Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED OFFICE ACTION
Information Disclosure Statement
The information disclosure statement (IDS) submitted on December 18, 2024 in compliance with the provisions of 37 CFR 1.97 has been considered by the examiner and made of record in the application file.
Claim Status
Claims 1-16 are pending in this application and are under examination in this Office Action. No claims have been allowed.
Priority
Applicant's claim for foreign priority to Japan Patent Application No. 2023-214694, filed December 20, 2023, is acknowledged.
Claim Objections
Claims 1, 8, 9, 14 and 15 are objected to because of the following informalities. Appropriate correction is required.
Regarding claim 1,
Claim 1 recites the processor as being "configured to acquire" first polarization characteristic values and then recites that the processor "acquires" second polarization characteristic values. The change from "acquire" to "acquires" interrupts the grammatical parallelism of the "configured to" limitation. Claim 1 also recites "information that represent an operation state," which contains a subject-verb agreement error. These are treated as minor informalities because, standing alone, they do not prevent the scope of claim 1 from being reasonably ascertained. Appropriate correction is required.
Regarding claim 8,
Claim 8 recites a processor "configured to" acquire and calculate, but later uses "calculates" and then returns to "estimate." The inconsistent verb forms within the same "configured to" series are grammatical informalities. Appropriate correction is required. The separate substantive indefiniteness concerning "the first polarization characteristic average values of the combined section" is addressed below under 35 U.S.C. 112(b).
Regarding claim 9,
Claim 9 recites a reception node arranged at "the another end" of the optical network. The phrase is grammatically improper; the intended relationship should be stated using clear and grammatically consistent terminology. Appropriate correction is required.
Regarding claim 14,
Claim 14 recites "wherein processor acquires" rather than using a grammatically complete reference to the previously recited processor. Appropriate correction is required.
Regarding claim 15,
Claim 15 recites a loss index that represents "power loss of the signal light that occur in a section." The subject-verb agreement should be corrected. Appropriate correction is required.
Claim Rejections - 35 U.S.C. § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 4 and 8 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Regarding claim 4,
Claim 4 recites that the processor is configured to "specify a part of the plurality of wavelengths in ascending order of the number until matching a threshold bandwidth."
The phrase "until matching a threshold bandwidth" does not define with reasonable certainty the endpoint of the claimed wavelength-selection operation. First, claim 4 does not identify what bandwidth associated with the selected "part of the plurality of wavelengths" is being compared with the threshold bandwidth. The selected wavelengths are ordered according to the number of second sections, and the claim does not require the selected wavelengths to be contiguous or otherwise state how their collective bandwidth is to be determined. Second, the word "matching" is reasonably susceptible to materially different meanings, including becoming exactly equal to the threshold, reaching at least the threshold, or exceeding the threshold.
The ambiguity is not resolved by the originally filed disclosure. Paragraphs [0093]-[0096] and FIG. 10 describe determining whether a predetermined threshold bandwidth "has been exceeded" and repeating channel selection until the predetermined threshold bandwidth is "exceeded." Thus, the disclosure uses an exceedance condition rather than the "matching" condition recited in claim 4. These alternatives may result in a different
set of selected wavelengths, particularly where the selected channels do not produce a bandwidth exactly equal to the threshold. As written, it is unclear what condition terminates the selection of the claimed "part of the plurality of wavelengths." Accordingly, the metes and bounds of claim 4 are not reasonably certain, and claim 4 is indefinite.
Regarding claim 8,
Claim 8 first recites "a first polarization characteristic average value" in the singular and defines that value as an average value of first polarization characteristic values common to the first sections. Claim 8 then recites "a second polarization characteristic average value" for a combined section and requires that second average value to be calculated "based on the first polarization characteristic values and the first polarization characteristic average values of the combined section." There is a lack of clear antecedent basis for "the first polarization characteristic average values of the combined section." The claim previously introduces only a singular "first polarization characteristic average value," and that singular value is associated with first polarization characteristic values common to the first sections. The claim does not previously define plural "first polarization characteristic average values" that are "of the combined section." The ambiguity is material because the unidentified plural values are expressly recited as inputs used to calculate the second polarization characteristic average value.
The originally filed specification does not cure the ambiguity. Paragraph [0099] identifies the average value of PMD values of a common separate section as an example of a first polarization characteristic average value. Paragraph [0100] separately identifies the average value of PMD values of a combined separate section as an example of a second polarization characteristic average value. Paragraphs [0100]-[0102] further describe particular calculations using an average value of one separate section together with a PMD value or another calculated average value. Accordingly, it remains unclear from claim 8 whether "the first polarization characteristic average values of the combined section" refers to (i) the previously recited singular first polarization characteristic average value, (ii) multiple first average values corresponding to constituent first sections, (iii) one or more values already associated with the combined section, or (iv) some other combination of raw and previously calculated polarization characteristic values. These alternatives define different calculation inputs and therefore different claim scope. Claim 8 further recites "when there is none of the second sections adjacent to the combined section in a transmission direction of signal light that includes any of the plurality of wavelengths." As written, it is unclear whether the absence of an adjacent second section must be determined for every wavelength, for any one wavelength, or for the combined section without regard to a particular wavelength. The disclosure at paragraphs [0103]-[0106] and FIG. 13 instead describes determining whether there is no combinable section and then separately determining whether there is an out-of-service operation section in the transmission direction. The claim does not
clearly state how those disclosed conditions correspond to the recited "none of the second sections adjacent" condition. This additional ambiguity further prevents the boundaries of claim 8 from being determined with reasonable certainty.
Accordingly, claims 4 and 8 are indefinite under 35 U.S.C. 112(b).
Claim Rejections – 35 U.S.C. § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for the obviousness rejections set forth in this Office Action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
As reiterated by the Supreme Court in KSR, and as set forth in MPEP 2141 (R-01.2024), II, the factual inquiries of Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), applied for establishing a background for determining obviousness under 35 U.S.C. § 103, are summarized as follows:
1. Determining the scope and content of the prior art;
2. Ascertaining the differences between the prior art and the claims at issue;
3. Resolving the level of ordinary skill in the pertinent art; and
4. Considering objective evidence indicative of obviousness or non-obviousness, if present.
This application currently names joint inventors. In considering patentability of the claims, the examiner presumes that the subject matter disclosed in the prior art was created by another (i.e., not by the inventive entity) unless proven otherwise. Applicant is advised of the obligation under 37 C.F.R. § 1.56 to point out the inventor and effective filing dates of each claim, and any evidence of common ownership/assignment as of the effective filing date, so that the examiner may properly consider the applicability of 35 U.S.C. § 102(b)(2)(C) for any potential 35 U.S.C. § 102(a)(2) prior art against the claimed invention(s).
The claimed subject matter concerns optical-network performance monitoring, PMD/polarization-characteristic measurement and estimation, wavelength-aware network management, coherent optical receivers, and time-series signal-quality estimation. The cited references are from the same or closely analogous optical-communications field and address the same types of optical paths, wavelengths, PMD/DGD measurements, network controllers, signal-quality indicators, and network-state changes.
Claim 1 is rejected under 35 U.S.C. § 103 as being unpatentable over Sakamoto et al. (US20110229128A1) in view of Chen (US20100272431A1), further in view of ITU-T Recommendation G.680 (07/2007).
Claim 1
Claim 1 recites an optical transmission path characteristic estimation device that estimates a polarization characteristic value of an optical path in which first sections that are in service operation of an optical communication service using a plurality of wavelengths and second sections that are out of the service operation are mixed; a memory; and a processor configured to acquire first polarization characteristic values for each wavelength in the first sections and second polarization characteristic values for each wavelength in the second sections, based on information representing the operation state of the optical communication service, and to calculate wavelength-specific polarization characteristic values of the optical path for each wavelength based on the first and second polarization characteristic values.
Sakamoto states: “Hereinafter, preferred embodiments of the disclosed technology will be described in detail and with reference to the attached drawings. The disclosed technology may be provided with, for example, a signal generator and a monitor for a measurement signal whose PMD characteristics are measured at each optical node, thereby making it possible to measure the per-span PMD characteristics (i.e., DGD values). The signal generator is provided in at least one optical node, and may be configured such that PMD characteristics are measured on a per-span basis by the signal processing of the monitor. The measurement signal uses signal light whose wavelength is not being used in the primary signal or primary signal band, or alternatively, signal light that is outside the primary signal band. In addition, by collecting PMD characteristics from individual optical nodes, a network management system or similar apparatus may compute the change in PMD characteristics (i.e., mean PMD values) over a fixed period of time, and both network administration as well as signal path controls may be conducted.” [Sakamoto, ¶ [0034]; FIGS. 1, 6, 13-14].
