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 2024-02-28 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 1-18, 20 and 27 are pending in this application and are under examination in this Office Action. Claims 19 and 21–26 and 28-30 are canceled. No claims have been allowed.
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:
Determining the scope and content of the prior art;
Ascertaining the differences between the prior art and the claims at issue;
Resolving the level of ordinary skill in the pertinent art; and
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 of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. 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 that was not commonly owned as of the effective filing date of the later invention in order for the examiner to 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 later invention.
Claims 1,2,8,14,15 and 27 are rejected under 35 U.S.C. §103 as being unpatentable over SAKAMOTO (US 2012/0301137 A1) in view of ICHIKAWA (JP 2002-171584 A) and further in view of KWON (US 2003/0066953 A1).
Claim 1
Claim 1 recites an optical path state assessment device having one or more memories storing instructions and one or more processors configured to execute the instructions to (i) receive propagation light propagating through an optical transmission line in a latter stage of an optical path switching device that switches a path of signal light, (ii) generate optical spectrum information of the propagation light, and (iii) assess a switching state of the optical path switching device from the optical spectrum information.
With respect to claim 1, all limitations of claim 1 are taught by SAKAMOTO in view of ICHIKAWA et al. and further in view of KWON, as set forth below limitation-by-limitation.
SAKAMOTO teaches “receive propagation light propagating through an optical transmission line in a latter stage of an optical path switching device that switches a path of signal light,” because SAKAMOTO receives spectrum information from an optical channel monitor located on an outgoing path (i.e., after the optical cross connect switch): “[0058] In step S12, the management complex (MC) 90 receives a frequency spectrum supplied by an optical channel monitor (e.g., 92-8 in FIG. 3) monitoring the outgoing path (i.e., the port #8) and determines whether the received frequency spectrum contains a peak frequency corresponding to the third fixed pattern (e.g., the peak frequency f2 in FIG. 4C). In step S13, if the received frequency spectrum contains the peak frequency corresponding to the third fixed pattern ("YES" in step S13), the result is determined as "OK" and the erroneous optical fiber connection monitoring processing is terminated ( end of the monitoring processing).” [SAKAMOTO, ¶[0058]].
SAKAMOTO further teaches “generate optical spectrum information of the propagation light,” because SAKAMOTO provides a detector configured to detect a frequency spectrum of the multiplexed optical signal on the outgoing path: “[0024] According to an aspect of an embodiment, a node device includes a data pattern generator configured to generate different fixed patterns for a plurality of ports to insert the generated fixed patterns into optical signals output from a plurality of optical transmitters; an optical switch configured to switch outgoing paths of the optical signals to output the optical signals as a multiplexed signal from one of the ports; a detector configured to detect a frequency spectrum of the multiplexed optical signal; and a management part configured to monitor a peak frequency of the detected frequency spectrum to detect an erroneous optical fiber connection associated with the optical transmitters based on peak frequencies corresponding to the different fixed patterns for the respective ports.” [SAKAMOTO, ¶[0024]].
SAKAMOTO teaches “assess a switching state of the optical path switching device from the optical spectrum information,” because SAKAMOTO monitors whether the detected spectrum contains the expected peak frequency and determines OK versus NG (alarm) and then switches an optical cross connect (OXC) outgoing path when NG is determined: “[0059] If, on the other hand, the received frequency spectrum does not contain the peak frequency corresponding to the third fixed pattern ("NO" in step S13), the result is determined as "NG" and an alarm is generated in step S15. Subsequently, in step S16, the management complex (MC) 90 switches an optical cross connect switch ( e.g., the optical cross connect switch (OXC) 81 in FIG. 3) switching the outgoing path to another one to which the optical signal is to be supplied by the transponder 77d. Thereafter, step S12 is processed again.” [SAKAMOTO, ¶[0059]].
ICHIKAWA similarly teach assessing a switch path/state using spectrum/wavelength information measured after the optical switch, because ICHIKAWA provides inspection light of predetermined wavelengths, detects wavelength of light after passing through the optical switch, and discriminates the optical path based on a stored discrimination table and the detected result: “Abstract PROBLEM TO BE SOL VED: To provide an optical switch inspection device that can efficiently inspect optical paths. SOLUTION: The optical switch inspection device is provided with a light source section 1 that outputs inspection light beams 01-04 with predetermined and different wavelengths by each of optical input terminals 121a-121b, a detection section 3 that detects the wavelength of inspection light beams 05-08 from optical output terminals 121e-121h after passing through the optical path of an optical switch and provides an output of the result of detection, a storage section 53 that stores in advance an optical path discrimination table 10 denoting a wavelength to be detected depending on the optical path, and a discrimination section 5 that discriminates the optical path of the optical switch on the basis of the optical path discrimination table 10 and the result of detection.” [ICHIKAWA, Abstract].
SAKAMOTO and ICHIKAWA do not expressly recite “one or more memories storing instructions” and “one or more processors configured to execute the instructions” in those exact words. However, within analogous art, KWON expressly teaches a microprocessor executing a stored program in an internal memory to control an optical switch and process optical values: “[0034] The microprocessor 34, in accordance with a masked program in an internal memory, transmits control data corresponding to the switching control signal (SCTL) and the filtering control signal (FTCS) shown in FIG. 1 to a digital to analog converter (DAC) 36, and controls the optical switch 18 and the tunable optical filter 28 using the analog signal as in FIG. 1. Also, the microprocessor 34 inputs a value of the wavelength division multiplexed optical signal (WDMOS) outputted from the analog to digital converter 32 and a value of the amplified spontaneous emission (ASE) with the added reference wavelengths of the main mode Ml and the side mode Sl. Further, the microprocessor 34 finds out the reference wavelength values of the main modes Ml and M2, and the side modes Sl and S2 out of the inputted amplified spontaneous emission (ASE) value. Here, the main modes Ml and M2, and the side modes Sl and S2, are reference signals of the amplified spontaneous emission, and the reference signal is used for calculating the optical signal (WDMOS) wavelength, the optical power, and the optical signal to noise ratio.” [KWON, ¶[0034]].
