Optical splitter port identification method and system based on CD estimation in coherent PON

Abstract

The invention provides an optical splitter port identification method and system based on CD estimation in a coherent PON, and relates to the technical field of optical fiber communication. Optical splitter ports are distinguished by cascading devices with different negative CD values at different ports of an optical splitter in an ODN. And a receiving end extracts and estimates the port CD through a two-stage dispersion estimation algorithm, so that identification of different ports is realized, and construction of the network topology is completed. According to the invention, under the condition that the receiving and transmitting modules are not added on the receiving and transmitting sides, the digital signal processing DSP algorithm of the receiving end in the optical network unit ONU is utilized to realize the accurate identification of the optical splitter port.

Description

Technical Field

[0001] The present invention relates to the technical field of optical fiber communication, and particularly to a method and system for identifying splitter ports based on CD estimation in coherent PON. Background Art

[0002] In recent years, with the development of emerging technologies such as 5G, Internet of Things, and artificial intelligence, the global data traffic has grown rapidly, and passive optical network (PON) has developed rapidly. Currently, 50G PON is in the initial commercial stage, and the access network rate will further evolve to 200G in the future. Coherent detection technology is also expected to be applied to 200G PON.

[0003] With the continuous growth of the number of access network users, the management of large-scale PON networks has become increasingly difficult. Due to its passive characteristics, the current PON port management mainly relies on manual operation, such as using manual records and paper labels. This not only has low efficiency and is prone to errors, but also because these devices cannot report their status by themselves, resource management is greatly affected by network and user changes. Therefore, there are problems such as low resource utilization rate and difficult network management. Based on this, in the next-generation 200G coherent PON, it is necessary to introduce splitter port identification technology to bind users and splitter ports to build a network topology, and finally improve the resource management efficiency.

[0004] Patent document CN114430512A (application number: 202011183533.X) discloses a method and device for port identification, belonging to the technical field of optical fiber communication. This method is applied to PON, and PON includes at least one stage of splitters and at least one ONT. The wavelengths of the test lights reflected by the reflection components of different ports of the same splitter are different. The method includes: obtaining the reflection information of each reflection peak formed by each ONT reflecting each test light when each test light provided by a wavelength-tunable device is transmitted in the PON, determining the port of the splitter corresponding to each reflection peak group according to the reflection information of each reflection peak, where each reflection peak group includes the reflection peaks of each ONT reflecting each test light, and determining the port corresponding to each ONT in the splitter respectively according to the first transmission information of at least one reflection peak in each reflection peak group, the port of the splitter corresponding to each reflection peak group, and the second transmission information between each ONT and the OLT. Summary of the Invention

[0005] Aiming at the defects in the prior art, the purpose of the present invention is to provide a method and system for identifying splitter ports based on CD estimation in coherent PON.

[0006] According to a method for identifying splitter ports based on CD estimation in coherent PON provided by the present invention, it includes:

[0007] Step S1: Add different negative dispersion values to different ports of the first-level splitter and the second-level splitter in the passive optical network (PON).

[0008] Step S2: Extract and estimate the dispersion value of the corresponding port in the digital signal processing unit (DSP) at the receiving end of the optical network unit (ONU), so as to realize the identification of the splitter port.

[0009] Preferably, the step S1 includes: In the configuration of the dispersion value of the splitter port, the dispersion interval between adjacent splitter ports is fixed. The number of ports of the first-level splitter is n 1 , and the number of ports of the second-level splitter is n 2 , then the maximum number of supported users is n 1 ×n 2 ; Define the dispersion interval between the ports of the second-level splitter as d, and the dispersion unit is ps / nm. Then the dispersion interval between the ports of the first-level splitter is n 2 d, and the dispersion value configurations of the n 2 ports of the second-level splitter are [0, -d, -2d, …, -(n 2 - 1)d], where the dispersion value of the first port is 0, and the dispersion value of the n 2 th port is -(n 2 - 1)d. Therefore, the required maximum negative dispersion is -(n 2 - 1)d; The dispersion value configurations of the n 1 ports of the first-level splitter are [0, -n 2 d, -2n 2 d, …, -(n 1 - 1)n 2 d], where the dispersion value of the first port is 0, and the dispersion value of the n 1 th port is -(n 1 - 1)n 2 d. Therefore, the required maximum negative dispersion is -(n 1 - 1)n 2 d; For the i-th port of the second-level splitter, its port dispersion interval is For the i-th port of the first-level splitter, its port dispersion interval is By judging the port dispersion interval where the dispersion value estimated based on the digital signal processing (DSP) at the receiving end is located, the identification of the splitter port where the user is located is realized.