This passage expressly teaches the underlying optical-network measurement architecture: multiple nodes and spans, PMD/DGD as the polarization characteristic, per-span measurement, collection by a network-management system, and network administration based on those measurements. Sakamoto also expressly places a measurement signal on wavelengths not used by the primary traffic. Although Sakamoto does not use the exact claim terminology of a physical 'first section' and 'second section,' its span-resolved measurements and operating/non-operating wavelength information provide the state-resolved data from which those section conditions are identified in the combined system.
Sakamoto states: “During system operation, the optical nodes N1 to N4 each send operating wavelength information to the NMS 130 (operations S1401 to S1404), and the NMS 130 acquires information regarding the operating wavelengths on the network from each of the optical nodes N1 to N4 (operation S1405). Subsequently, when acquiring DGD values, acquisition instructions for each transmission span are issued.” [Sakamoto, ¶ [0069]; FIG. 14].
Thus, Sakamoto expressly provides operation-state information material to the claim: during actual system operation, the network nodes report which wavelengths are operating, and the NMS uses that information when issuing per-span PMD/DGD acquisition instructions. The reported operating-wavelength information distinguishes resources carrying service from resources not carrying service on a span-by-span, wavelength-by-wavelength basis.
Sakamoto states: “First, DGD acquisition instructions for the span L1 are issued (operation S1406). By means of these acquisition instructions, the optical node N1 (102) provided with the signal generator 120 on the span L1 uses the signal generator 120 to output a measurement signal with the signal generator 120 that sweeps all wavelengths other than the operating wavelengths (operation S1407). Meanwhile, in the optical node N2 (110a) provided with the monitor 121 that measures measurement signals on the span L1, the monitor 121 is used to measure the DGD values on all wavelengths, including the operating wavelengths (operation S1408).” [Sakamoto, ¶ [0070]; FIG. 14].
The foregoing passage is particularly important to claim 1. It expressly distinguishes operating wavelengths from non-operating wavelengths using network-state information, measures DGD on operating wavelengths, and sends measurement light on wavelengths other than the operating wavelengths.
Accordingly, Sakamoto supplies measured polarization-characteristic values for operating wavelength resources and a controlled measurement mechanism for non-operating wavelength resources. The additional circumstance recited by claim 1 that active and inactive portions are mixed along a deployed path is reinforced by Chen's in-service/dark-channel testing and Sakamoto's express ability to measure spans having no primary signal.
Sakamoto states: “The configuration illustrated in FIG. 7 is able to measure the DGD regardless of whether the primary signal is operational or non-operational, and may even measure the DGD in the case where there are no operating wavelengths in the primary signal. For example, the DGD may also be measured by using only OSC light among the optical nodes, before primary signal connections are made.” [Sakamoto, ¶ [0053]; FIG. 7].
Sakamoto states: “According to this configuration, it becomes possible to monitor polarization mode dispersion without affecting the primary signal, and even on spans with no primary signal.” [Sakamoto, ¶ [0061]; FIGS. 10-11].
These disclosures expressly teach measuring the claimed polarization characteristic in both operating and non-operating conditions and, importantly, on spans having no primary signal. They therefore supply the technical mechanism for measuring an out-of-service section without disturbing revenue-bearing traffic.
Chen states: “In accordance with an exemplary implementation, test devices for in-service testing may be configured to provide testing for an optical path in network 100 without taking any of nodes 110 out of service. For example, FIG. 3 illustrates an exemplary scenario in network 100 in which a transmitter test device 300 and a receiver test device 310 may be used to test an optical path, such as path 1 illustrated in FIG. 2. Referring to FIG. 3, test device 300 may represent a transmitter device used to generate and transmit a test signal on a selected channel at node 110-1 (e.g., a channel not currently being used for normal traffic).” [Chen, ¶ [0022]; FIGS. 2-3].
Chen states: “For example, when it is determined that a particular channel in a path through network 100 is not currently used (e.g., is “dark”), test devices 300 and 310 may be configured to, through compensation, identify PMD and RCD values corresponding to the path.” [Chen, ¶ [0038]; FIGS. 3-6].
Chen independently confirms the service-preserving context needed by claim 1: a deployed optical path is tested while network nodes remain in service, and a channel that is not currently used for normal traffic (a 'dark' channel) is intentionally selected to obtain PMD/RCD measurements. Read together with Sakamoto's per-span operating-wavelength map and its ability to measure spans having no primary signal, Chen supplies a concrete implementation for obtaining the second-section measurements without interrupting the first/in-service sections.
The references therefore address complementary parts of the same deployed-network problem rather than unrelated functions: Sakamoto supplies per-span/per-wavelength PMD acquisition under operating and non-operating conditions, while Chen supplies an in-service dark-resource testing discipline for a path that otherwise remains operational.
Sakamoto states: “According to this configuration, a wavelength control signal is output from the NMS 130, and by means of a control for varying the output wavelength of the wavelength-variable optical source 801, DGD values are measured with respect to all wavelengths inside the primary signal band.” [Sakamoto, ¶ [0056]; FIG. 8].
Sakamoto states: “Also, in this configuration, signal generators 120 and monitors 121 disposed in respective optical nodes (N1 to N4) may be used to individually measure DGD values on specific spans L1, L2, and L3 in the primary signal band.” [Sakamoto, ¶ [0068]; FIGS. 13-14].
Sakamoto accordingly teaches values resolved by wavelength and by span. What remains to obtain the claimed wavelength-specific polarization characteristic of the overall optical path is the known optical-link operation of combining the per-section PMD contributions for the same wavelength.
ITU-T G.680 states: “The PMD of an optical fibre cable is specified according to a statistical format that can be combined with the other elements of the optical link to determine a maximum DGD that is defined as a probability limit.” [ITU-T G.680, § 9.3.1, p. 22].
ITU-T G.680 then provides Equation (9-6), which combines PMD/DGD contributions from the optical fiber and cascaded components by a root-sum-square relationship, and identifies each PMDCi as the PMD value of the ith component. [ITU-T G.680, § 9.3.1, p. 22, Eq. (9-6)].
Thus, the standard teaches the recognized mathematical treatment for combining polarization-dispersion contributions of cascaded optical sections/elements into the characteristic of the complete optical path.
One of ordinary skill in the art would have been motivated to combine Sakamoto with Chen because both references address the same technical problem: obtaining PMD/DGD characteristics of deployed optical networks without unnecessarily interrupting live optical service.
Sakamoto already teaches a network-management system that knows the operating wavelengths, measures operating wavelengths, sweeps non-operating wavelengths, and can measure spans having no primary signal.
Chen expressly teaches the service-preserving implementation of selecting an unused/dark channel and testing an optical path while the nodes remain in service. Applying Chen’s in-service/dark-channel testing discipline to Sakamoto’s per-span, per-wavelength PMD measurement would have predictably allowed the controller to obtain measured PMD values for the portions of a route having live traffic and for portions/wavelength resources that are not carrying service, without disturbing active traffic.
A person of ordinary skill would also have been motivated to use the combination rule of ITU-T G.680 because once Sakamoto supplies per-span DGD/PMD values for the same wavelength, a network controller must combine the section contributions to evaluate end-to-end polarization impairment. ITU-T G.680 is expressly directed to the impact of cascaded optical network elements on line-system PMD and provides a standardized root-sum-square combination framework. Using that standardized calculation on the per-section measurements would have yielded, for each measured wavelength, the wavelength-specific polarization-characteristic value of the optical path. This is the predictable use of a known PMD-combination rule for its established purpose.
Accordingly, claim 1 would have been obvious.
Claims 2, 3 and 7 are rejected under 35 U.S.C. § 103 as being unpatentable over Sakamoto et al. in view of Chen, further in view of ITU-T G.680 and Irie (US20190379461A1).
Claim 2
With respect to claim 2, claim 2 incorporates every limitation of claim 1, which is taught by Sakamoto, Chen and ITU-T G.680 for the reasons set forth above, except wherein claim 2 further requires the processor to calculate a polarization characteristic average value that is an average of the wavelength-specific polarization characteristic values, based on a total sum of those values and the number of wavelengths.
However, within analogous art, Irie states: “The PMD value acquiring unit 702 acquires the PMD value of each wavelength and registers the PMD value in the PMD value DB 801.” [Irie, ¶ [0086]; FIG. 6].
Irie states: “With reference to FIG. 4 again, the maximum value calculating unit 703 calculates the mean value of the PMD values of the respective wavelengths from the PMD value DB 801. The mean value of the PMD values of the respective wavelengths is substantially equal to the temporal mean value of the PMD values.” [Irie, ¶ [0088]; FIGS. 4 and 6].
Irie therefore expressly teaches the added limitation of claim 2: individual PMD values are acquired for respective wavelengths and a mean/average of those wavelength values is calculated. For a finite set of wavelength-specific values, calculation of a mean is mathematically the total sum divided by the number of values, which is the ordinary definition of an arithmetic average.