One of ordinary skill in the art would have been motivated to combine the spectrum-based outgoing-path monitoring and OK/NG determination of SAKAMOTO with ICHIKAWA’s wavelength-based optical-path discrimination and with KWON’s explicit microprocessor/memory execution framework, because each reference is directed to optical switching/monitoring in optical networks and the combination yields the predictable result of implementing a processor-executed spectrum/wavelength analysis to assess the switching state of an optical path switching device using measured optical spectrum information downstream of the switch.
Claim 2
Claim 2 depends from claim 1 and further recites determining, from the optical spectrum information, whether the propagation light includes “specific light,” and assessing a first switching state when the specific light is present and a second switching state when it is absent.
With respect to claim 2, all the limitations of claim 1 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, except claim 2 explicitly recites determining whether the propagation light includes specific light and assessing a first switching state when present and a second switching state when absent.
However, SAKAMOTO teaches determining, based on optical spectrum information (i.e., a received frequency spectrum), whether the propagation light includes specific light by checking for the presence/absence of an expected spectral peak corresponding to the routed signal. For example, SAKAMOTO states: “If, on the other hand, the received frequency spectrum does not contain the peak frequency corresponding to the third fixed pattern ("NO" in step S13), the result is determined as "NG" and an alarm is generated in step S15. Subsequently, in step S16, the management complex (MC) 90 switches an optical cross connect switch (e.g., the optical cross connect switch (OXC) 81 in FIG. 3) switching the outgoing path to another one to which the optical signal is to be supplied by the transponder 77d. Thereafter, step S12 is processed again.” [SAKAMOTO, ¶[0059]]. Accordingly, when the received spectrum includes the specific peak (signal present), the optical path switching device is assessed as being in the first switching state (signal sent to the optical transmission line), and when the spectrum lacks the specific peak (signal absent), the optical path switching device is assessed as being in the second switching state (signal sent to other than the optical transmission line).
SAKAMOTO also teaches comparing measured spectra to expected spectral signatures (e.g., fixed patterns/expected components) to determine whether a particular spectral component is present, and using that presence/absence information to identify the output port/path state (SAKAMOTO, ¶¶[0058]–[0060]). ICHIKAWA similarly teaches determining the switch state by detecting whether a particular inspection wavelength is present at the monitored output (ICHIKAWA, Abstract). KWON provides the programmed processor and memory framework for executing this determination/assessment logic (KWON, ¶[0034]).
It would have been obvious to combine these teachings because each reference addresses spectrum-based determination of which path is selected, and combining them yields the predictable result of reliably assessing switch state based on the presence/absence of a specific spectral component.
A POSITA would have applied SAKAMOTO’s peak-present versus peak-absent decision logic to assess whether the signal is being sent to the monitored optical transmission line (first state) or is routed elsewhere / not delivered to that line (second state), because the spectrum evidence provides an objective indicator of routing state with predictable results.
Claim 8
Claim 8 depends from claim 1 and further recites assessing that the optical path switching device is in a state where signal light is sent to other than the optical transmission line when determining from the optical spectrum information that it is in a no-signal state.
With respect to claim 8, all limitations of claim 1 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, except claim 8 explicitly assesses that the switch sends signal light to other than the optical transmission line when a no-signal state is determined from spectrum information.
SAKAMOTO teaches evaluating whether an expected spectral component/peak is present in the measured spectrum, and generating an abnormality/NG determination (no-signal / missing peak) when it is not detected (SAKAMOTO, ¶¶[0059]–[0060]). Under the claimed context, a no-signal determination at the monitored output corresponds to the switch being set to send the signal to a different path (i.e., other than the monitored optical transmission line). ICHIKAWA’s inspection approach similarly uses detection/non-detection of an inspection wavelength at an output to infer the selected path (ICHIKAWA, Abstract). KWON provides the programmable processing architecture for making this assessment (KWON, ¶[0034]).
SAKAMOTO, also teaches that when the expected spectral peak is absent, NG is determined and corrective switching may be performed (e.g., via OXC), indicating the signal is not on the monitored line [SAKAMOTO, ¶[0059]].
A POSITA would interpret the no-peak/no-signal determination as indicating that the signal is routed elsewhere or not delivered to that line and would assess the state accordingly because that conclusion directly follows from spectrum-based monitoring evidence and known OXC switching behavior.
Claim 14
Claim 14 recites an optical path state assessment method comprising (by a computer): receiving propagation light propagating through an optical transmission line in a later stage of an optical path switching device that switches a path of signal light; generating optical spectrum information of the propagation light; and assessing a switching state of the optical path switching device from the optical spectrum information.With respect to claim 14, all method limitations are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON.
SAKAMOTO teaches monitoring an outgoing/selected optical line downstream of an optical cross-connect switch (OXC), obtaining a frequency spectrum of the outgoing light using an optical channel monitor (OCM), and providing the spectrum to a management complex for evaluation (SAKAMOTO, ¶¶[0058]–[0060]; FIGS. 2–3, 5).