[0010] Preferably, the step S2 includes:

[0011] Step S2.1: In the downlink direction of the optical network unit (ONU), the digital signal processing unit (DSP) at the receiving end performs blind dispersion search on the dispersion value in the link, and initializes the dispersion value parameters of the dispersion compensation module (CDC) in the digital signal processing unit (DSP) at the receiving end.

[0012] Step S2.2: The digital signal processing unit (DSP) at the receiving end extracts the residual dispersion in the link based on the tap coefficients in the multiple-input multiple-output (MIMO) equalizer.

[0013] Step S2.3: Update the dispersion value of the chromatic dispersion compensation module (CDC) based on the residual dispersion extracted from the tap coefficients of the MIMO equalizer; repeat and trigger Steps S2.2 to S2.3 until the dispersion value parameter of the CDC converges, and obtain the final estimation result of the link dispersion.

[0014] Step S2.4: Compare the final estimation result of the link dispersion with the ranging result of the optical fiber link to obtain the negative dispersion value introduced through the splitter port, and identify the splitter port through the port negative dispersion value.

[0015] Preferably, Step S2.1 includes: in the estimation stage of the DSP at the receiving end of the optical network unit (ONU) downlink, after low-pass filtering (LPF) and front-end correction, the X and Y polarization received signals are respectively r X (t), r Y (t), the dispersion scanning interval is Δ, the minimum dispersion is α min , the number of scanned dispersion values is n, the i-th scanned dispersion value α i is α min +(i - 1)Δ, the maximum scanned dispersion value α max is α min +(n - 1)Δ, the Fourier transforms of the X and Y polarization signals r X (t) and r Y (t) are respectively r X (f) and r Y (f), and the X and Y polarization signals r X (f) and r Y (f) are respectively dispersion-compensated in the frequency domain using the i-th scanned dispersion value α i , and their output signals are respectively and

[0016]

[0017] where c is the speed of light and λ is the wavelength of light;

[0018] Take the inverse Fourier transform of and to obtain the signals and Take the fourth power of and ​ and obtain the frequency-domain signal through Fourier transform and when using the calculated dispersion value α corresponding to the maximum i is the result cd of the blind dispersion search 1 , and use cd 1 to initialize the first value cd[1] of the dispersion value parameter cd of the dispersion compensation module CDC in the decoding stage

[0019] Preferably, the step S2.2 includes: in the nth decoding stage of the digital signal processing unit DSP at the receiving end, the nth dispersion value parameter of the dispersion compensation module CDC is cd[n]. After low-pass filtering LPF and front-end correction, the signal is compensated based on the dispersion value parameter cd[n]. After frequency offset estimation FOE and synchronization, the X and Y polarization signals obtained are d X (t), d Y (t). Use d X (t) and d Y (t) to train the 2×2 MIMO equalizer. The MIMO equalizer is trained based on the least mean square LMS algorithm, and the error function is the least mean square error MSE. After the equalizer converges, the residual dispersion is extracted and estimated from the coefficient W(t), and the nth residual dispersion estimate value cd 2 [n] based on the tap coefficients of the MIMO equalizer is obtained

[0020] Preferably, the step S2.3 includes: in the decoding stage of the digital signal processing unit DSP at the receiving end, the first dispersion value parameter cd[1] in the dispersion compensation module CDC is initialized to cd[1]=cd 1 by the dispersion estimate value cd of the blind dispersion search 1 , and the nth dispersion value parameter of the dispersion compensation module CDC is cd[n], where n represents the number of operations of the digital signal processing unit DSP at the receiving end. The nth dispersion value extracted based on the tap coefficients of the MIMO equalizer is cd 2 [n]. Multiply cd 2 [n] by K p to obtain Δcd, where K pis a fixed coefficient greater than 0 and less than 1. The absolute value of Δcd is limited in t to obtain Δcd′, where t is a positive coefficient greater than 0. The dispersion value parameter of the dispersion compensation module CDC is updated with Δcd′ to obtain the dispersion value cd[n + 1] = cd[n] + Δcd′ for the (n + 1)-th digital signal processing unit DSP at the receiving end. Repeat the above process until the dispersion value parameter of the dispersion compensation module CDC converges. At this time, when the digital signal processing unit DSP at the receiving end runs m times, the final result cd f [m] is cd f [m] = cd[m].

[0021] Preferably, the step S2.4 includes:

[0022] The optical network unit ONU obtains the link distance l from the OLT end to the current user through uplink ranging. If the dispersion coefficient is D, the port dispersion value cd p [m] = cd f [m] - lD introduced through the port. The port number of the current ONU located between the first-stage splitter and the second-stage splitter is judged by the negative dispersion value of this port, so as to realize the distinction and identification of the splitter ports.