One of ordinary skill in the art would have been motivated to add Irie’s mean-value calculation to the Sakamoto/Chen/ITU-T G.680 system because Sakamoto already measures DGD values over all wavelengths, while Irie explains how those per-wavelength PMD values are reduced to a representative mean for network-quality estimation.
The modification requires only routine arithmetic on measurements already present in the controller, reduces a large set of wavelength-specific measurements to a compact network characteristic, and enables the subsequent statistical worst-case estimation taught by Irie and ITU-T G.680. The expected result is exactly predictable: the controller obtains the arithmetic mean of the measured wavelength-specific PMD values.
Accordingly, claim 2 would have been obvious.
Claim 3
With respect to claim 3, all limitations of claim 2 are taught by Sakamoto, Chen, ITU-T G.680 and Irie for the reasons stated above, except wherein claim 3 further requires estimating a limit value of the polarization characteristic value of the optical path as a constant multiple of the polarization characteristic average value, based on a Maxwell distribution in which an occurrence probability of the limit value is fixed.
However, within analogous art, Irie states: “The maximum value calculating unit 703 multiplies the mean value of the PMD values of the respective wavelengths by a prescribed ratio, to thereby calculate the maximum value of the PMD value that is temporally varied. The ratio of the maximum value to the mean value of the PMD values is described in Table 9-2 of ITU-T Recommendation G.680, for example.” [Irie, ¶ [0089]; FIG. 7].
Irie states: ““Ratio of max. to mean” corresponds to the ratio of the maximum value to the mean value of the PMD values. “Probability of exceeding max.” corresponds to temporal probability with which the PMD value exceeds the maximum value.” [Irie, ¶ [0090]; FIG. 7].
Irie states: “Thus, in this case, 3.2 that is a value in “Ratio of max. to mean” corresponding to 9.2×10−6 in “Probability of exceeding max.” is used as the above-mentioned ratio. The maximum value calculating unit 703 multiplies the mean value of the PMD values by 3.2 to calculate the maximum value of the PMD value that is temporally varied.” [Irie, ¶ [0092]; FIG. 7].
ITU-T G.680 states: “This equation assumes that the statistics of the instantaneous DGD are approximated by a Maxwell distribution, with the probability of the instantaneous DGD exceeding DGDmaxlink being controlled by the value of the Maxwell adjustment factor taken from Table 9-2.” [ITU-T G.680, § 9.3.1, p. 22, immediately following Eq. (9-6)].
Table 9-2 of ITU-T G.680 expressly lists “Ratio of max. to mean (S)” against “Probability of exceeding max.”; for example, S=3 corresponds to 4.2×10−5, S=3.2 corresponds to 9.2×10−6, and S=4 corresponds to 7.4×10−9. [ITU-T G.680, p. 23, Table 9-2].
The motivation to use Irie and ITU-T G.680 is direct and technical rather than hindsight reconstruction.
Once the controller of claim 2 has an average PMD value, network engineering requires a design/worst-case PMD value corresponding to an acceptably small outage probability. Irie expressly solves that problem by selecting a prescribed maximum-to-mean ratio from ITU-T G.680 and multiplying the measured mean by that constant. ITU-T G.680 expressly ties the constant to a Maxwell distribution and a probability of exceeding the maximum. Incorporating this known standardized calculation into the combined system would therefore have been the routine and predictable way to turn the measured average into a statistically meaningful limit/worst value for path design.
Accordingly, claim 3 would have been obvious.
Claim 7
With respect to claim 7, all limitations of claim 3 are taught by Sakamoto, Chen, ITU-T G.680 and Irie, except wherein claim 7 further requires selecting a signal type of signal light that uses the plurality of wavelengths based on the estimated limit value.
However, within analogous art, Irie states: “The device controlling unit 400 executes, in cooperation with the device controlling unit 300 of the transmitter 1, the series of control processing processes for selecting an appropriate multi-level modulation scheme.” [Irie, ¶ [0062]; FIGS. 2-4].
Irie states: “The BER acquiring unit 704 acquires the BER of the polarization-multiplexed optical signal S in each multi-level modulation scheme. The BER is an example of an index value of the transmission quality of the polarization-multiplexed optical signal S.” [Irie, ¶ [0094]].
Irie states: “For example, the modulation mode selecting unit 705 refers to the BER-DB 802 to acquire the BER in each modulation mode. The BER includes a PMD penalty, but the penalty in question is smaller than a penalty (hereinafter referred to as ‘maximum penalty’) depending on the maximum value of the PMD value that is generated with temporal probability. The modulation mode selecting unit 705 thus calculates the maximum penalty from the maximum value of the PMD value based on the database measured in advance, for example, and corrects the BER in each modulation mode with the maximum penalty.” [Irie, ¶ [0100]; FIG. 8].
A person of ordinary skill would have been motivated to select the transmitted signal type/modulation mode based on the statistically estimated maximum PMD because PMD tolerance depends on modulation format and baud rate. Irie expressly uses the calculated maximum PMD to determine the PMD penalty and to select the appropriate multi-level modulation scheme.
Applying that teaching to the limit value already calculated under claim 3 would have predictably selected a signal type whose transmission-quality margin remains acceptable under the estimated worst polarization condition. This is a direct use of Irie’s stated purpose and would have been obvious.
Accordingly, claim 7 would have been obvious.
Claim 4 is rejected under 35 U.S.C. § 103 as being unpatentable over Sakamoto et al. in view of Chen and ITU-T G.680, further in view of Tanaka et al. (US20230076671A1), Akasaka et al. (US20090214202A1), and Hara (US20200099462A1).
Claim 4
With respect to claim 4, all limitations of claim 1 are taught by Sakamoto, Chen and ITU-T G.680 for the reasons stated above, except wherein claim 4 additionally requires the processor to count a number of second/out-of-service sections in the optical path for each wavelength and specify a part of the plurality of wavelengths in ascending order of that number until matching a threshold bandwidth, with first polarization characteristic values acquired according to that selected part of the wavelengths.
For purposes of this prior-art rejection only, and without withdrawing the rejection of claim 4 under 35 U.S.C. § 112(b), the phrase 'until matching a threshold bandwidth' is interpreted consistently with the originally filed description at paragraphs [0093]-[0096] as continuing the ranked wavelength selection until the selected measurement bandwidth reaches or exceeds the predetermined threshold bandwidth. If applicant intends exact numerical equality, a different definition of the selected bandwidth, or another endpoint, the § 112(b) rejection remains applicable.
Sakamoto already supplies the underlying per-wavelength operation-state data and PMD acquisition. As quoted above, during system operation each node sends operating-wavelength information to the NMS, the NMS acquires operating-wavelength information, and the measurement process sweeps wavelengths other than the operating wavelengths. [Sakamoto, ¶¶ [0069]-[0070]].
Once the controller possesses operation-state information on a span-by-span/wavelength-by-wavelength basis, the number of non-operating sections for each wavelength is a directly countable property of the stored state map.
Tanaka states: “In the “cost” field, values indicating the costs of the paths corresponding to the pieces of path identification information are written. Here, a cost is, for example, a value represented as the number of relay node devices 61 to 64 on a path from a start node device 61 to 64 to an end node device 61 to 64.” [Tanaka, ¶ [0061]; FIG. 6].
Tanaka states: “For example, it is assumed that, in step S21, the request receiving unit 203 detects pieces of resource data in ascending order of the value of the “cost” field of the resource table 161.” [Tanaka, ¶ [0119]; FIGS. 9-11].
Tanaka does not itself count out-of-service sections per wavelength. It does, however, expressly teach the pertinent controller technique of reducing an optical-path configuration to a numerical count-based cost and processing resource records in ascending order of that cost. In the combined system, Sakamoto supplies the actual operating/non-operating span map, while Tanaka supplies the known ascending-order selection mechanism for a count-derived network cost.
Applying that known metric-selection technique to Sakamoto’s stored count of non-operating sections would select wavelengths requiring the fewest out-of-service test sections first.
Akasaka states: “Available wavelengths of the possible paths are determined at step 418. The differential group delay for each available wavelength of the possible paths are determined at step 422. The wavelengths are sorted according to differential group delay at step 426.” [Akasaka, ¶ [0041]; FIG. 4].
Akasaka states: “One or more criteria for selecting a path are taken into account at step 430. Criteria may include, for example, maximum tolerated chromatic dispersion, filter bandwidth, maximum tolerated ASE accumulation, maximum tolerated interference with other channels, or any other appropriate criterion.” [Akasaka, ¶ [0042]; FIG. 4].
Hara states: “The wavelength bands of the test transponders 23, 33 are arbitrarily set, and the wavelength interval between those and the wavelength bands of the additional transponders 12, 42 are changed to evaluate the influence of mutual interference.” [Hara, ¶ [0038]; FIGS. 6-7].
