computation model afterwards, is deleted
Whether also node etc. is operated so that the network topology change of OTN networks, it is contemplated that after OTN network topology changes and change in topology
The problem that can continue to transmit, if judging that the OTN networks after change in topology meet the condition for continuing to transmit, completion is opened up to network
The OSNR flutterred after change is calculated.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, for those of ordinary skill in the art
Speech, on the premise of not paying creative work, can also obtain other accompanying drawings according to these accompanying drawings.
Fig. 1 is a kind of schematic flow sheet of the OSNR computational methods of OTN networks provided in an embodiment of the present invention；
Fig. 2 is the cascaded link structural representation in a kind of OTN networks provided in an embodiment of the present invention；
Fig. 3 is the cascaded link structural representation in another OTN networks provided in an embodiment of the present invention.
Specific embodiment
In order that those skilled in the art more fully understand the technical scheme in the present invention, below in conjunction with of the invention real
The accompanying drawing in example is applied, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described implementation
Example is only a part of embodiment of the invention, rather than whole embodiments.Based on the embodiment in the present invention, this area is common
The every other embodiment that technical staff is obtained under the premise of creative work is not made, should all belong to protection of the present invention
Scope.
It is a kind of a kind of light noise of OTN networks provided in an embodiment of the present invention provided in an embodiment of the present invention referring to Fig. 1
Than the schematic flow sheet of computational methods, methods described includes：
S101, the cascaded link in OTN networks sets up OSNR computation model.
Obtain the number of the amplifier in OTN networks end cascaded link；Number according to the amplifier determines the OTN
The series of network cascade link；Set up the OSNR computation model of series identical with the series of the cascaded link.
If Fig. 2 is the cascaded link structural representation in a kind of OTN networks, Pin is input end signal power as shown in the figure,
Pout is output end signal power, and the cascaded link in Fig. 2 includes N number of amplifier.It is thus determined that the OTN networks cascade chain
The series on road is N grades.
The definition of OSNR be in the ratio that light effective bandwidth is optical signal power and noise power in 0.1nm, generally can be with
It is expressed as：
OSNR=Sout/Nout (1)
Wherein, Sout is output end signal power, and Nout is output end noise power.Noise power is made up of two parts,
A part be the external noise power of input by the output after equipment, another part is that the internal noise power of equipment is defeated
Go out.Because outside input noise power is difficult to measure, ignore herein, so as to set output end optical noise power only by equipment
Internal noise constitute.Then OSNR can be expressed as：
OSNR=Sout/PASE (2)
OSNR (dB)=Sout-PASE (3)
Wherein, PASE is the output end noise power produced by device interior noise.Due in OTN networks, node and
Link be serially connected generation business route, transmission signal business route on transmit when can sequentially pass through cascade with amplify work(
The equipment of energy.Assuming that all EDFA make an uproar in gross output (including accumulation ASE power), the link of each amplifier out
When sound index F, gain, every section of optical fiber attenuation L are identical, OSNR can be expressed as：
Rout(dB)=Pin-F-10lgN-10lg(hvB0)=Pout-L-F-10lgN-10lg(hvB0) (4)
S102, obtains the output parameter and link parameter of the computation model.
Obtain the output power signal of the output end of the model and the ASE power of accumulation；Calculate the computation model chain
Amplifier gain and link load in road.
In cascade EDFAs system, due to light delivery section (OTS) bout length of each wdm system and its loss in practice
It is not quite similar, the amplifier that each office's (station) is configured is also incomplete same, therefore above-mentioned expression formula is under actual scene
Application can be subject to significant restrictions.Therefore for cascade amplifier apparatus, we using the basic definition of OSNR come
Calculate the OSNR of cascade system：
OSNR=Sout/PASE is total (5)
OSNR (dB)=Sout-PASE is total (6)
Wherein, Pout is the signal power of output end, and the ASE general powers that PASE is always accumulated, physical meaning is each
After device interior noise is by the gain and decay of cascade system, in the noise power that output end embodies.
1) the signal power Pout of output end
In actual power grid application, the power output Pout (unit is dBm) of the multiplying arrangement that we can collect,
The ASE power that Pout is contained in signal power and accumulated in theory, but the ASE power due to signal power much larger than accumulation,
Therefore when calculating, Pout is considered as the signal power of output end for we.