SAKAMOTO further teaches assessing the path/switching state by determining whether the received spectrum contains an expected peak frequency/pattern associated with the selected port/path and generating an abnormality (NG/alarm) when the expected spectral component is absent (SAKAMOTO, ¶[0059]).
ICHIKAWA similarly teaches detecting wavelength(s) of inspection light after passing through an optical switch and discriminating the optical path based on stored wavelength-to-path correspondence (ICHIKAWA, Abstract). However, KWON teaches executing programmed instructions on a microprocessor (with internal memory) for optical monitoring/control operations, consistent with the “by a computer” limitation (KWON, ¶[0034]).Accordingly, it would have been obvious to implement the method steps of claim 14 using SAKAMOTO’s spectrum-based monitoring/decision logic together with ICHIKAWA’s wavelength/path discrimination, on KWON’s programmed processor platform, because the combination yields the predictable result of determining switch/path state from downstream spectrum measurements in a switched optical transmission system.
Claim 15
Claim 15 recites an optical path state assessment method corresponding to the device functionality of claim 1 (receiving propagation light downstream of an optical path switching device; generating optical spectrum information; and assessing switching state from the optical spectrum information).
With respect to claim 15, all limitations of claim 14 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON except Claim 15 adds branching assessment based on whether propagation light includes specific light. SAKAMOTO teaches checking whether spectrum contains the expected peak and determining NG when absent [SAKAMOTO, ¶[0059]].
Further, SAKAMOTO, teaches receiving optical signals on an outgoing path of an OXC (i.e., downstream/latter stage relative to switching) and obtaining frequency spectrum information for those optical signals (SAKAMOTO, FIGS. 2 and 5; ¶¶[0024], [0058]–[0059]). SAKAMOTO further teaches assessing the path state by evaluating the measured spectrum versus expected spectral components associated with a selected port/path (SAKAMOTO, ¶¶[0059]–[0060]).
SAKAMOTO’s spectrum evaluation provides the claimed “specific light” presence/absence determination: the expected peak frequency/pattern corresponds to a specific spectral component associated with the signal routed to the monitored optical transmission line. When the expected peak is detected (OK), this corresponds to the first switching state in which the signal light is sent to that optical transmission line; when the expected peak is not detected (NG), this corresponds to the second switching state in which the signal light is sent to other than the monitored optical transmission line (SAKAMOTO, ¶¶[0058]–[0060]).
However, ICHIKAWA teaches using detection/non-detection of a designated wavelength to discriminate the optical path (ICHIKAWA, Abstract), and KWON provides the programmed processor implementation for performing the determination and assessment steps (KWON, ¶[0034]).
Claim 27
Claim 27 recites a non-transitory computer-readable program record medium storing a program that causes a computer to execute (i) generating optical spectrum information of propagation light downstream of an optical path switching device and (ii) assessing a switching state of the optical path switching device from the optical spectrum information.
Claim 27 recites a non-transitory computer-readable program record medium recording a program for causing a computer to execute operations corresponding to claim 1 (i.e., generating optical spectrum information of propagation light and assessing a switching state from the optical spectrum information). With respect to claim 27, all limitations of claim 1 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON. In particular, KWON teaches a program recorded on a recording medium for causing a microprocessor to execute the inspection/control operations, including spectrum-based evaluation, as follows: “The microprocessor 34 reads out a masked program from a memory 42 and executes the program ... The microprocessor 34 inputs a value of the wavelength division multiplexed optical signal (WDMOS) outputted from the ADC 32 ...” [KWON, ¶[0034]]. Thus, it would have been obvious to provide the claimed non-transitory program record medium to implement the spectrum generation and switching-state assessment functions.
SAKAMOTO teaches the underlying spectrum acquisition and spectrum-based path-state assessment logic (frequency spectra supplied to a management complex for evaluation) (SAKAMOTO, ¶¶[0058]–[0060]).
However, in an analogous art , KWON teaches a memory (internal memory) storing a program (“masked program”) and a microprocessor executing the program to coordinate/control optical switching and spectrum-related monitoring functions “ The microprocessor 34, in accordance with a masked program in an internal memory, transmits control data corresponding to the switching control signal (SCTL) and the filtering control signal (FTCS) shown in FIG. 1 to a digital to analog converter (DAC) 36, and controls the optical switch 18 and the tunable optical filter 28 using the analog signal as in FIG. 1. Also, the microprocessor 34 inputs a value of the wavelength division multiplexed optical signal (WDMOS) outputted from the analog to digital converter 32 and a value of the amplified spontaneous emission (ASE) with the added reference wavelengths of the main mode Ml and the side mode Sl. Further, the microprocessor 34 finds out the reference wavelength values of the main modes Ml and M2, and the side modes Sl and S2 out of the inputted amplified spontaneous emission (ASE) value. Here, the main modes Ml and M2, and the side modes Sl and S2, are reference signals of the amplified spontaneous emission, and the reference signal is used for calculating the optical signal (WDMOS) wavelength, the optical power, and the optical signal to noise ratio. The reference wavelength values of the main modes Ml and M2, and the side modes Sl and S2, obtained from the amplified spontaneous emission (ASE) value, consist with the reflection wavelength values or the absorbance wavelength values of the tilted fiber bragg gratings 24 and 26, which are already known through the measurement. In this manner, that is, using the reference wavelength values of the main modes Ml, and the side modes Sl on the time base, the microprocessor 34 inputting the reference wavelength values can monitor the wavelength value, the optical signal power, and the optical signal to noise ratio of the successively inputted wavelength division multiplexed optical signal (WDMOS) more easily..” [KWON, ¶[0034]].