Hara states: “FIG. 3 illustrates the configuration of the test control circuit 25 included in the transmitting-side optical wavelength multiplexing transmission apparatus 2. Input and output interface 254 is an interface for an operator to connect an external device and is used in order that the operator can control each section through the external device. The operator instructs wavelength tunable filter controller 251, through the external device, on the center wavelength and the wavelength band that the wavelength tunable filter 22 transmits, and instructs the test transponder controller 252 on the wavelength band of the test optical signal generated by the test transponder 23 and the wavelength interval between the test optical signal and the optical signal that the wavelength tunable filter 22 transmits. The wavelength tunable filter controller 251 sets, in accordance with the above-described instructions, the center wavelength and the wavelength band that the wavelength tunable filter 22 transmits. The test transponder controller 252 sets, in accordance with the above-described instructions, the wavelength band of the test optical signal generated by the test transponder 23 and the wavelength interval between the test optical signal and the optical signal that the wavelength tunable filter 22 transmits.” [Hara, ¶ [0033]; FIG. 3].
One of ordinary skill in the art would have been motivated to modify the Sakamoto/Chen measurement controller so that it first tests wavelengths needing the fewest out-of-service section activations. Sakamoto itself recognizes that non-operating resources can require a measurement signal and that measurements should avoid affecting live traffic.
Each additional out-of-service section that must be temporarily illuminated consumes transmitter/receiver resources and creates an additional configuration operation. Tanaka teaches that optical-network controllers routinely reduce such routing/configuration burden to a count-based “cost” and select candidate paths in ascending order of that count. Substituting the count of out-of-service sections as the cost metric would have been a straightforward application of Tanaka’s known resource-selection method to Sakamoto’s known state map.
A person of ordinary skill in the art would further have selected enough of the best-ranked wavelengths to provide the predetermined measurement bandwidth because Akasaka expressly sorts available wavelength candidates according to a measured optical characteristic and expressly recognizes filter bandwidth as a path-selection criterion, while Hara teaches that an optical test controller deliberately sets a test center wavelength and wavelength band. Once candidate wavelengths are already ranked by Sakamoto/Tanaka's count-based state metric, stopping the ranked selection when the required measurement bandwidth is reached is the predictable finite implementation of those teachings: it provides enough spectral coverage for a representative PMD estimate while avoiding unnecessary activation of additional out-of-service sections.
The expected result is reduced test time, reduced control load, and reduced disturbance risk with adequate wavelength-band coverage.
Accordingly, claim 4 would have been obvious.
Claim 5 is rejected under 35 U.S.C. § 103 as being unpatentable over Sakamoto et al. in view of Chen, ITU-T G.680 and Irie, further in view of Masuda et al. (US20210218476A1).
Claim 5
With respect to claim 5, all limitations of claim 2 are taught by Sakamoto, Chen, ITU-T G.680 and Irie for the reasons stated above, except wherein claim 5 further requires collecting a speed of a polarization fluctuation occurring in the first/in-service sections; identifying first sections in which a polarization fluctuation amount according to the fluctuation speed exceeds a threshold fluctuation amount and identifying a part of the wavelengths; then acquiring the polarization values and calculating the average based on the selected data.
Sakamoto states: “Furthermore, the NMS 130 monitors the DGD values (operation S610), and indexes the sites where DGD varies significantly (operation S611).” [Sakamoto, ¶ [0049]; FIG. 6].
Masuda states: “The SOP monitoring unit 48 (control unit) detects the SOP fluctuation speed of the digital signal input from the wavelength dispersion compensation unit 46 to the adaptive equalizer 47, based on an output from the coefficient updater 49. For example, the SOP monitoring unit 48 derives the value of a Stokes parameter indicating the state of polarization of the digital signal, based on the output from the coefficient updater 49. The SOP monitoring unit 48 periodically detects, based on the derived value of the Stokes parameter, the SOP fluctuation speed at a predetermined period. The SOP monitoring unit 48 periodically outputs information indicating the SOP fluctuation speed to the coefficient updater 49 at a predetermined period.” [Masuda, ¶ [0035]; FIGS. 1-3].
Masuda states: “a control unit configured to detect a fluctuation speed of a state of polarization of the digital signal based on the second tap coefficient, determine whether or not the fluctuation speed is higher than or equal to a speed threshold, and change the first tap coefficient to the updated second tap coefficient if it is determined that the fluctuation speed is higher than or equal to the speed threshold.” [Masuda, ¶ [0008]; Abstract].
The combination is technically natural. Sakamoto already monitors temporal DGD variation and identifies the sites at which DGD varies significantly.
Masuda provides an expressly quantified polarization-dynamics metric SOP fluctuation speed and teaches comparing that speed to a threshold.
A person of ordinary skill in the art seeking to improve the reliability of Sakamoto's statistical PMD estimate would have been motivated to use Masuda's periodically detected SOP fluctuation speed as the objective time-resolved metric for Sakamoto's identification of sites where DGD varies significantly. Because Masuda produces repeated speed measurements at predetermined periods, reducing those repeated values to an accumulated or average fluctuation amount over a selected observation interval and comparing that amount with a threshold would have been a routine signal-monitoring operation used to reject momentary excursions and identify persistently dynamic sections. The resulting section/channel selection uses the very polarization-dynamics information that Sakamoto already monitors and focuses PMD acquisition on the portions of the network most likely to control the statistical worst case.
The modification therefore does not require a new sensing principle: Sakamoto supplies the network-level DGD-variation monitoring and selection purpose, while Masuda supplies periodic polarization-fluctuation-speed measurements and a threshold comparison. Aggregating periodic speed samples into a section-level fluctuation amount before making the selection is a predictable implementation of those known monitoring functions, with the expected result of targeted PMD sampling and improved statistical relevance.
Accordingly, claim 5 would have been obvious.
Claim 6 is rejected under 35 U.S.C. § 103 as being unpatentable over Sakamoto et al. in view of Chen, ITU-T G.680 and Irie, further in view of Mason et al. (US20220123844A1) and Frank J. Massey, Jr., “The Kolmogorov-Smirnov Test for Goodness of Fit,” (1951).
Claim 6
With respect to claim 6, all limitations of claim 3 are taught by Sakamoto, Chen, ITU-T G.680 and Irie for the reasons stated above, except wherein claim 6 additionally requires determining whether a set of first polarization characteristic values is in line with a cumulative distribution function of the Maxwell distribution based on a goodness-of-fit test and, when the set is not in line with the cumulative distribution function, acquiring first polarization characteristic values until the goodness-of-fit test is met.
Mason states: “In some embodiments, the step of sorting the magnitudes comprises normalising the magnitudes. This allows statistical analysis of the samples to be performed. In even more preferred embodiments the step of fitting a plurality of known distributions comprises applying a hypothesis test. Fitting a known distribution to the statistical distribution of samples will always have an uncertainty as a result of operating on a subset of the ‘real world’ received signal. Indeed a number of different known distributions may in fact provide a substantially equal ‘good’ fit to the samples themselves. Hypothesis testing allows a null hypothesis (for instance that the received signal magnitude exhibits a Rayleigh distribution for an assigned confidence interval) to have a measure of similarity such as a probability assigned to it, such that a null hypothesis with an optimum (maximal) probability of being correct can be determined.” [Mason, ¶ [0011]; FIGS. 1, 3].
Mason states: “Even more preferred is that the hypothesis tests comprise Kolmogorov Smirnov, Anderson Darling, Chi Squared and Lilliefors tests.” [Mason, ¶ [0012]].
Massey states: “The test is based on the maximum difference between an empirical and a hypothetical cumulative distribution.” [Massey, p. 68, article summary].
Massey states: “If F0(x) is the population cumulative distribution, and SN(x) the observed cumulative step-function of a sample (i.e., SN(x) = k/N, where k is the number of observations less than or equal to x), then the sampling distribution of d = maximum |F0(x) - SN(x)| is known, and is independent of F0(x) if F0(x) is continuous.” [Massey, p. 69, § 2, 'The Test'].
Irie and ITU-T G.680 supply the claimed Maxwell-distribution model for PMD, while Mason and Massey supply the known goodness-of-fit/K-S machinery for deciding whether an empirical sample follows a specified theoretical cumulative distribution.
A POSITA would have been motivated to apply a K-S goodness-of-fit check before relying on the Maxwell-based worst-value calculation because the accuracy of a statistical tail estimate depends on whether the measured sample adequately represents the assumed distribution. Irie and ITU-T G.680 expressly use a Maxwell model to convert a measured mean PMD into a maximum/limit value.
Mason teaches that finite real-world samples may not fit the assumed distribution and that hypothesis testing, including the Kolmogorov-Smirnov test, is used to assess the fit.