2) the ASE power PASE of accumulation is total
The internal noise power of i-th multiplying arrangement passed through for signal can be calculated by below equation：
PASEi (dB)=NFi+Gi+Nin (7)
Or
PASEi (W)=2nsp(Gi-1)hvB0 (8)
PASEi (dB)=10log2nsp+10log(Gi-1)+10loghvB0≈4+(-58)+Gi (9)
Wherein, NFiIt is external noise factor, is the ratio of input signal to noise ratio and output end signal to noise ratio.GiFor amplifier increases
Benefit.NinIt is the noise power of input, Nin=10loghvB0, i.e. input noise is a power for photon.nspIt is the reversion factor,
Will be generally greater than or equal to 1.
Total ASE noise powers of the amplifier accumulation for then being cascaded in business route can be expressed as：
Wherein, PASEi、Li、GiUnit be dBm, LiLink load, GiIt is amplifier gain.Then
Total (the W)=P of PASEASE1·L1△2…△n-1Gn+PASE2·L2△3…△n-1Gn+PASEn (11)
Wherein, △j=GjLj。
3) amplifier gain G
Amplifier gain is related to its type, and its actual gain meets its nominal value range.And can be from existing network data
The middle input for obtaining amplifier and power output, therefore the actual gain of amplifier can be calculated according to following formula.For non-
Pure amplifier apparatus (equipment may contain two and above amplifier), regard this equipment as an amplifier, by its signal
Input power is considered as equivalent overall gain with the ratio of output power signal.
4) link load L
Link load can directly read the nominal value of link load from existing network topology or be referred to according to paper information
Value, cable loss coefficient is 0.275dB/km.
S103, changes the nodes in the computation model.
The number of the amplifier in the computation model is increased or decreased, when the amplifier number hair in the computation model
After changing, corresponding cascaded link changes, and now also needs to judge whether the computation model changed after posterior nodal point meets
The condition of transmission.Specially：Judge the constraints for whether meeting optical signal power of the computation model after the concept transfer
With OSNR constraints；If it is satisfied, then carrying out OSNR calculating.
After node is increased in a network, because node is while signal is amplified, internal noise can be produced, believed to light
While number power output is impacted, the OSNR of optical signal can also be impacted, the two key elements are for optical signal
Can be transmitted on service link has and relation, i.e., only when the minimum power input and output signal power for meeting node
Within zone of reasonableness, the optical signal could continue transmission to OSNR values.Due to receiving the amplifier None- identified power of optical signal
Too small optical signal, if if serious by the optical signal decay of link transmission, causing luminous power less than multiplying arrangement most
Small rated input power, then the multiplying arrangement optical signal cannot be amplified, i.e., this light path is not connected, and is undertaken in light path
Business can also interrupt, so must being fulfilled for the minimum rated input power of node.For ensure business data transmission stabilization and
Accurately, the OSNR values of OTN optical-fiber networks must are fulfilled for 18dB, if being less than 18dB, even if input optical power is higher than multiplying arrangement most
Small rated input power, business cannot also be transmitted accurate stable on optical-fiber network, so the OSNR values of output signal must be
Within zone of reasonableness.
Therefore consider network topology change to business route can the influence of normal transmission mainly have two aspects：Node becomes
Whether optical signal power meets the minimum rated input power of multiplying arrangement after change；The OSNR values of business route are after node change
It is no to meet 18dB.Then built according to above-mentioned two aspect and meet the constraints that business route normal transmission, consider to increase first
Node：
To increase node in existing business link, it is thus necessary to determine that the Amplifier type of node, node location, such as Fig. 3
The cascaded link structural representation in another OTN networks provided in an embodiment of the present invention is shown, compared to the cascade chain in Fig. 2
Road, be increased in Fig. 3 amplifier it is relative increase 1 node, it is assumed that represented respectively in cascaded link interior joint 1,2
Original node, node 3 represents node to be increased, and G1, G2, G3 distinguish the gain of node 1,2,3.L is node 1 and node 2
Original link load before, L1, L2 are respectively after increase node 3 and node 1 and the link load of node 2.P1out is node
1 power output, P3in is the input power of node 3, and P3out is the power output of node 3, and P2in is the input work of node 2
Rate, P2out is the power output of node 2.