[0023] According to a splitter port identification system based on CD estimation in a coherent PON provided by the present invention, it includes:

[0024] Module M1: Add different negative dispersion values to different ports of the first-stage splitter and the second-stage splitter in the passive optical network PON;

[0025] Module M2: Extract and estimate the corresponding port dispersion value in the digital signal processing unit DSP at the receiving end of the optical network unit ONU, so as to realize the identification of the splitter port.

[0026] Preferably, the module M1 includes: In the dispersion value configuration of the splitter port, the dispersion interval between adjacent splitter ports is fixed. The number of ports of the first-stage splitter is n 1 , and the number of ports of the second-stage splitter is n 2 , then the maximum number of supported users is n 1 ×n 2 ; Define the dispersion interval between the ports of the second-stage splitter as d, and the dispersion unit is ps / nm. Then the dispersion interval between the ports of the first-stage splitter is n 2 d, and the dispersion value configurations of the n 2 ports of the second-stage splitter are respectively [0, -d, -2d,..., -(n 2 - 1)d], where the dispersion value of the first port is 0, and the dispersion value of the n 2 -th port is -(n 2-1)d, so the maximum required negative dispersion is -(n 2 -1)d; the dispersion values of the n ports of the first-level optical splitter 1 are configured as [0, -n 2 d, -2n 2 d, …, -(n 1 -1)n 2 d], where the dispersion value of the first port is 0, and the dispersion value of the nth 1 port is -(n 1 -1)n 2 d, so the maximum required negative dispersion is -(n 1 -1)n 2 d; for the ith port of the second-level optical splitter, its port dispersion range is For the ith port of the first-level optical splitter, its port dispersion range is By determining the port dispersion range in which the dispersion value estimated based on the digital signal processing (DSP) at the receiving end is located, the identification of the optical splitter port where the user is located is realized.

[0027] Preferably, the module M2 includes:

[0028] Module M2.1: In the downstream direction of the optical network unit (ONU), the digital signal processing unit (DSP) at the receiving end performs blind dispersion search on the dispersion value in the link, and initializes the dispersion value parameters of the dispersion compensation module (CDC) in the digital signal processing unit (DSP) at the receiving end;

[0029] Module M2.2: The digital signal processing unit (DSP) at the receiving end extracts the residual dispersion in the link based on the tap coefficients in the multiple-input multiple-output (MIMO) equalizer;

[0030] Module M2.3: Updates the dispersion value of the dispersion compensation module (CDC) based on the residual dispersion extracted from the tap coefficients of the multiple-input multiple-output (MIMO) equalizer; repeatedly triggers Module M2.2 to Module M2.3 until the dispersion value parameters of the dispersion compensation module (CDC) converge, and obtains the final estimated result of the link dispersion;

[0031] Module M2.4: Compares the final estimated result of the link dispersion with the ranging result of the optical fiber link, obtains the negative dispersion value introduced through the optical splitter port, and realizes the identification of the optical splitter port through the port negative dispersion value.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. By adding different negative dispersions to the ports of the primary splitter and secondary splitter in the PON, the present invention can distinguish the ports without adding additional transceiver modules on both the transmitting and receiving sides, nor deploying distributed fiber optic sensors or Bragg gratings to distinguish the splitter ports, effectively reducing the system cost and facilitating system maintenance. Moreover, the present invention is compatible with the system architecture of the next-generation coherent PON, improving the feasibility and practicality of the solution.

[0034] 2. The present invention extracts and estimates the dispersion of the splitter port in two stages through the digital signal processing unit DSP in the ONU downstream receiver. The two-stage dispersion extraction is a blind dispersion search algorithm and a residual dispersion extraction algorithm based on the tap coefficients of the MIMO equalizer. The accuracy of dispersion estimation is improved through the two-stage dispersion extraction algorithm, thereby improving the accuracy of splitter port identification.

[0035] 3. The dispersion extraction algorithm adopted by the present invention is compatible with the existing DSP algorithms of coherent PON, enabling the reuse of modules such as LPF, front-end correction, CDC, and MIMO equalizer in coherent PON, reducing the complexity of the algorithm, and achieving a reduction in system cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects, and advantages of the present invention will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0037] Figure 1 Schematic diagram of a splitter port identification system based on CD estimation in coherent PON.

[0038] Figure 2 Flowchart of the dispersion estimation algorithm based on blind dispersion search.

[0039] Figure 3 Flowchart of the residual dispersion extraction algorithm based on the tap coefficients of the MIMO equalizer.

[0040] Figure 4 A mean error and standard deviation result graph.