Therefore, it would have been obvious to store and execute instructions that implement SAKAMOTO’s spectrum-based path-state assessment on the programmable microprocessor/memory platform of KWON to yield the claimed program-record medium.
Claims 3,4,5,9,16,17 and 18 are rejected under 35 U.S.C. §103 as being unpatentable over SAKAMOTO in view of ICHIKAWA and further in view of KWON and GARIEPY (US 9,112,604 B2)
Claim 3
Claim 3 depends from claim 2 and further specifies that the “specific light” is at least one of signal light and amplified spontaneous emission (ASE) light, and that a first switching state is assessed when both signal light and ASE are present, whereas a second switching state is assessed when signal light is not present.
With respect to claim 3, all limitations of claims 1–2 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, except for expressly characterizing the spectrum-based determination in terms of signal light and ASE light together. claim 3 specifies the specific light is at least one of signal light and amplified spontaneous emission (ASE) light and recites decision logic based on signal + ASE versus absence of signal.
However, GARIEPY teaches optical spectrum trace analysis for estimating the spectral shape of a data-carrying signal contribution in the presence of noise and explicitly discusses ASE behavior in optical links “There is provided a method for determining an in-band noise parameter, such as the Optical Signal-to-Noise Ratio (OSNR), on an optical signal-under-test (SUT) propagating along an optical communication link and comprising a data carrying signal contribution of any arbitrary degree of polarization and a noise contribution. A spectral shape trace of data-carrying signal contribution in the SUT is estimated using a reference optical spectrum trace of a reference signal which comprises a data-carrying signal contribution that is spectrally representative of the data-carrying signal contribution of the SUT and a noise contribution which is at least approximately known. The data-carrying signal contribution is mathematically discriminated from said noise contribution in the SUT using the spectral shape trace and the test optical spectrum trace. The in-band noise parameter is then determined at least from the mathematically discriminated noise contribution” [GARIEPY, Abstract]. ASE discussion at ‘The Optical Signal-to-Noise Ratio (OSNR) is a direct indicator of the quality of signal carried by an optical telecommunication link. Under normal and proper operating conditions, the OSNR of an optical communication link is typically high, often in excess of 15 dB or 20 dB, or even greater. The dominant component of the noise in an optical communication link is typically unpolarized Amplified Spontaneous Emission (ASE), which is a broadband noise source contributed by the optical amplifiers in the link. In general, the ASE may be considered to be spectrally uniform across the small wavelength range spanning the signal spectral width’ [GARIEPY, p22].
GARIEPY also teaches that optical spectrum traces contain both a signal component (channel power/peaks) and an ASE noise component, and that the noise (ASE) level can be evaluated from the spectrum as a largely smooth/background component compared to the signal (GARIEPY, Abstract; col. 11, ll. 32–48).
Also, KWON teaches using ASE light and selected wavelengths as part of optical monitoring and control (KWON, ¶[0034]). Thus, it would have been obvious to interpret SAKAMOTO/ICHIKAWA’s presence/absence determinations in terms of whether the measured spectrum includes (i) signal light and (ii) ASE background, because GARIEPY explicitly teaches analyzing spectrum traces with both signal and ASE components for monitoring/assessment purposes, yielding the predictable result of assessing different switch states based on whether signal features are present above ASE background
A POSITA would have used GARIEPY’s spectrum-trace concepts to distinguish conditions where both a data-carrying signal component and ASE/noise are present versus conditions where the signal component is absent, because ASE is a known noise source and spectrum-based estimation techniques yield predictable identification of signal presence/absence.
Claim 4
Claim 4 depends from claim 3 and further recites determining that the propagation light includes both the signal light and the amplified spontaneous emission (ASE) light when, in wavelength dependency of an optical level of the propagation light included in the optical spectrum information, a discontinuous difference occurs in the optical level over the entirety of a wavelength band of the propagation light.
With respect to claim 4, all limitations of claims 1–3 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON and GARIEPY except for the specific “discontinuous difference” criterion tied to signal + ASE. GARIEPY teaches that when a signal is present, the spectrum includes distinct signal power (e.g., channel peaks) relative to a noise (ASE) level, whereas the ASE/background portion of the spectrum is comparatively smooth (GARIEPY, col. 11, ll. 32–48). The presence of distinct signal peaks constitutes a discontinuous difference in optical level across the band compared to the smooth noise background. Therefore, it would have been obvious to use the discontinuity (signal peaks above a smooth ASE level) as an indicator that both signal and ASE are present, as claimed.
claim 4 recites determining signal + ASE when a discontinuous difference occurs in optical level over the entirety of a wavelength band, where specifies the particular decision criterion that a discontinuous difference in wavelength-dependent optical level over the wavelength band is used to determine that both signal light and ASE light are present.
However, GARIEPY teaches deriving and using a spectral shape trace of a data-carrying signal contribution from optical spectrum traces, enabling identification of wavelength-dependent features/discontinuities indicative of signal contribution relative to noise
“There is provided a method for determining an in-band noise parameter such as the Optical Signal-to-Noise Ratio OSNR on an optical signal-under-test SUT propagating along an optical communication link and comprising a data carrying signal contribution of any arbitrary degree of polar ization and a” [GARIEPY, Abstract].