1) optical signal power constraints：
The input power of each website after network topology change is greater than the minimum rated input power equal to the equipment,
I.e.：
P2in(W)=P1outG3/L1L2≥Pmin (12)
PminIt is the acceptable specified minimum power of node 2.
2) OSNR constraints
The OSNR of each website output signal after network topology change is greater than equal to 18dB, and the signal could be after
Resume it is defeated, i.e.,：
OSNRout=P2out/ PASE is total >=18dB (13)
According to the power output of our calculate nodes 2 first of OSNR formula：
P2out=P2inG2 (14)
The output noise power of calculate node 2 again：
Total (the W)=P of PASEASE1G3/L1L2+PASE3/L2+PASE2 (15)
PASEiIt is the noise power of node, can be obtained by formula (7).
S104, the computation model after changing to node carries out OSNR calculating.
Calculate node increase or decrease after computation model output end signal power and accumulation ASE power；According to institute
The ASE power of the output end signal power and accumulation of stating the computation model after node is increased or decreased obtains node and increases or decreases
The OSNR of computation model afterwards.If above-mentioned two condition all meets, after can obtaining increasing node using formula (5)
OSNR.
If deletion of node, as a example by described in above-described embodiment, deletion of node 3, then link L1 and L2 be merged into L, with increasing
Supernumerary segment point needs the constraints for meeting similar, can be divided into two kinds of situations, that is, delete optical signal work(after node posterior nodal point change
Whether rate meets the minimum rated input power of multiplying arrangement；Whether the OSNR values of business route meet 18dB after node change.
Specific computation model is similar to the OSNR constraints after calculation procedure and increase node.
As seen from the above-described embodiment, a kind of OSNR computational methods of OTN networks provided in an embodiment of the present invention, described
Method includes：Cascaded link in OTN networks sets up OSNR computation model；Obtain the output ginseng of the computation model
Number and link parameter；Change the nodes in the computation model；Computation model after changing to node carries out OSNR meter
Calculate.The embodiment of the present invention sets up corresponding OSNR computation model, the output parameter of the computation model by calculating
And link parameter, obtain the OSNR of the computation model.Increase node is carried out based on the computation model afterwards, section is deleted
The operation such as point so that the network topology change of OTN networks, it is contemplated that whether can also after OTN network topology changes and change in topology
The problem for continuing to transmit, if judging that the OTN networks after change in topology meet the condition for continuing to transmit, completes to network topology
OSNR after change is calculated.
The description of the embodiment of the method more than, it is apparent to those skilled in the art that the present invention can
Realized by the mode of software plus required general hardware platform, naturally it is also possible to by hardware, but in many cases the former
It is more preferably implementation method.Based on such understanding, technical scheme substantially makes tribute to prior art in other words
The part offered can be embodied in the form of software product, and the computer software product is stored in a storage medium, bag
Some instructions are included to be used to so that a computer equipment (can be personal computer, server, or network equipment etc.) performs
The all or part of step of each embodiment methods described of the invention.And foregoing storage medium includes：Read-only storage
(ROM), random access memory (RAM), magnetic disc or CD etc. are various can be with the medium of store program codes.
The present invention can be described in the general context of computer executable instructions, such as program
Module.Usually, program module includes performing particular task or realizes routine, program, object, the group of particular abstract data type
Part, data structure etc..The present invention can also be in a distributed computing environment put into practice, in these DCEs, by
Remote processing devices connected by communication network perform task.In a distributed computing environment, program module can be with
In local and remote computer-readable storage medium including including storage device.
It should be noted that herein, term " including ", "comprising" or its any other variant be intended to non-row
His property is included, so that process, method, article or equipment including a series of key elements not only include those key elements, and
And also include other key elements being not expressly set out, or also include for this process, method, article or equipment institute are intrinsic
Key element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including institute
Also there is other identical element in process, method, article or the equipment of stating key element.
The above is only specific embodiment of the invention, is made skilled artisans appreciate that or realizing this hair
It is bright.Various modifications to these embodiments will be apparent to one skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, the present invention
The embodiments shown herein is not intended to be limited to, and is to fit to and principles disclosed herein and features of novelty phase one
The scope most wide for causing.