Massey provides the standard empirical-CDF-versus-theoretical-CDF comparison and critical-value framework. Mason explains why a finite sample can produce uncertainty in distribution fitting and expressly identifies the K-S test as an available hypothesis test. If the empirical PMD sample does not satisfy the selected fit criterion, obtaining additional PMD observations and rerunning the same K-S test would have been the ordinary iterative sampling response, because the controller cannot rationally rely on the Maxwell-based tail estimate until the measured sample adequately represents the assumed Maxwell distribution. The modification uses the same sensor and the same statistical test repeatedly and predictably increases confidence in the distributional estimate.
Accordingly, claim 6 would have been obvious.
Claim 8 is rejected under 35 U.S.C. § 103 as being unpatentable over Sakamoto et al. in view of Bottari et al. (US20120321297A1), further in view of Oda et al. (US20180097562A1), Irie and ITU-T G.680.
Claim 8
Claim 8 is an independent claim. It requires a device estimating a polarization characteristic of an optical path in which in-service first sections and out-of-service second sections are mixed; acquiring first polarization-characteristic values for each wavelength in first sections based on operation-state information; calculating a first average from first values common to the first sections; calculating a second average for a combined section formed by adjacent first sections; and, when no second section is adjacent to that combined section in the transmission direction, estimating a limit value as a constant multiple of the second average according to a Maxwell distribution with a fixed occurrence probability.
For purposes of this prior-art rejection only, and without withdrawing the rejection of claim 8 under 35 U.S.C. § 112(b), the disputed phrase 'the first polarization characteristic average values of the combined section' is interpreted as the previously determined average/section values of the constituent in-service sections that are used in calculating the combined-section average. The condition concerning 'none of the second sections adjacent' is interpreted, consistently with the originally filed description at paragraphs [0103]-[0106], as the condition in which no out-of-service section remains downstream of the completed in-service combined section. The § 112(b) rejection is maintained because the claim itself does not state those relationships with reasonable certainty.
Sakamoto teaches the network, memory/controller, operation-state information, per-wavelength/per-span PMD acquisition, and mean-PMD calculation for operating optical networks as set forth above. In particular, Sakamoto teaches that the NMS receives operating-wavelength information from each node, measures per-span DGD values, computes mean PMD values, and monitors/controls routes. [Sakamoto, ¶¶ [0034], [0049]-[0051], [0068]-[0070]].
Bottari states: “Advantageously, the step of determining a quality of transmission along the candidate optical path determines at least one parameter indicative of quality of transmission for a composite path comprising multiple optical sections by operating on the retrieved parameters for optical sections in the composite path.” [Bottari, ¶ [0011]; FIG. 4].
Bottari states: “A lightpath for carrying traffic is established between a pair of LERs/ROADMs 12. As an example, a lightpath can be set up between node 40 and node 43 via node 42. The lightpath comprises an optical section 30 between nodes 40 and 42 and an optical section 35 between nodes 42 and 43. Optical section 31 includes an optical amplifier 41. At node 42 traffic may remain on the same wavelength, or it may be switched between wavelengths, so that the lightpath uses a first wavelength on optical section 30 and a second wavelength on optical section 35.” [Bottari, ¶ [0028]; FIG. 1].
Bottari states: “FIG. 1 also shows entities used in the planning and routing of lightpaths. A Photonic Link Design Engine (PLDE) 50 calculates parameters for interfaces of each optical section 30-39 of the network 10. The interface can be defined in terms of one or more of a bit rate, line coding type and modulation type. A set of parameters is calculated for interfaces supported by an optical section 30-39. The set of parameters for an interface of an optical section are indicative of transmission quality along the optical section, taking into account the traffic type (bit rate, modulation, line coding) and the impairments of the optical section.” [Bottari, ¶ [0029]].
Bottari states: “FIG. 3 schematically shows operation of the PLDE 50. The PLDE stores detailed data about optical sections, including the types of fibres, transponder/muxponder parameters, amplifier parameters. When the PLDE is invoked, it emulates the behaviour of light across the fibre and across the amplifiers/nodes of an optical section. Each optical impairment is considered and evaluated as a penalty to be addressed to the OSNR, or on Q factor. The evaluation of an optical section includes the transmitter (i.e. transmitting transponder/muxponder), receiver (i.e. receiving transponder/muxponder), and all fibre spans between the transmitter and receiver.” [Bottari, ¶ [0033]; FIG. 3].
Bottari’s Tables 2-3 expressly include a polarization mode dispersion (PMD) penalty among the per-section quality parameters. [Bottari, ¶¶ [0034]-[0035]].
Oda states: “The fifth arithmetic unit 42B calculates a PDL of each span in a wavelength path based on the receiving terminal PDL 63B of the wavelength path according to the following equations (17) and (18), and sequentially stores the PDL of each span in the wavelength path for the path identification information of the wavelength path in the first information storage unit 60B. The receiving terminal PDL is a value approximate to an averaged PDL mean obtained by statistical addition.” [Oda, ¶ [0163]; FIG. 35; Eqs. (17)-(18)].
Oda further states: “although it has been illustrated in the fifth embodiment that a receiving terminal PDL of a wavelength path is used to estimate a receiving terminal of a wavelength path of an estimation target, a polarization mode dispersion (PMD) may be used.” [Oda, ¶ [0182]; FIG. 36].
Oda therefore expressly confirms, in the same optical-network-controller art, that polarization impairments associated with multiple spans/wavelength paths may be statistically combined and that the disclosed span-combination framework is applicable to PMD as well as PDL. Bottari supplies the composite-path/adjacent-section construction, while Oda and ITU-T G.680 supply physically recognized statistical accumulation of polarization impairment rather than an arbitrary mathematical combination.
Thus, Bottari expressly teaches building a combined/composite adjacent-section path by mathematically operating on the individual section impairment parameters.
ITU-T G.680 states: “The PMD of an optical fibre cable is specified according to a statistical format that can be combined with the other elements of the optical link to determine a maximum DGD that is defined as a probability limit.” [ITU-T G.680, § 9.3.1, p. 22].
ITU-T G.680 Equation (9-6) provides a root-sum-square combination of cascaded PMD contributions and Table 9-2 provides the Maxwell adjustment factor/probability relation. [ITU-T G.680, pp. 22-23, Eq. (9-6), Table 9-2].
Irie independently teaches calculating the mean of PMD values and multiplying that mean by the Table 9-2 constant to obtain the temporally varying maximum. [Irie, ¶¶ [0088]-[0093]].
A person of ordinary skill in the art would have been motivated to combine Sakamoto with Bottari and Oda because Sakamoto supplies measured per-span/per-wavelength PMD information and operation-state data, Bottari supplies a controller architecture that forms a composite path from multiple optical sections and operates on the constituent section parameters, and Oda expressly teaches statistical addition of polarization impairment on a span/path basis and expressly states that PMD may be used in that framework. ITU-T G.680 then supplies the standardized root-sum-square PMD accumulation law. Together, those teachings provide a direct engineering reason to compute section averages from common in-service measurements and then combine adjacent in-service sections using the known statistical accumulation rule, reducing repeated end-to-end measurements while preserving the physical PMD relationship.
When the constructed composite in-service section reaches the downstream direction and the operation-state map indicates that no out-of-service section remains, a person of ordinary skill would have had no reason to establish an additional dark test path; the available in-service section measurements already cover the remaining route. Conversely, where an out-of-service section remains, Sakamoto's non-operating-span measurement mechanism supplies the missing measurement. This conditional control follows directly from using Sakamoto's service-state map with Bottari's iterative composite-path construction. Irie and ITU-T G.680 then teach estimating the limit as a fixed multiple of the combined mean according to a selected Maxwell-tail probability. Under the stated prior-art interpretation, the combination accounts for each operative limitation of claim 8.
Claims 9, 13, 14 and 15 are rejected under 35 U.S.C. § 103 as being unpatentable over Robinson et al. (US20020122220A1) in view of Beacall et al. (US20220131613A1).
Claim 9
Claim 9 recites an optical transmission path characteristic estimation device that estimates a characteristic value that fluctuates with time according to a polarization characteristic of an end-to-end optical transmission path containing multiple nodes; a memory and processor; acquisition, from a reception node, of signal-quality indices after the signal propagates through the optical path; calculation of a quality-change amount for a certain period; and estimation of the characteristic value based on that quality-change amount.
Robinson states: “All of this BER data may be summarized into a “Q” factor or quality metric for the received signal. In general terms, the broader the range of timings over which a low BER can be sustained, the greater the Q factor of the signal. A receiver with an auxiliary decision circuit can measure and output such a Q factor.” [Robinson, ¶ [0015]; FIGS. 1-3].