[0041] Figure 5 Result graph of port dispersion interval and port identification accuracy. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0043] Embodiment 1

[0044] Aiming at the problem that it is difficult to identify the splitter ports in the current PON, the technical problem to be solved by the present invention is to design a system solution and corresponding DSP algorithms for identifying splitter ports in the coherent PON scenario, so as to achieve high-precision identification of the ports of the first-level splitter and the second-level splitter in the ODN. Therefore, the present invention proposes a method and system for identifying splitter ports based on CD estimation in coherent PON. By introducing different negative dispersion values at different ports of the first-level splitter and the second-level splitter, a two-stage dispersion estimation algorithm is adopted in the DSP at the ONU receiving end to accurately extract and estimate the dispersion values of the corresponding ports, so as to achieve high-precision identification of the splitter ports. The present invention does not need to add additional transceiver modules on both the sending and receiving sides, can reuse the existing coherent DSP algorithms, and is compatible with the existing system architecture of coherent PON, so the superiority of this solution is highlighted.

[0045] The method for identifying splitter ports based on CD estimation in the coherent PON includes:

[0046] Step S1: Add different negative dispersion values at different ports of the first-level splitter and the second-level splitter in the PON to distinguish the splitter ports.

[0047] Step S2: In the downstream direction of the ONU, first, through the estimation stage in the receiving-end DSP algorithm, perform blind dispersion search on the dispersion value in the link, and initialize the dispersion value parameter of the dispersion compensation (CDC) module in the decoding stage of the receiving-end DSP algorithm.

[0048] Step S3: In the decoding stage of the receiving-end DSP algorithm, extract the residual dispersion in the link through the tap coefficients in the multi-input multi-output (MIMO) equalizer.

[0049] Step S4: Use the residual dispersion value extracted based on the tap coefficients of the MIMO equalizer to update the dispersion value parameter of the CDC module in multiple rounds until the dispersion value parameter of the CDC module converges. This dispersion value parameter is the final estimation result of the link dispersion.

[0050] Step S5: Compare the final estimation result of the link dispersion with the ranging result of the optical fiber link to obtain the negative dispersion value introduced through the splitter port, and identify the splitter port through this port negative dispersion value.

[0051] Specifically, the step S1 includes: As Figure 1 shown, add different negative dispersion values at different ports of the first-level splitter and the second-level splitter in the PON to distinguish the splitter ports. In the dispersion value configuration of the splitter ports, the dispersion interval between adjacent splitter ports is fixed, and the number of ports of the first-level splitter is n1 , the number of ports of the secondary optical splitter is n 2 , then the maximum number of supported users is n 1 ×n 2 , define the dispersion interval between ports of the secondary optical splitter as d, and the dispersion unit is ps / nm, then the dispersion interval between ports of the primary optical splitter is n 2 d, and the dispersion values of the n 2 ports of the secondary optical splitter are configured as [0, -d, -2d, …, -(n 2 - 1)d], where the dispersion value of the first port is 0, and the dispersion value of the n 2 th port is -(n 2 - 1)d. Therefore, the required maximum negative dispersion is -(n 2 - 1)d, and the dispersion values of the n 1 ports of the primary optical splitter are configured as [0, -n 2 d, -2n 2 d, …, -(n 1 - 1)n 2 d], where the dispersion value of the first port is 0, and the dispersion value of the n 1 th port is -(n 1 - 1)n 2 d. Therefore, the required maximum negative dispersion is -(n 1 - 1)n 2 d. For the i-th port of the secondary optical splitter, its port dispersion interval is For the i-th port of the primary optical splitter, its port dispersion interval is By judging the port dispersion interval where the dispersion value estimated based on the receiving-end DSP is located, the identification of the optical splitter port where the user is located can be realized.

[0052] Specifically, the step S2 includes: when the receiving-end DSP in the ONU downlink is first run, execute the blind dispersion search algorithm in the estimation stage, as Figure 2 shown. After low-pass filtering (LPF) and front-end correction, the X and Y polarization received signals are respectively r X (t), r Y (t), the dispersion scanning interval is Δ, the minimum dispersion is α min , the number of scanned dispersion values is n, and the i-th scanned dispersion value α i is α min + (i - 1)Δ, the maximum scanned dispersion value α max is α min + (n - 1)Δ, and the Fourier transforms of the X polarization and Y polarization signals r X (t) and r Y (t) are respectively r X (f) and r Y(f), for the signals r of X polarization and Y polarization X (f) and r Y (f) respectively adopt the i-th scanning dispersion value α i Perform dispersion compensation in the frequency domain, and the output signals are respectively and The corresponding calculation formula is and where c is the speed of light, λ is the wavelength of light, for and Perform inverse Fourier transform to obtain the time-domain signals and For and The fourth power of and Perform Fourier transform to obtain the frequency-domain signals and When using Calculated The α corresponding to the maximum i Is the result cd of dispersion estimation 1 , the blind dispersion search algorithm is only executed when the receiver DSP is run for the first time, and the result cd of its dispersion estimation 1 Initializes the first value cd[1] of the dispersion value parameter cd of the CDC module in the decoding stage of the receiver DSP, that is, cd[1] = cd 1 .