Claims (7)
1. a kind of OSNR computational methods of OTN networks, it is characterised in that methods described includes：
Cascaded link in OTN networks sets up OSNR computation model；
Obtain the output parameter and link parameter of the computation model；
Change the nodes in the computation model；
Computation model after changing to node carries out OSNR calculating.
2. OSNR computational methods of OTN networks according to claim 1, it is characterised in that described according to OTN networks
In cascaded link set up OSNR computation model, including：
Obtain the number of the amplifier in OTN networks end cascaded link；
Number according to the amplifier determines the series of the OTN networks cascade link；
Set up the OSNR computation model of series identical with the series of the cascaded link.
3. OSNR computational methods of OTN networks according to claim 2, it is characterised in that the acquisition meter
The output parameter and link parameter of model are calculated, including：
Obtain the output power signal of the output end of the model and the ASE power of accumulation；
Calculate the amplifier gain in the computation model link and link load.
4. OSNR computational methods of OTN networks according to claim 3, it is characterised in that the change meter
The nodes in model are calculated, including：
Increase or decrease the number of the amplifier in the computation model.
5. OSNR computational methods of OTN networks according to claim 4, it is characterised in that also include：Judge to change
Whether the computation model after node meets the condition of transmission.
6. OSNR computational methods of OTN networks according to claim 5, it is characterised in that the judgement changes section
Whether the computation model after point meets the condition of transmission, including：
Judge the constraints for whether meeting optical signal power and the OSNR constraint of the computation model after the concept transfer
Condition；
If it is satisfied, then carrying out OSNR calculating.
7. OSNR computational methods of OTN networks according to claim 6, it is characterised in that described to change to node
Computation model afterwards carries out OSNR calculating, including：
Calculate node increase or decrease after computation model output end signal power and accumulation ASE power；
The output end signal power of the computation model after being increased or decreased according to the node and the ASE power of accumulation obtain node
The OSNR of the computation model after increasing or decreasing.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611197849.8A CN106788708A (en) | 2016-12-22 | 2016-12-22 | The OSNR computational methods of OTN networks |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611197849.8A CN106788708A (en) | 2016-12-22 | 2016-12-22 | The OSNR computational methods of OTN networks |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106788708A true CN106788708A (en) | 2017-05-31 |
Family
ID=58899366
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611197849.8A Pending CN106788708A (en) | 2016-12-22 | 2016-12-22 | The OSNR computational methods of OTN networks |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106788708A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107797000A (en) * | 2017-10-25 | 2018-03-13 | 成都西井科技有限公司 | The microwave signal detection method of analysis based on model |
| CN108512596A (en) * | 2018-03-09 | 2018-09-07 | 烽火通信科技股份有限公司 | OSNR computational methods for cascading image intensifer communication system and device |
| CN110958066A (en) * | 2019-11-18 | 2020-04-03 | 腾讯科技（深圳）有限公司 | Gain network acquisition method and device, storage medium and computer equipment |
| CN112585889A (en) * | 2018-08-20 | 2021-03-30 | 华为技术有限公司 | Method and device for establishing data model |
| CN116074661A (en) * | 2022-12-22 | 2023-05-05 | 北京邮电大学 | Self-adaptive routing method based on Q learning and related equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101262297A (en) * | 2007-03-08 | 2008-09-10 | 华为技术有限公司 | Method and device for configuring device in wave division multiplexing WDM network |
| CN102098596A (en) * | 2011-03-11 | 2011-06-15 | 中国联合网络通信集团有限公司 | Route establishing method and device in optical network |
| CN105610496A (en) * | 2015-12-18 | 2016-05-25 | 陈骋 | Computing method for simulating value of optical signal to noise ratio (OSNR) of pre-built transmission network |
-
2016
- 2016-12-22 CN CN201611197849.8A patent/CN106788708A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101262297A (en) * | 2007-03-08 | 2008-09-10 | 华为技术有限公司 | Method and device for configuring device in wave division multiplexing WDM network |