Robinson states: “During the time that an auxiliary decision circuit is accumulating measurements to compile a Q factor for a received signal, a shift in dispersion characteristics, particularly PMD characteristics, can take place along the fiber. This can result in an inaccurate assessment of the signal quality, especially if a PMD compensator cannot quickly and sufficiently compensate for the PMD change. Therefore the Q factor cannot be solely relied upon as a measure of path quality.” [Robinson, ¶ [0018]].
Robinson states: “the System devices may comprise an optical receiver providing a Q factor as the indicator of an optical Signal passing through the communication System. This receiver may also provide an actual observed bit error rate (BER) of the optical signal as another indicator.” [Robinson, ¶ [0020]; Abstract].
Robinson thus directly teaches acquiring a reception-node signal-quality index (Q or BER) and teaches that temporal PMD changes manifest in the Q measurement. The controller can therefore use the observed signal-quality change to infer a polarization-related path characteristic.
Beacall states: “Referring to FIG. 1b, shown therein is a block diagram of an exemplary embodiment of the control system 88. The control system 88 is provided with a processor 92 and at least one non-transitory computer readable medium 94 coupled to the processor 92. The non-transitory computer readable medium 94 stores a link database 96, and a degradation prediction algorithm 98. The link database 96 is continuously (e.g., at intervals such as every 15 minutes) populated with performance data associated with the link 21, and each such population of the performance data is time stamped so that performance trends over time can be analyzed. The performance data may include one or more performance attribute. Exemplary performance attributes include Q-factor, Optical Signal to Noise ratio, repeater input (received light level (RLL), i.e., the light level in dBm into each repeater), output send light level (SLL), i.e., total output optical power of each repeater, data from a Wet Plant Line Monitoring (WPLM) unit, repeater gain changes and associated impact on timelines can also be derived. WPLM is a device that sends commands to the repeaters 30 and receives performance attributes from the repeaters 30. Further performance attributes include a repeater gain change, which may be used to compensate for inter span fiber degradation. Repeater gain change values may be -1, nominal and nominal +1. The repeater gain change may be changed manually and entered into the link database, or the degradation prediction algorithm may estimate the repeater gain change value by determining an increase in output power in relation to the repeater input power. Other performance attributes include per carrier OSNR, per carrier Q factor, all system interface TX and RX optical powers, power feed equipment (PFE) voltage and currents, repeater bias currents where applicable, repair indication and location of that repair. Age of any particular fiber optic cable may not be a requirement, but initial measured performance attributes of the fiber optic cable may be considered as start of life performance attributes.” [Beacall, ¶ [0076]; FIG. 1B].
Beacall states: “The processor 92 runs the degradation prediction algorithm 98 continuously and/or at intervals to determine the predicted level of degradation of one or more links or spans, such as the link 21 or the span 38, over time. The predicted level of degradation over time is then used to determine one or more instants of time (e.g., day) when the capacity of the link 21 or span 38 is projected to need to be reduced so as to avoid errors above a threshold occurring within the link 21.” [Beacall, ¶ [0077]].
A person of ordinary skill would have been motivated to combine Robinson and Beacall because Robinson identifies Q/BER at the optical receiver as an indicator that responds to PMD variation, while Beacall provides the mature time-series controller architecture for repeatedly acquiring, time-stamping, storing, and analyzing Q-factor performance over defined periods. In the combined system, the processor would obtain the receiver Q/BER at regular intervals, calculate the observed change over the selected analysis period, and use Robinson’s known PMD-to-Q relationship to estimate the polarization-related characteristic responsible for that change.
The use of a change amount rather than a single absolute Q value is predictable because it suppresses static offsets and emphasizes the time-varying impairment that the claim is concerned with.
Accordingly, claim 9 would have been obvious.
Claim 13
With respect to claim 13, all limitations of claim 9 are taught by Robinson and Beacall, except wherein claim 13 additionally requires acquiring, from a first relay node, a loss index representing signal-light power loss in the upstream span from a second relay node; calculating a new signal-quality index by excluding from the measured signal-quality index a signal-quality change amount calculated from that loss index for the certain period; and estimating the polarization-related characteristic from the new index.
Beacall states: “Referring to FIG. 1b, shown therein is a block diagram of an exemplary embodiment of the control system 88. The control system 88 is provided with a processor 92 and at least one non-transitory computer readable medium 94 coupled to the processor 92. The non-transitory computer readable medium 94 stores a link database 96, and a degradation prediction algorithm 98. The link database 96 is continuously (e.g., at intervals such as every 15 minutes) populated with performance data associated with the link 21, and each such population of the performance data is time stamped so that performance trends over time can be analyzed. The performance data may include one or more performance attribute. Exemplary performance attributes include Q-factor, Optical Signal to Noise ratio, repeater input (received light level (RLL), i.e., the light level in dBm into each repeater), output send light level (SLL), i.e., total output optical power of each repeater, data from a Wet Plant Line Monitoring (WPLM) unit, repeater gain changes and associated impact on timelines can also be derived. WPLM is a device that sends commands to the repeaters 30 and receives performance attributes from the repeaters 30. Further performance attributes include a repeater gain change, which may be used to compensate for inter span fiber degradation. Repeater gain change values may be -1, nominal and nominal +1. The repeater gain change may be changed manually and entered into the link database, or the degradation prediction algorithm may estimate the repeater gain change value by determining an increase in output power in relation to the repeater input power. Other performance attributes include per carrier OSNR, per carrier Q factor, all system interface TX and RX optical powers, power feed equipment (PFE) voltage and currents, repeater bias currents where applicable, repair indication and location of that repair. Age of any particular fiber optic cable may not be a requirement, but initial measured performance attributes of the fiber optic cable may be considered as start of life performance attributes.” [Beacall, ¶ [0076]; FIG. 1B].
Beacall states: “Repeater span losses are calculated by taking the optical power OUT of a repeater 30 (SLL) and the receive power in (RLL) for a downstream receiver, and then calculating the difference. Using span loss calculations and changes per span with corresponding changes in Q can be correlated over time to see where span degradation happens most and highlighting spans that have the most detrimental impact.” [Beacall, ¶ [0154]; FIG. 23].
Thus, Beacall expressly teaches the claimed loss index: a span-loss value for the section from an upstream repeater to a downstream repeater is calculated from upstream output power and downstream received power. Beacall also expressly correlates the change in that span loss to the corresponding change in Q over time.
Robinson teaches that Q change can reflect PMD/polarization behavior but can also be degraded by other causes. Beacall identifies one such non-polarization cause span loss and provides both the per-span loss index and the Q impact associated with changes in that index.
A person of ordinary skill in the art seeking the polarization-specific characteristic would have been motivated to remove the Q contribution attributable to span-loss variation before using the remaining Q variation as a proxy for PMD/PDL. Robinson expressly warns that Q cannot be relied upon in isolation when PMD changes during the measurement, and Beacall expressly calculates span loss, correlates changes in span loss with corresponding changes in Q, and states that the impact of a span-loss increase on Q can be calculated. Once that non-polarization Q contribution is known, excluding it from the measured quality change is the conventional decomposition of a measured response into known and residual contributions. The predictable result is a corrected Q index with improved specificity for the remaining time-varying polarization impairment.
Accordingly, claim 13 would have been obvious.
Claim 14
With respect to claim 14, all limitations of claim 9 are taught by Robinson and Beacall, except wherein claim 14 further requires acquiring from the reception node a power index representing the input power of signal light to the reception node, calculating a new signal-quality index by excluding a signal-quality change amount calculated from that power index for the certain period, and estimating the characteristic based on the new signal-quality index.
Beacall states: “Referring to FIG. 1b, shown therein is a block diagram of an exemplary embodiment of the control system 88. The control system 88 is provided with a processor 92 and at least one non-transitory computer readable medium 94 coupled to the processor 92. The non-transitory computer readable medium 94 stores a link database 96, and a degradation prediction algorithm 98. The link database 96 is continuously (e.g., at intervals such as every 15 minutes) populated with performance data associated with the link 21, and each such population of the performance data is time stamped so that performance trends over time can be analyzed. The performance data may include one or more performance attribute. Exemplary performance attributes include Q-factor, Optical Signal to Noise ratio, repeater input (received light level (RLL), i.e., the light level in dBm into each repeater), output send light level (SLL), i.e., total output optical power of each repeater, data from a Wet Plant Line Monitoring (WPLM) unit, repeater gain changes and associated impact on timelines can also be derived. WPLM is a device that sends commands to the repeaters 30 and receives performance attributes from the repeaters 30. Further performance attributes include a repeater gain change, which may be used to compensate for inter span fiber degradation. Repeater gain change values may be -1, nominal and nominal +1. The repeater gain change may be changed manually and entered into the link database, or the degradation prediction algorithm may estimate the repeater gain change value by determining an increase in output power in relation to the repeater input power. Other performance attributes include per carrier OSNR, per carrier Q factor, all system interface TX and RX optical powers, power feed equipment (PFE) voltage and currents, repeater bias currents where applicable, repair indication and location of that repair. Age of any particular fiber optic cable may not be a requirement, but initial measured performance attributes of the fiber optic cable may be considered as start of life performance attributes.” [Beacall, ¶ [0076]; FIG. 1B].