GARIEPY further, teaches estimating and using a spectral shape trace of the data-carrying signal contribution and mathematically discriminating noise from the data-carrying signal contribution using the spectral shape trace and the test optical spectrum trace, which inherently relies on identifying distinct wavelength-dependent spectral features attributable to the signal contribution relative to noise/ASE. (GARIEPY, Abstract; col. 11, ll. 32–48).
Thus, when the wavelength-dependent optical level exhibits discontinuous differences across the wavelength band (e.g., abrupt changes/peaks superimposed on a broadband ASE background), GARIEPY’s spectral-shape/trace analysis supports determining that a signal contribution is present in addition to ASE, corresponding to the claimed determination that the propagation light includes both signal light and ASE light. (GARIEPY, Abstract; col. 11, ll. 32–48).
“A spectral shape trace of data-carrying signal contribution in the SUT is estimated using a reference optical spectrum trace of a reference signal which comprises a data-carrying signal contribution that is spectrally representative of the data-carrying signal contribu tion of” [GARIEPY, Abstract].
A person of ordinary skill in the art would have been motivated to apply GARIEPY’s spectral-shape discrimination within SAKAMOTO’s downstream spectrum monitoring of an OXC output to improve reliability of distinguishing “signal+ASE” versus “ASE-only/no-signal” conditions, because doing so yields the predictable result of more accurate switching-state assessment from optical spectrum information.
A POSITA would have recognized that a discontinuity or distinct feature across the band in the derived spectral shape indicates the presence of a structured signal component in addition to ASE, and would have applied GARIEPY’s spectral-shape estimation to implement the claimed discontinuity-based determination with predictable results.
Claim 5
Claim 5 depends from claim 3 and further recites determining that the propagation light does not include the signal light when, in wavelength dependency of an optical level of the propagation light included in the optical spectrum information, the optical level continuously changes over the entirety of a wavelength band of the propagation light.
With respect to claim 5, all limitations of claims 1–3 are taught by the applied references, except where claim 5 specifies using a continuously changing wavelength-dependent optical level over the band to determine that the propagation light does not include the signal light which expressly using the “continuous change” criterion to infer no signal.
SAKAMOTO teaches determining whether an expected spectral component (peak frequency/pattern) is present and generating NG/alarm when the expected component is absent, consistent with determining that signal light is not present on the monitored optical transmission line. [SAKAMOTO, ¶[0059]].
However, in an analogous art, GARIEPY teaches that ASE noise appears as a comparatively uniform/smooth spectrum component (i.e., lacking distinct signal peaks) “evaluating the spectrum/trace shape and mathematically discriminating the noise contribution from the data-carrying signal contribution using the spectral shape trace and the test optical spectrum trace, supporting that when the measured spectrum lacks distinct signal features and instead presents a smooth/continuously varying in-band noise (ASE) profile over the wavelength band, the signal light is not present” (GARIEPY, col. 11, ll. 32–48). Thus, when only amplified spontaneous emission (ASE) light (and no signal peaks) is present, the spectrum exhibits a smooth/continuously varying level across the band. claim 5 recites determining no signal when the optical level continuously changes over the entirety of a wavelength band. Also, GARIEPY teaches spectrum-trace estimation of signal contribution relative to noise, supporting interpretation of a smooth/no-distinct-feature band as signal-absent [GARIEPY Abstract].
A person of ordinary skill in the art would have been motivated to combine SAKAMOTO’s no-expected-peak (NG) logic with GARIEPY’s spectral-shape discrimination to make the no-signal determination more robust, yielding the predictable result of correctly identifying the claimed second switching state conditions using optical spectrum information.
A POSITA would have applied SAKAMOTO’s no-peak/NG logic together with GARIEPY’s spectrum-trace interpretation to determine a no-signal condition when the band lacks identifiable signal features, because this is a predictable use of established spectrum-monitoring principles. It would have been obvious to use this continuous spectral behavior as an indicator of no signal light, yielding the predictable result of distinguishing the claimed states using spectrum shape
Claim 9
Claim 9 depends from claim 1 and further recites deriving an optical spectrum shape from the optical spectrum information and assessing the switching state from the optical spectrum shape. With respect to claim 9, all limitations of claim 1 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, except claim 9 requires deriving an optical spectrum shape from optical spectrum information and assessing the switching state from the optical spectrum shape.
SAKAMOTO teaches obtaining frequency spectra and using the spectrum information to determine whether expected spectral components are present for a given path/port (SAKAMOTO, ¶¶[0058]–[0060]).
However, GARIEPY teaches analyzing an optical spectrum trace (spectrum shape) to derive monitoring metrics (e.g., signal and noise characteristics) and to evaluate conditions/state based on the shape of the measured spectrum (GARIEPY, Abstract; col. 11, ll. 32–48).
GARIEPY also, expressly teaches estimating a spectral shape trace of the data-carrying signal contribution based on optical spectrum traces and using that trace for evaluation [GARIEPY, Abstract].
A POSITA would have used GARIEPY’s spectral-shape trace derived from measured spectrum information as an input to assess whether the monitored path state corresponds to expected signal conditions, because spectral-shape-based assessments are known and yield predictable results in optical monitoring. Therefore, it would have been obvious to assess switch state using the derived spectrum shape, as claimed.
Claim 16
Claim 16 depends from claim 15 and corresponds to claim 3 in method form (specific light is at least one of signal light and ASE; first state assessed when both signal and ASE are present; second state assessed when signal is absent). For the reasons discussed for claim 3, this is taught by SAKAMOTO/ICHIKAWA/KWON in view of GARIEPY (SAKAMOTO, ¶¶[0058]–[0060]; GARIEPY, col. 11, ll. 32–48; KWON, ¶[0034]).