[0053] Specifically, the step S3 includes: in the decoding stage of the receiver DSP, the value of the first dispersion value parameter cd[1] of the CDC module is cd 1 , the n-th dispersion value parameter of the CDC module is cd[n], where n represents the number of times the receiver DSP algorithm runs. When the decoding stage of the receiver DSP is run for the n-th time, the received signal passes through the LPF and front-end correction, and is compensated based on the dispersion value parameter cd[n] in the CDC module. The compensated signal passes through the FOE and synchronization to obtain the X and Y polarization signals d X (t), d Y (t), as Figure 3 Shown, using d X (t) and d Y (t) train the 2×2 MIMO equalizer. The MIMO equalizer is trained based on the LMS algorithm, and the error function is MSE. When MSE is less than a specific threshold e, it is considered that the training of the equalizer converges. The equalizer coefficients after convergence are Its Fourier transform is The determinant of the W(f) matrix is det(W(f)), and the phase response determined by dispersion extracted by the MIMO equalizer taps is Since the influence of dispersion on the phase is quadratic, taking the frequency f as the independent variable and the phase response p as the dependent variable, a quadratic fit is performed on the phase response curve. The quadratic term in the fitted quadratic curve is b. Then, when the decoding stage of the receiver DSP runs for the nth time, the residual dispersion estimate value extracted based on the MIMO equalizer tap coefficients is

[0054] Specifically, step S4 includes: in the decoding stage of the receiver DSP, the first dispersion value parameter cd[1] in the CDC module is initialized to cd[1]=cd with the dispersion estimate value cd 1 obtained by blind dispersion search. 1 The nth dispersion value parameter of the CDC module is cd[n], where n represents the number of runs of the receiver DSP algorithm. The nth dispersion value extracted based on the MIMO equalizer tap coefficients is cd 2 [n]. Multiply cd 2 [n] by K p to obtain Δcd, where K p is a fixed coefficient greater than 0 and less than 1. Limit the absolute value of Δcd to t to obtain Δcd'. Here, t is a positive coefficient greater than 0. When Δcd is negative and its absolute value is greater than t, Δcd'=-t; when Δcd is positive and its absolute value is greater than t, Δcd'=t; when the absolute value of Δcd is less than t, Δcd'=Δcd. Update the dispersion value parameter of the CDC module with Δcd' to obtain the CDC dispersion value parameter for the (n + 1)th run of the receiver DSP as cd[n + 1]=cd[n]+Δcd'. Repeat the above process until the dispersion value parameter cd of the CDC module converges. At this time, after the receiver DSP runs m times, the final result of the dispersion estimate cd f [m]=cd[m].

[0055] Specifically, step S5 includes: the ONU obtains the link distance from the OLT to the current user as l through uplink ranging. The dispersion coefficient is D. Then, the port dispersion value cd p [m] introduced by the port is cd f [m]-lD. Determine the port numbers of the current ONU at the first-stage splitter and the second-stage splitter through this port dispersion value to achieve the distinction and identification of the splitter ports.

[0056] The present invention also provides a splitter port identification system based on CD estimation in a coherent PON. The splitter port identification system based on CD estimation in the coherent PON can be implemented by executing the process steps of the splitter port identification method based on CD estimation in the coherent PON. That is, those skilled in the art can understand the splitter port identification method based on CD estimation in the coherent PON as a preferred embodiment of the splitter port identification system based on CD estimation in the coherent PON.

[0057] Embodiment 2

[0058] Embodiment 2 is a preferred example of Embodiment 1

[0059] According to a splitter port identification technology based on CD estimation in coherent PON provided by the present invention, in order to verify the effectiveness of this technology, the proposed technical solution was verified in a band-limited C-band coherent PON system. In the transmitter, the random bit sequence is respectively mapped into quadrature phase shift keying (QPSK) and 16-quadrature amplitude modulation (16-QAM) symbols with a rate of 240 Gbps, and pulse shaping is performed using a root-raised cosine (RRC) filter with a roll-off factor of 0.1. Subsequently, the signal is sent by a four-channel arbitrary waveform generator (AWG) with a sampling rate of 80 GSa / s and modulated by a coherent driver modulator (CDM) with a bandwidth of 40 GHz. Its light source is generated by an external cavity laser (ECL) with a working wavelength of 1545 nm, and the output optical power is 14.5 dBm. The modulated optical signal is amplified to 12 dBm by an erbium-doped fiber amplifier (EDFA) and then input into the optical fiber for transmission. In the optical fiber channel, 15 km and 5 km standard single-mode fibers (SSMF) are respectively used to simulate the two-stage splitter structure of PON. After each section of the optical fiber, a section of dispersion compensating fiber (DCF) is added to simulate the negative dispersion value of the port. By cascading different DCFs, the magnitude of the negative dispersion value can be changed. At the receiving end, a variable optical attenuator (VOA) is used to adjust the received optical power (ROP). The optical signal after attenuation is received by an integrated coherent receiver (ICR) with a bandwidth of 40 GHz and converted into four-channel electrical signals, and then extracted by two digital storage oscilloscopes (DSO) with a sampling rate of 100 GSa / s. Finally, offline DSP is performed, including LPF, front-end correction, CDC, FOE, synchronization, MIMO equalization, and carrier phase recovery CPR. The implementation steps of the dispersion estimation algorithm are as follows:

[0060] S1: After the experimental system receives data, it first performs LPF and front-end correction on the signal sequence in the estimation stage. The processed data is used to obtain the dispersion estimation value cd through blind dispersion search. 1 , and uses cd 1 to initialize the first dispersion value parameter cd[1] of the CDC module in the decoding stage.

[0061] S2: In the decoding stage, after performing LPF, front-end correction, CDC, FOE, synchronization, and MIMO equalization on the received data, based on the tap coefficients of the MIMO equalizer, phase extraction and quadratic fitting are performed to obtain the dispersion estimation value cd. 2 , and uses cd 2 to continuously update the dispersion value parameter of the CDC module in the decoding stage.

[0062] S21: Conduct multiple groups of experiments, and update the dispersion value parameter of the CDC module in each experiment until the dispersion value parameter of the CDC module converges in the m-th experiment, obtaining the corresponding final dispersion estimation value cd f [m]. Statistically calculate the mean and standard deviation of a total of 200 final dispersion estimation values from the m-th to the m + 199-th experiments.

[0063] S22: Perform Gaussian fitting on the distribution of experimental data through the mean and standard deviation, and calculate the probability that the dispersion estimation value falls within the target dispersion interval through the fitted Gaussian distribution, which is the recognition accuracy of the port.

[0064] S3: By changing the DCF after 15 km and 5 km of SSMF, the negative dispersion value of the port is changed. In the experiment, two cases where the total negative dispersion value of the port is -4612.6 ps / nm and -1158.7 ps / nm are respectively tested, and the recognition accuracy of the port is calculated through statistical experiments.

[0065] S4: This example also gives the schematic diagrams of the mean error, standard deviation of the dispersion estimation based on this system, and the results of the port recognition accuracy, as shown in Figure 4 and 5 . For the dispersion estimation results of 30 GBaud / s 16QAM and 60 GBaud / s QPSK signals, the absolute value of the mean error is within 7 ps / nm, and the standard deviation is within 0.5 ps / nm, indicating that the dispersion estimation algorithm can achieve stable and accurate dispersion estimation. The schematic diagram of the implementation result of the port recognition accuracy is as shown in Figure 5 . When the port dispersion interval is 15.2 ps / nm, the port recognition accuracy is 95%. When the port dispersion interval is 15.75 ps / nm, the port recognition accuracy is 99%. When the port dispersion interval is 17.8 ps / nm, the port recognition accuracy is 100%.

[0066] In the above technical solution, the standard deviation of the CD estimated value is within 0.5 ps / nm, and the absolute value of the mean error is within 7 ps / nm, indicating that the proposed optical splitter port identification scheme based on CD estimation can accurately and stably identify the primary optical splitter ports and secondary optical splitter ports. When the dispersion interval between ports is 17.8 ps / nm, a 100% port identification accuracy rate can be achieved. This technical solution does not require additional transceiver modules on both the transmitting and receiving sides, is compatible with existing coherent DSPs, and can be flexibly applied to PON systems with any number of optical splitter ports.

[0067] In the coherent PON, the optical splitter port identification technology based on CD estimation described in this embodiment distinguishes the optical splitter ports by adding devices with different negative dispersion values at the primary optical splitter and secondary optical splitter ports, and accurately extracts the dispersion through a two-stage dispersion estimation algorithm in the ONU downlink, thereby completing the binding between the user and the optical splitter port. The proposed method does not require additional transceiver modules on both the transmitting and receiving sides, is compatible with the DSP algorithm of the coherent receiver, and can be applied to future 200G coherent PON systems.

[0068] Those skilled in the art know that in addition to implementing the systems, devices, and their respective modules provided by the present invention in the form of pure computer-readable program codes, the method steps can be logically programmed to enable the systems, devices, and their respective modules provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc., to achieve the same program. Therefore, the systems, devices, and their respective modules provided by the present invention can be regarded as a kind of hardware component, and the modules included therein for implementing various programs can also be regarded as the structures within the hardware component; the modules for implementing various functions can also be regarded as either software programs for implementing the methods or the structures within the hardware component.

[0069] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined arbitrarily with each other.