Beacall states: “As Q is correlated to receive OSNR, the degradation prediction algorithm 98 may also correlate the Q to carrier receive OSNR. These OSNR values can be taken either directly from a line card or through an Optical Power Measurement (OPM) of the individual Wavelength Selector Switch (WSS). The degradation prediction algorithm 98 would not only correlate Q versus receive OSNR over time alongside any external factors previously mentioned but can be used for automated deployment of systems using software tools to configure nodes, such as the transmitter blocks 12-1-12-n, or receiver blocks 22-1-22-n.” [Beacall, ¶ [0155]].
The receiver input optical power is a directly measured operating variable that affects receiver OSNR and therefore Q independently of PMD. Beacall time-stamps both Q and RX optical power and expressly correlates Q with receive OSNR/external factors over time. A POSITA trying to infer a polarization-specific degradation from Q would therefore remove the part of the Q change attributable to receiver-input-power variation, rather than misattribute that non-polarization change to PMD/PDL.
Computing the power-induced quality change from the known receiver characteristic and subtracting/excluding it from the measured index is a routine calibration/normalization step and would yield the predictable corrected signal-quality index required by claim 14.
Accordingly, claim 14 would have been obvious.
Claim 15
With respect to claim 15, all limitations of claim 9 are taught by Robinson and Beacall, except wherein claim 15 further requires acquiring the relay-span loss index and the reception-node input-power index, calculating the respective signal-quality change amounts for the certain period, excluding both contributions from the measured signal-quality indices, and estimating the polarization-related characteristic using the resulting new signal-quality index.
Beacall states: “The degradation prediction algorithm 98 may also determine inter repeater 30 span loss changes and correlate the inter repeater span loss changes to Q changes across the communication system 10 thereby estimating performance impact per repair and producing a more accurate decision on whether or not to change the modulation format. For example, FIG. 23 shows the degradation rolloff prior to a repair, as well as correlated degradation and adjusted degradation time before next modulation format change. Repeater span losses are calculated by taking the optical power OUT of a repeater 30 (SLL) and the receive power in (RLL) for a downstream receiver, and then calculating the difference. Using span loss calculations and changes per span with corresponding changes in Q can be correlated over time to see where span degradation happens most and highlighting spans that have the most detrimental impact. In other words, the receiver OSNR depends on the span loss as well as other parameters, such as repeater output power and the like. An increase in the span loss will reduce the receiver OSNR. Because Q is related to receiver OSNR, the impact of a span loss increase on Q can be calculated.” [Beacall, ¶ [0154]; FIG. 23].
Beacall states: “Referring to FIG. 1b, shown therein is a block diagram of an exemplary embodiment of the control system 88. The control system 88 is provided with a processor 92 and at least one non-transitory computer readable medium 94 coupled to the processor 92. The non-transitory computer readable medium 94 stores a link database 96, and a degradation prediction algorithm 98. The link database 96 is continuously (e.g., at intervals such as every 15 minutes) populated with performance data associated with the link 21, and each such population of the performance data is time stamped so that performance trends over time can be analyzed. The performance data may include one or more performance attribute. Exemplary performance attributes include Q-factor, Optical Signal to Noise ratio, repeater input (received light level (RLL), i.e., the light level in dBm into each repeater), output send light level (SLL), i.e., total output optical power of each repeater, data from a Wet Plant Line Monitoring (WPLM) unit, repeater gain changes and associated impact on timelines can also be derived. WPLM is a device that sends commands to the repeaters 30 and receives performance attributes from the repeaters 30. Further performance attributes include a repeater gain change, which may be used to compensate for inter span fiber degradation. Repeater gain change values may be -1, nominal and nominal +1. The repeater gain change may be changed manually and entered into the link database, or the degradation prediction algorithm may estimate the repeater gain change value by determining an increase in output power in relation to the repeater input power. Other performance attributes include per carrier OSNR, per carrier Q factor, all system interface TX and RX optical powers, power feed equipment (PFE) voltage and currents, repeater bias currents where applicable, repair indication and location of that repair. Age of any particular fiber optic cable may not be a requirement, but initial measured performance attributes of the fiber optic cable may be considered as start of life performance attributes.” [Beacall, ¶ [0076]; FIG. 1B].
Beacall therefore acquires and time-correlates all of the variables recited in claim 15 in the same monitoring architecture: signal quality, span loss components, and receiver/transceiver optical powers. Robinson supplies the reason for isolating the polarization-related portion of the remaining Q variation.
Once it is known to correct a quality metric for the effect of span loss and known to correct for the effect of receiver input power, applying both corrections together is the predictable superposition of two known calibration steps.
A person of ordinary skill in the art would have combined both corrections because leaving either known power-related contribution in the time-series Q data can falsely inflate or suppress the inferred polarization penalty. Beacall expressly analyzes multiple synchronized performance attributes together, including Q, RX/TX optical powers, and span-loss components, and expressly calculates the Q impact of span-loss change. Applying the two known corrections together is the predictable superposition of the same calibration principle and leaves a residual quality index more representative of the time-varying polarization
impairment described by Robinson. No new optical hardware is required; the controller already stores the synchronized quantities needed for the calculation.
Accordingly, claim 15 would have been obvious.
Claim 10 is rejected under 35 U.S.C. § 103 as being unpatentable over Robinson et al. in view of Beacall et al., further in view of Lianshan Yan et al., “Polarization-Mode-Dispersion Emulator Using Variable Differential-Group-Delay (DGD) Elements and Its Use for Experimental Importance Sampling,” (2004).
Claim 10
With respect to claim 10, all limitations of claim 9 are taught by Robinson and Beacall as set forth above, except wherein claim 10 additionally requires calculating the quality-change amount based on an average value of the signal-quality indices and a Maxwell distribution.
Yan states: “The DGD follows a Maxwellian distribution that falls off to low probabilities at times the average value and extends out to infinity. It is the occasional events in the tail of the distribution that are likely to cause system outages.” [Yan, p. 1051, Introduction].
Yan states: “This technique is used to measure the Q-factor degradation due to both average and rare PMD values in a 10-Gb/s transmission system.” [Yan, p. 1051, Abstract].
Yan states: “We demonstrate a practical polarization-mode-dispersion (PMD) emulator using programmable differential-group-delay (DGD) elements. The output PMD statistics of the emulator can be chosen by varying the average of the Maxwellian DGD distribution applied to each element. The emulator exhibits good stability and repeatability in a laboratory
environment. In addition, we demonstrate how this emulator may be used to experimentally employ the powerful technique of importance sampling to quickly generate extremely low probability events. This technique is used to measure the Q-factor degradation due to both average and rare PMD values in a 10-Gb/s transmission system.” [Yan, p. 1051, Abstract].
Yan thereby expressly links the average and tail of a Maxwellian PMD/DGD distribution to measured Q-factor degradation. Robinson supplies the receiver Q metric, and Beacall supplies repeated Q samples and trend analysis over a defined time period.
One of ordinary skill in the art would have been motivated to characterize the time-varying Q data using the known Maxwellian PMD statistics because Robinson establishes that Q changes with temporal PMD behavior, Beacall supplies repeated time-stamped Q samples and trend analysis, and Yan experimentally demonstrates Q-factor degradation caused by both average and rare states of a Maxwellian DGD/PMD distribution. Computing a representative average from the accumulated Q samples and using the Maxwell-tail relation to derive the polarization-related quality-change amount is therefore not an arbitrary statistical substitution; it applies the known PMD probability model to the receiver-quality metric that the art already identifies as responding to PMD. The expected result is a statistically defined quality-change amount that captures ordinary and rare polarization states. Accordingly, claim 10 would have been obvious.
Claims 11 and 12 are rejected under 35 U.S.C. § 103 as being unpatentable over Robinson et al. in view of Beacall et al., further in view of Frankel et al. (US20060139742A1) and Oda et al.
Claim 11
With respect to claim 11, all limitations of claim 9 are taught by Robinson and Beacall as set forth above, except wherein claim 11 additionally requires that, when the processor detects an operation-state change including an increase or decrease in the number of wavelengths in the optical communication service, the processor discards signal-quality indices already acquired and re-acquires the indices.
Frankel’742 states: “if OSC power remains substantially constant but the signal wavelength power changes, then a controller of the optical amplifier can determine the change is due to a wavelength count change.” [Frankel’742, ¶ [0035]; FIGS. 3-4B].