| CN102098596A (en) * | 2011-03-11 | 2011-06-15 | 中国联合网络通信集团有限公司 | Route establishing method and device in optical network |
| CN105610496A (en) * | 2015-12-18 | 2016-05-25 | 陈骋 | Computing method for simulating value of optical signal to noise ratio (OSNR) of pre-built transmission network |
Non-Patent Citations (2)
| Title |
|---|
| 刘海涛 等: "WDM/OTN系统OSNR的计算与优化", 《邮电设计技术》 * |
| 国脉科技股份有限公司教育培训事业部: "《通信技术项目教程》", 1 September 2009 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107797000A (en) * | 2017-10-25 | 2018-03-13 | 成都西井科技有限公司 | The microwave signal detection method of analysis based on model |
| CN108512596A (en) * | 2018-03-09 | 2018-09-07 | 烽火通信科技股份有限公司 | OSNR computational methods for cascading image intensifer communication system and device |
| CN108512596B (en) * | 2018-03-09 | 2019-06-21 | 烽火通信科技股份有限公司 | For cascading the OSNR calculation method and device of image intensifer communication system |
| WO2019169915A1 (en) * | 2018-03-09 | 2019-09-12 | 烽火通信科技股份有限公司 | Osnr calculation method and apparatus for cascaded optical amplifier communication system |
| CN112585889A (en) * | 2018-08-20 | 2021-03-30 | 华为技术有限公司 | Method and device for establishing data model |
| US11483090B2 (en) | 2018-08-20 | 2022-10-25 | Huawei Technologies Co., Ltd. | Method for establishing data model and apparatus |
| CN110958066A (en) * | 2019-11-18 | 2020-04-03 | 腾讯科技（深圳）有限公司 | Gain network acquisition method and device, storage medium and computer equipment |
| CN110958066B (en) * | 2019-11-18 | 2022-09-09 | 腾讯科技（深圳）有限公司 | Gain network acquisition method and device, storage medium and computer equipment |
| CN116074661A (en) * | 2022-12-22 | 2023-05-05 | 北京邮电大学 | Self-adaptive routing method based on Q learning and related equipment |
| CN116074661B (en) * | 2022-12-22 | 2023-08-22 | 北京邮电大学 | Self-adaptive routing method based on Q learning and related equipment |
| US11855689B1 (en) | 2022-12-22 | 2023-12-26 | Beijing University Of Posts And Telecommunications | Routing method and related device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106788708A (en) | The OSNR computational methods of OTN networks | |
| US6330381B1 (en) | Methods, systems, media and signals for determining optimum pre-compensation and optimization of an optical system | |
| US7693422B2 (en) | Constraint-based design of optical transmission systems | |
| Bouda et al. | Accurate prediction of quality of transmission based on a dynamically configurable optical impairment model | |
| Rosa et al. | Signal power asymmetry optimisation for optical phase conjugation using Raman amplification | |
| US9820020B2 (en) | Grooming method and device for packet optical transport network | |
| US6404744B1 (en) | Method for designing a communication network | |
| CN102238060B (en) | Routing method and apparatus thereof | |
| CN101908942B (en) | Method for transmitting damage information, node and network system | |
| He et al. | Analysis of blocking probability for first-fit wavelength assignment in transmission-impaired optical networks | |
| Chaves et al. | Fast and adaptive impairment aware routing and wavelength assignment algorithm optimized by offline simulations | |
| Amirabadi et al. | Deep neural network-based QoT estimation for SMF and FMF links | |
| CN102148642A (en) | Fiber optic communication network reliability assessment method | |
| CN104917564A (en) | FEC selection method and device of optical paths | |
| CN107465535A (en) | A kind of link down risk analysis method, device, electronic equipment and storage medium | |
| Downie et al. | A study of power efficiency maximization in submarine cable systems | |
| US7295515B2 (en) | Communication network design | |
| CN115276820A (en) | Method for setting power gradient of on-chip optical interconnection light source with mapping assistance | |
| US10122443B2 (en) | Method for determining an optical transmission system description | |
| JP6387461B2 (en) | Method for creating a transmission quality estimator for optical transmission | |
| Fumagalli et al. | Optimal amplifier placement in multiwavelength optical networks based on simulated annealing | |
| US8873951B2 (en) | Technology for simulating and/or controlling communication optical networks | |
| Routray et al. | Optical performance monitor placement in OTNs using link statistical model | |
| Khan et al. | Cross-Train: Machine Learning Assisted QoT-Estimation in Un-used Optical Networks | |
| US20230085524A1 (en) | Automatic configuration of pump attributes of a raman amplifier to achieve a desired gain profile |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170531 |