Claims

1. A method for identifying a splitter port in a coherent PON based on CD estimation, characterized in that: include: Step S1: adding different negative dispersion values ​​to different ports of a primary optical splitter and a secondary optical splitter in a passive optical network PON; Step S2: extracting and estimating the dispersion value of the corresponding port in the digital signal processing unit DSP of the receiving end of the optical network unit ONU, so as to realize the identification of the splitter port.

2. The method for identifying optical splitter ports based on CD estimation in a coherent PON according to claim 1, characterized in that: The step S1 comprises: in the dispersion value configuration of the splitter port, the dispersion interval between adjacent splitter ports is fixed, the number of the first-level splitter ports is n1, the number of the second-level splitter ports is n2, and the maximum number of users that can be supported is n1×n2; the dispersion interval between the second-level splitter ports is defined as d, and the dispersion unit is ps / nm, then the dispersion interval between the first-level splitter ports is n2d, and the dispersion value configurations of the n2 ports of the second-level splitter are respectively [0, -d, -2d, ..., -(n2-1)d], wherein The dispersion value of the first port is 0, and the dispersion value of the n2th port is -(n2-1)d, so the maximum negative dispersion required is -(n2-1)d; the dispersion value of the n1 port of the first-level splitter is configured as [0,-n2d,-2n2d,…,-(n1-1)n2d], ​​where the dispersion value of the first port is 0, and the dispersion value of the n1th port is -(n1-1)n2d, so the maximum negative dispersion required is -(n1-1)n2d; for the i-th port of the second-level splitter, its port dispersion range is For the i-th port of the first-stage optical splitter, its port dispersion range is By determining the port dispersion interval where the dispersion value estimated by the receiving end digital signal processing DSP is located, the splitter port where the user is located can be identified.

3. The method for identifying optical splitter ports based on CD estimation in a coherent PON according to claim 1, characterized in that: The step S2 comprises: Step S2.1: In the downstream direction of the optical network unit ONU, a blind dispersion search is performed on the dispersion value in the link through the digital signal processing unit DSP at the receiving end, and the dispersion value parameters of the dispersion compensation module CDC in the digital signal processing unit DSP at the receiving end are initialized; Step S2.2: extracting residual dispersion in the link based on tap coefficients in a multiple-input multiple-output MIMO equalizer through a digital signal processing unit DSP at the receiving end; Step S2.3: updating the dispersion value of the dispersion compensation module CDC based on the residual dispersion extracted by the tap coefficients of the multiple-input multiple-output MIMO equalizer; repeatedly triggering steps S2.2 to S2.3 until the dispersion value parameters of the dispersion compensation module CDC converge, and obtaining the final estimation result of the link dispersion; Step S2.4: Compare the final estimation result of the link dispersion with the distance measurement result of the optical fiber link to obtain the negative dispersion value introduced by the splitter port, and identify the splitter port through the negative dispersion value of the port.

4. The method for identifying optical splitter ports based on CD estimation in a coherent PON according to claim 3, characterized in that: The step S2.1 comprises: in the estimation stage of the digital signal processing unit DSP at the receiving end of the optical network unit ONU downlink, after low-pass filtering LPF and front-end correction, the X and Y polarization receiving signals are r X (t), r Y (t), the dispersion scanning interval is Δ, and the minimum dispersion is α min , the number of scanned dispersion values ​​is n, the i-th scanned dispersion value α i is α min +(i-1)Δ, maximum scanning dispersion value α max is α min +(n-1)Δ, X polarization and Y polarization signal r X (t) and r Y The Fourier transform of (t) is r X (f) and r Y (f), for X-polarized and Y-polarized signals r X (f) and r Y (f) Using the i-th scanning dispersion value α i Dispersion compensation is performed in the frequency domain, and the output signals are and in, c is the speed of light, λ is the wavelength of light; right and Find the inverse Fourier transform to get the signal and right and The fourth power and Calculate the Fourier transform to get the frequency domain signal and When used Calculated The maximum dispersion value α i The result of the blind dispersion search is cd1, and cd1 is used to initialize the first value cd[1] of the dispersion value parameter cd of the dispersion compensation module CDC in the decoding stage.

5. The method for identifying optical splitter ports based on CD estimation in a coherent PON according to claim 3, characterized in that: The step S2.2 comprises: in the nth decoding stage of the digital signal processing unit DSP at the receiving end, the nth dispersion value parameter of the dispersion compensation module CDC is cd[n], after low-pass filtering LPF and front-end correction, the signal is compensated based on the dispersion value parameter c[n], and the compensated signal is subjected to frequency offset estimation FOE and synchronization to obtain X and Y polarization signals d respectively. X (t), d Y (t), using d X (t) and d Y (t) The 2×2 MIMO equalizer is trained based on the least mean square (LMS) algorithm. The error function is the minimum mean square error (MSE). After the equalizer converges, the residual dispersion is extracted and estimated from the coefficient W(t) to obtain the nth residual dispersion estimate cd2[n] extracted based on the MIMO equalizer tap coefficients.