With respect to claim 16, all limitations of claims 14 -15 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON except Claim 16 adds signal and/or ASE. GARIEPY teaches spectrum-trace analysis of data-carrying signal contribution in presence of noise and describes ASE behavior “The Optical Signal-to-Noise Ratio (OSNR) is a direct indicator of the quality of signal carried by an optical telecommunication link. Under normal and proper operating conditions, the OSNR of an optical communication link is typically high, often in excess of 15 dB or 20 dB, or even greater. The dominant component of the noise in an optical communication link is typically unpolarized Amplified Spontaneous Emission (ASE), which is a broadband noise source contributed by the optical amplifiers in the link. In general, the ASE may be considered to be spectrally uniform across the small wavelength range spanning the signal spectral width” [GARIEPY, p22].
Claim 17
Claim 17 depends from claim 16 and corresponds to claim 4 in that the assessing includes determining that the propagation light includes both the signal light and the ASE light when, in wavelength dependency of an optical level of the propagation light, a discontinuous difference occurs in the optical level over the entirety of the wavelength band.
With respect to claim 17, all limitations of claims 16 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON and GARIEPY except Claim 17 specifies the discontinuous-difference criterion across the wavelength band. As discussed for claim 4, GARIEPY’s spectral-shape trace analysis supports identifying distinct wavelength-dependent spectral features attributable to a data-carrying signal contribution relative to noise/ASE, consistent with a discontinuous difference in optical level across the band indicating signal+ASE. (GARIEPY, Abstract; col. 11, ll. 32–48). Claim 17 adds discontinuity-based signal + ASE determination. GARIEPY teaches that signal peaks relative to smooth ASE noise constitute a discontinuous difference in optical level across the band, supporting the claimed determination (GARIEPY, col. 11, ll. 32–48).
GARIEPY’s spectral-shape trace estimation supports wavelength-dependent feature/discontinuity interpretation for presence of signal contribution “.. A spectral shape trace of data-carrying signal contribution in the SUT is estimated using a reference optical spectrum trace of a reference signal which comprises a data-carrying signal contribution that is spectrally representative of the data-carrying signal contribution of the SUT and a noise contribution which is at least approximately known. The data-carrying signal contribution is mathematically discriminated from said noise contribution in the SUT using the spectral shape trace and the test optical spectrum trace. ” [GARIEPY, Abstract].
Claim 18
Claim 18 depends from claim 16 and corresponds to claim 5 in that it further recites determining that the propagation light does not include the signal light when, in wavelength dependency of an optical level of the propagation light included in the optical spectrum information, the optical level continuously changes over entirety of a wavelength band of the propagation light.
With respect to claim 18, all limitations of claim 16 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON and GARIEPY, except wherein the propagation light is determined not to include the signal light when the wavelength-dependent optical level continuously changes over the entire wavelength band. However, SAKAMOTO teaches making a no-signal/abnormal (NG) determination when the expected spectral peak is absent, as follows: “If, on the other hand, the received frequency spectrum does not contain the peak frequency corresponding to the third fixed pattern ("NO" in step S13), the result is determined as "NG" and an alarm is generated in step S15. Subsequently, in step S16, the management complex (MC) 90 switches an optical cross connect switch (e.g., the optical cross connect switch (OXC) 81 in FIG. 3) switching the outgoing path to another one to which the optical signal is to be supplied by the transponder 77d. Thereafter, step S12 is processed again.” [SAKAMOTO, ¶[0059]]. Further, in an analogous art, GARIEPY teaches analyzing spectral shape/trace features of an optical spectrum trace and discriminating signal contribution from noise, including situations where the spectrum is dominated by ASE-like noise and lacks distinct signal features, as follows: “A spectral shape trace of data-carrying signal contribution in the SUT is estimated using a reference optical spectrum trace of a reference signal which comprises a data-carrying signal contribution that is spectrally representative of the data-carrying signal contribution of” [GARIEPY, Abstract]. A person of ordinary skill in the art would have been motivated to apply SAKAMOTO’s peak-absence (no-signal) evaluation together with GARIEPY’s spectral-shape/trace analysis to robustly determine that the propagation light does not include the signal light when the optical level varies smoothly/continuously across the wavelength band, thereby improving optical path state assessment reliability in the presence of ASE/background noise.
Claims 6,11,12 and 13 are rejected under 35 U.S.C. §103 as being unpatentable over SAKAMOTO in view of ICHIKAWA and further in view of KWON and ARCHAMBAULT (WO 2011139757 A1).
Claim 6
Claim 6 depends from claim 2 and further recites that the specific light is an identification signal whose spectrum shape is shaped and inserted in the optical path switching device or an upstream stage.
With respect to claim 6, all limitations of claim 2 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, except for expressly using a shaped-spectrum identification signal. ARCHAMBAULT teaches embedding identification information in a designated “topology wavelength” by toggling a wavelength selective switch (WSS) to transmit a specific identification signal (card ID) on that wavelength, which is then detected/used by the network (ARCHAMBAULT, ¶[0024]). This provides an identification signal with a defined spectral characteristic at a selected wavelength that can be inserted upstream of a monitored point.
claim 6 specifies that the specific light is an identification signal whose spectrum shape is inserted in the optical path switching device or a former stage.