Frankel’742 states: “A single fiber strand can carry many independent multiple optical signals (e.g., >100), each signal being differentiated by a slightly different wavelength (e.g., 0.4 nm separation). Accordingly, optical amplifiers amplify all the wavelengths simultaneously. As is known in the art, it is common for the optical amplifiers to be operated in a saturated mode having a fixed total optical power output, but variable gain. Optical wavelength signals can appear and disappear in the fiber-optic link, either due to component failures and/or fiber cuts in the fixed OADM case, or due to active wavelength switching in the dynamic OADM case. As optical wavelength signals disappear, optical amplifiers operating in a constant power mode allocate the unused power to the remaining signals potentially causing a substantial increase in their power. Conversely, newly added optical wavelengths can cause substantial power drop in the already existing ones.” [Frankel’742, ¶¶ [0005], [0007]].
Oda states: “In the transmission system 1, when a signal is communicated to a wavelength path of an estimation target, a path BER of a different wavelength path adjacent to the wavelength path of the estimation target is changed. Therefore, after communicating of the optical signal to the wavelength path λ3 of the estimation target, the estimation device 4A may measure path BERs of different wavelength paths λ1, λ2, and λ4 and store the measured path BERs of different wavelength paths λ1, λ2, and λ4 in the information storage unit 30.” [Oda, ¶ [0122]; FIG. 20].
Oda therefore expressly recognizes that changing the active wavelength population can change the measured quality of existing wavelength paths and teaches obtaining a fresh set of quality measurements after the new wavelength is communicated. This directly reinforces the reason not to mix quality samples from different wavelength-count regimes.
Beacall states: “In reality any repair takes time. Consequently, any repair will likely result in either a single or multiple carriers being out of frame with no usable performance data when the repair is made. Performance attributes logged into the link database 96 for a component that is being repaired, would therefore in effect skew the results of the degradation prediction algorithm 98 thereby reducing the time to modulation change. Therefore any carriers that become Loss Of Frame (LOF) either side of a network event are disregarded for analysis during that LOF time span. Conversely any carriers that are either removed or added as part of an upgrade process are logged into the link database 96. FIG. 22 shows an exemplary Q effect of a cable repair, i.e., the Q goes to zero. To avoid skewing the results of the degradation prediction algorithm, such data logged during a repair is either removed from the link database 96 or ignored. The degradation prediction algorithm 98 can be notified of a repair by an operator using the graphical user interface. Or, the degradation prediction algorithm 98 can determine that the link 21 is being repaired when an out of frame event, or an optical loss of signal event is detected.” [Beacall, ¶ [0152]; FIGS. 20-22].
Beacall’s database is continuously repopulated at defined intervals with fresh performance attributes, including Q factor. [Beacall, p. 8, ¶ [0076]].
Accordingly, after removal/ignoring of invalid pre-event/event data, fresh quality indices are acquired as the post-event state is monitored.
A person of ordinary skill in the art would have been motivated to combine Frankel's explicit wavelength-count-change detector with Beacall's event-aware performance database and Oda's post-change remeasurement because a change in the number of WDM carriers changes amplifier loading and can change the measured BER/Q of existing wavelength paths. Using stale pre-change Q/BER samples in a post-change statistical distribution would mix measurements from materially different operating regimes. Beacall expressly removes or ignores event-corrupted performance data and continuously repopulates its database with fresh measurements; Oda expressly remeasures path BER after a new wavelength-path signal is communicated. Thus, upon Frankel's detected wavelength-count change, discarding the prior regime's quality samples and re-acquiring a new time series would have been the predictable data-integrity response.
Accordingly, claim 11 would have been obvious.
Claim 12
With respect to claim 12, all limitations of claim 9 are taught by Robinson and Beacall, except wherein claim 12 recites the alternative response to a wavelength-count change: calculate a difference between signal-quality indices before and after the operation-state change and correct already-acquired indices based on that difference.
Frankel’742 states: “Comparison logic 330 can be configured to compare power levels of the signals and the OSC at the node to the respective baseline measurements. Identification logic 340 can be configured to identify a type of system perturbation based on the power level comparisons.” [Frankel’742, ¶ [0039]; FIG. 3].
Frankel’742 states: “These power measurements can be determined at start-up/installation of the system components. However, the values can also be periodically updated to account for changes in the network.” [Frankel’742, ¶ [0041]; FIG. 4A].
Oda states: “The update unit 47 in the controller 23A calculates a difference between the path OSNR based on the measured path BER and the path OSNR based on the path BER of estimation (Operation S36). Based on the calculated difference, the update unit 47 updates an OSNR of each span in the wavelength path of the estimation target, which is stored in the information storage unit 30 (Operation S37).” [Oda, ¶ [0104]; FIG. 13B].
Oda thus expressly teaches the alternative to discarding data: calculate a measured-versus-baseline quality difference and use that difference to correct previously stored path-quality parameters. In combination with Frankel's detection of a wavelength-count perturbation and Oda's post-addition BER remeasurement, the same difference-based update is directly applicable to normalizing quality samples across the operation-state transition.
Beacall states: “The degradation prediction algorithm 98 may also determine inter repeater 30 span loss changes and correlate the inter repeater span loss changes to Q changes across the communication system 10 thereby estimating performance impact per repair and producing a more accurate decision on whether or not to change the modulation format. For example, FIG. 23 shows the degradation rolloff prior to a repair, as well as correlated degradation and adjusted degradation time before next modulation format change. Repeater span losses are calculated by taking the optical power OUT of a repeater 30 (SLL) and the receive power in (RLL) for a downstream receiver, and then calculating the difference. Using span loss calculations and changes per span with corresponding changes in Q can be correlated over time to see where span degradation happens most and highlighting spans that have the most detrimental impact. In other words, the receiver OSNR depends on the span loss as well as other parameters, such as repeater output power and the like. An increase in the span loss will reduce the receiver OSNR. Because Q is related to receiver OSNR, the impact of a span loss increase on Q can be calculated.” [Beacall, ¶ [0154]; FIG. 23].
The combined references teach the operative pieces of the claimed normalization. Frankel identifies a wavelength-count change by comparing current power measurements with baseline measurements. Oda teaches that adding/communicating a wavelength can change path BER, remeasures quality after the change, calculates a difference between measured and baseline/estimated quality, and updates stored quality parameters based on that difference. Beacall independently teaches event-aware time-series Q analysis and the removal of event-induced skew.
Instead of discarding all pre-change measurements as in claim 11, a person of ordinary skill in the art would have recognized the known alternative expressly exemplified by Oda: determine the offset attributable to the changed operating condition and apply a difference-based update to the stored quality representation. Applying the observed before/after Q or BER difference associated with Frankel's detected wavelength-count transition to previously acquired quality indices preserves useful historical samples while translating them to the new operating baseline. This is a predictable baseline-normalization technique using quantities already measured by the cited systems and has the same technical purpose identified by Beacall—preventing a network event from skewing degradation analysis. Accordingly, claim 12 would have been obvious.
Claim 16 is rejected under 35 U.S.C. § 103 as being unpatentable over Robinson et al. in view of Beacall et al., further in view of Frankel et al. (US20180191432A1).
Claim 16
With respect to claim 16, all limitations of claim 9 are taught by Robinson and Beacall as set forth above, except wherein claim 16 further specifies that the signal-quality indices include one of a quality (Q) factor or a pre-error-correction bit-error rate of the signal light.
Robinson states: “the System devices may comprise an optical receiver providing a Q factor as the indicator of an optical Signal passing through the communication System. This receiver may also provide an actual observed bit error rate (BER) of the optical signal as another indicator.” [Robinson, ¶ [0020]].
Frankel’432 states: “existing channels provide a measure of both pre-corrected and post-corrected Forward Error Correction (FEC) error counts. These are only available for specific lightpaths, where channels with embedded FEC are already installed and operational. Further, pre-FEC bit error rate (BER) is only accurate at high values.” [Frankel’432, ¶ [0005]].
The additional limitation is therefore expressly taught. Robinson identifies Q and BER as receiver quality indicators, and Frankel expressly identifies pre-FEC BER as an available performance measurement on operating optical lightpaths. Selecting either Q or pre-FEC BER as the stored quality index would have been a routine choice based on receiver capability and operating BER range. Both are standard quality metrics serving the same monitoring purpose, and Beacall’s time-series database accepts performance attributes such as Q. Accordingly, claim 16 would have been obvious.
Claims 1-16 are rejected under 35 U.S.C. § 103 for the reasons set forth above. Each rejection identifies the scope and content of the relied-upon prior art, the differences from the claimed subject matter, and an articulated reason with rational underpinning for the proposed combination, consistent with Graham, KSR, and MPEP §§ 2141 and 2143.
It is noted that any citations to specific pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP § 2123.
Conclusion
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/MOHAMMED ABDELRAHEEM/Examiner, Art Unit 2635
/OMAR S ISMAIL/Primary Examiner, Art Unit 2635
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