6. The method for identifying optical splitter ports based on CD estimation in a coherent PON according to claim 3, characterized in that: The step S2.3 comprises: in the decoding stage of the receiving end digital signal processing unit DSP, the first dispersion value parameter cd[1] in the dispersion compensation module CDC is initialized to cd[1]=cd1 by the dispersion estimation value cd1 based on the blind dispersion search, the nth dispersion value parameter of the dispersion compensation module CDC is cd[n], wherein n represents the number of times the receiving end digital signal processing unit DSP is run, the nth dispersion value extracted based on the MIMO equalizer tap coefficient is cd2[n], cd2[n] is multiplied by K p Get Δcd, where K p is a fixed coefficient greater than 0 and less than 1, the absolute value of Δcd is limited to t to obtain Δcd′, where t is a positive coefficient greater than 0, and Δcd′ is used to update the dispersion value parameter of the dispersion compensation module CDC, and the dispersion value cd[n+1]=cd[n]+Δcd′ for the n+1th receiving end digital signal processing unit DSP is obtained. The above process is repeated until the dispersion value parameter of the dispersion compensation module CDC converges. At this time, when the receiving end digital signal processing unit DSP runs m times, the final result of the dispersion estimation cd f [m] stands for cd f [m] = cd[m].

7. The method for identifying optical splitter ports based on CD estimation in a coherent PON according to claim 3, characterized in that: The step S2.4 comprises: The optical network unit ONU obtains the link distance from the OLT to the current user through uplink ranging as l, and the dispersion coefficient is D. Then the port dispersion value cd introduced by the port is p [m] = cd f [m]-lD, the negative dispersion value of the port is used to determine the port number of the current ONU located on the primary splitter and the secondary splitter, so as to distinguish and identify the splitter ports.

8. A splitter port identification system based on CD estimation in a coherent PON, characterized in that: include: Module M1: Add different negative dispersion values ​​to different ports of the primary splitter and the secondary splitter in the passive optical network PON; Module M2: extracts and estimates the dispersion value of the corresponding port in the digital signal processing unit DSP of the receiving end of the optical network unit ONU, thereby realizing the identification of the splitter port.

9. The optical splitter port identification system based on CD estimation in a coherent PON according to claim 8, characterized in that: The module M1 includes: in the dispersion value configuration of the splitter port, the dispersion interval between adjacent splitter ports is fixed, the number of primary splitter ports is n1, the number of secondary splitter ports is n2, and the maximum number of supported users is n1×n2; the dispersion interval between the secondary splitter ports is defined as d, the dispersion unit is ps / nm, the dispersion interval between the primary splitter ports is n2d, and the dispersion value configurations of the n2 ports of the secondary splitter are [0, -d, -2d, ..., -(n2-1)d] respectively, wherein The dispersion value of the first port is 0, and the dispersion value of the n2th port is -(n2-1)d, so the maximum negative dispersion required is -(n2-1)d; the dispersion value of the n1 port of the first-level splitter is configured as [0,-n2d,-2n2d,…,-(n1-1)n2d], ​​where the dispersion value of the first port is 0, and the dispersion value of the n1th port is -(n1-1)n2d, so the maximum negative dispersion required is -(n1-1)n2d; for the i-th port of the second-level splitter, its port dispersion range is For the i-th port of the first-stage optical splitter, its port dispersion range is By determining the port dispersion interval where the dispersion value estimated by the receiving end digital signal processing DSP is located, the splitter port where the user is located can be identified.

10. The optical splitter port identification system based on CD estimation in coherent PON according to claim 8, characterized in that: The module M2 comprises: Module M2.1: In the downstream direction of the optical network unit ONU, the digital signal processing unit DSP at the receiving end performs blind dispersion search on the dispersion value in the link, and initializes the dispersion value parameters of the dispersion compensation module CDC in the digital signal processing unit DSP at the receiving end; Module M2.2: extract the residual dispersion in the link based on the tap coefficients in the multiple-input multiple-output MIMO equalizer through the digital signal processing unit DSP at the receiving end; Module M2.3: Update the dispersion value of the dispersion compensation module CDC based on the residual dispersion extracted by the tap coefficients of the multi-input multi-output MIMO equalizer; repeatedly trigger modules M2.2 to M2.3 until the dispersion value parameters of the dispersion compensation module CDC converge, and obtain the final estimation result of the link dispersion; Module M2.4: Compare the final estimation result of the link dispersion with the distance measurement result of the optical fiber link, obtain the negative dispersion value introduced by the splitter port, and identify the splitter port through the negative dispersion value of the port.

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