ARCHAMBAULT also, teaches using a dedicated topology wavelength carrying a card-ID identification signal and discovering interconnections by toggling a WSS between inputs and reading the card-ID signal from each input “Referring to FIG. 5, in an exemplary embodiment, a flowchart illustrates an exemplary automated topology method 500 for detecting interconnections between degrees in a ROADM node/network/system. Similar to the automated topology method 400, the automated topology method 500 may be implemented with any node or network configured to provide automated topology discovery for colorless, directionless ROADMs. In particular, the automated topology method500 designates one of a plurality of wavelengths as a topology wavelength (step 502). In the example of FIGS. 2 - 3, the system includes 96 total wavelengths and λ96 is designated as the topology wavelength. The topology wavelength is dedicated across all nodes solely for automated topology discovery and thus is unavailable for carrying traffic. The automated topology method 500 is configured to detect connections between ROADM cards/nodes/degrees using transmitters and receivers for the topology wavelength built into each ROADM card, such as described in FIGS. 2 - 3. The automated topology method 500 may be manually or automatically initiated (step 504). The transmitter includes a laser emitting at the topology wavelength, e.g. λ96, which is transmitted to other nodes/cards/degrees (step 506). In an exemplary embodiment, information about the node, address card ID/location, etc. may be encoded in an output signal of the topology wavelength. This card ID signal is combined with the WDM channels using an Add filter and then broadcast to the other ROADM cards via a lxN splitter. The other ROADM cards can then discover which cards they are connected to by toggling the WSS at λ96 between their different inputs and reading the card ID signal from each input port (step 508). Note, e.g. in FIG. 2, that the WSS output is followed by a 1x3 splitter, with one output going to the OCM, one to the local λ96 receiver and one to the output fiber connected to the next node. Since λ96 (i.e., the topology wavelength) is within the gain bandwidth of the optical amplifiers, the card ID signal will propagate to the next node, where it is dropped to another λ96receiver, thus providing information about node-to-node connectivity. In this way, the entire mesh optical network can be mapped without disrupting the data traffic. Additionally, interconnection data between the ROADM nodes may be sent via a data communications link to an NMS, EMS, etc. and stored therein in a database or the like.” [ARCHAMBAULT ¶[0024]].
One of ordinary skill in the art would have been motivated to use ARCHAMBAULT’s identification/topology wavelength technique with SAKAMOTO’s spectrum-based monitoring to improve state determination and to provide an unambiguous identifier for the monitored optical path, because dedicated ID wavelengths are known to provide robust detection in ROADM/WSS systems. It would have been obvious to incorporate ARCHAMBAULT’s identification signaling into SAKAMOTO/ICHIKAWA’s spectrum-based switch-state assessment so that the presence/absence (or shape) of the identification signal in the measured spectrum can be used as the “specific light” for determining the switch state, because this yields a predictable improvement in diagnosability and reduces ambiguity compared to relying only on traffic-dependent signals.
Claim 11
Claim 11 recites an optical transmission system including (i) a first optical path state assessment device of claim 1, (ii) a second optical path state assessment device of claim 1, and (iii) an optical path switching device, wherein the first and second devices generate first and second optical spectrum information, respectively.
With respect to claim 11, all limitations of claim 11 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON and ARCHAMBAULT, except claim 11 recites a first and a second optical path state assessment device each being the device of claim 1 and each generating respective optical spectrum information (first and second optical spectrum information) for assessing an optical path switching state.
SAKAMOTO teaches a network including an OXC and monitoring arrangements supplying frequency spectra for multiple optical signals/ports to a management complex (SAKAMOTO, FIGS. 2 and 5; ¶¶[0024], [0058]–[0059]). This inherently involves multiple monitored points producing spectrum information.
SAKAMOTO also, teaches a management complex receiving frequency spectra from multiple optical receivers corresponding to outgoing paths/ports, consistent with multiple optical path state assessment devices generating first and second spectrum information “ Thus, even if the optical fibers are erroneously connected, the optical signal output by the transponder subject to monitoring may be output from a desired one of the outgoing paths. Note that in step S16, the management complex (MC) 90 may receive all the frequency spectra supplied by optical channel monitors (e.g., 92-1 to 92-8 in FIG. 3) monitoring the corresponding outgoing paths, determine which one of the received frequency spectra contains the peak frequency corresponding to the third fixed pattern (i.e., the peak frequency f2 in FIG. 4C), and switch the optical cross connect switch (OXC) 81 to switch the outgoing path to the desired path to which the transponder supplies the optical signal..” [SAKAMOTO, ¶[0060]].
SAKAMOTO does not expressly teach a ROADM/WSS module However, in an analogous art, ARCHAMBAULT teaches a ROADM/WSS module that can include an optical channel monitor (OCM) for measuring per-channel power and can use OCM/receiver placement after a WSS “ Referring to FIG. 3, in an exemplary embodiment, each of the degrees 1 12, 1 14, 1 16, 1 18may include a module 200 with automated topology discovery capability. The module 200 supports a single degree in a ROADM node using a broadcast-and-select architecture. Note, the broadcast-and-select architecture is shown for illustration purposes, and the module 200 may support other implementations. Further, the various components described herein with respect to the module 200may be integrated into a single device, line card, module, etc. or may be distributed among several devices, line cards, modules, etc. In general, the module 200 includes a line side 202 and a node side204, i.e. the line side 202 connects to a network and the node side 204 connects to local add/drop and/or other degrees. The module includes a lxN splitter 206 and a Nxl wavelength selective switch (WSS) 208. The l N splitter 206 is utilized on a receive side (relative to the network) and the Nxl WSS208 is utilized on a transmit side (relative to the network), and those of ordinary skill in the art will recognize that the module 200 could be constructed switching the location of the lxN splitter 206 and the Nxl WSS 208 or replacing the lxN splitter 206 by a second Nxl WSS 208. The lxN splitter 206 is configured to broadcast an input (received) signal from one direction to various other interconnected degrees. The Nxl WSS 208 is configured to receive input (transmit) signals from the various interconnected degrees and to select appropriate signals for transmission to the network. Additionally, the module 200 may include an optical channel monitor (OCM) 210 for measuring individual per-channel power at various points in the module 200. In an exemplary embodiment, the OCM 210 may be utilized in place of the optical receiver 232 to detect the topology wavelength.
In various exemplary embodiments, the present invention includes an automated topology that enables the module 200 to do a complete mapping of the optical connections within a mesh optical network (i.e., to other modules 200) that includes tunable lasers and multi-degree ROADM's with colorless/directionless add/drop. Advantageously, the additional hardware/software that is required (add/drop filters, low speed transmitters and receivers), is relatively simple and inexpensive, using off-the-shelf components. Specifically, the present invention includes designating one of a plurality of support wavelengths solely for topology discovery. For example, assume a wavelength division multiplexed (WDM) system using the module 200 supports 96 possible wavelengths, which normally would all be available to carry data. The present invention reserves one of these wavelengths, designated as λ96, for topology discovery, i.e. only 95 wavelengths are available to carry data. Note, the particular WDM system may use any wavelength and may include any amount of total supported wavelengths. Further, the topology wavelength does not necessarily have to be a fixed wavelength. the user or even the system software could choose any one of the available wavelengths as it sees fit. Here, the topology wavelength may include a tunable transceiver. This approach of the present invention may be used both to verify connections between the transceivers (XCVR's) and ROADM cards such as the module 200, as well as connections between ROADM cards, within the same network element or across different nodes.. [ARCHAMBAULT ¶[0019] - [0020]], supporting an optical transmission system having multiple assessment devices and a switching device as in claim 11.
Also, ARCHAMBAULT teaches architectures with wavelength-selective switching and associated monitoring/identification signaling on topology wavelengths across network elements (ARCHAMBAULT, ¶¶[0019]–[0020], [0024]).
Thus, it would have been obvious to provide first and second assessment devices (e.g., at different monitored outputs/locations) that each generate their own optical spectrum information associated with the switch state, as an obvious duplication of known monitoring points for improved observability and redundancy.
Claim 12
Claim 12 depends from claim 11 and recites that the first and second devices assess the switching state from at least one of the first and second optical spectrum information
With respect to claim 12, all limitations of claim 11 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON and ARCHAMBAULT, except claim 12 recites that the first optical path state assessment device and the second optical path state assessment device assess the switching state from at least one of the first optical spectrum information and the second optical spectrum information.
SAKAMOTO teaches using received spectrum information to assess path state (SAKAMOTO, ¶¶[0059]–[0060]). Given multiple spectrum sources (first/second devices),
SAKAMOTO’s management processing uses received spectra corresponding to outgoing paths to determine whether expected conditions are met, thereby using at least one spectrum dataset to assess state “.the frequency spectra supplied by optical channel monitors (e.g., 92-1 to 92-8 in FIG. 3) monitoring the corresponding outgoing paths, determine which one of the received frequency spectra contains the peak frequency corresponding to the third fixed pattern (i.e., the peak frequency f2 in FIG. 4C), and switch the optical cross connect switch (OXC) 81 to switch the outgoing path to the desired path to which the transponder supplies the optical signal..” [SAKAMOTO, ¶[0060]]. It would have been obvious to assess state from either one or both spectra, depending on availability/quality, as a routine design choice for fault tolerance.
Claim 13
Claim 13 depends from claim 11 and further recites a network management device that acquires the first and second optical spectrum information from the first and second devices and assesses the switching state based on both.
With respect to claim 13, all limitations of claim 11 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON and ARCHAMBAULT, except claim 13 further recites a network management device that acquires the first optical spectrum information from the first device, acquires the second optical spectrum information from the second device, and assesses the switching state based on the first and second optical spectrum information.
SAKAMOTO explicitly teaches a management complex receiving frequency spectra supplied from monitored optical signals and using that information for evaluation/management (SAKAMOTO, ¶[0058]).
However in an analogous art, ARCHAMBAULT teaches that interconnection data may be sent via a data communications link to an NMS/EMS and stored in a database “Referring to FIG. 5, in an exemplary embodiment, a flowchart illustrates an exemplary automated topology method 500 for detecting interconnections between degrees in a ROADM node/network/system. Similar to the automated topology method 400, the automated topology method 500 may be implemented with any node or network configured to provide automated topology discovery for colorless, directionless ROADMs. In particular, the automated topology method500 designates one of a plurality of wavelengths as a topology wavelength (step 502). In the example of FIGS. 2 - 3, the system includes 96 total wavelengths and λ96 is designated as the topology wavelength. The topology wavelength is dedicated across all nodes solely for automated topology discovery and thus is unavailable for carrying traffic. The automated topology method 500 is configured to detect connections between ROADM cards/nodes/degrees using transmitters and receivers for the topology wavelength built into each ROADM card, such as described in FIGS. 2 - 3. The automated topology method 500 may be manually or automatically initiated (step 504). The transmitter includes a laser emitting at the topology wavelength, e.g. λ96, which is transmitted to other nodes/cards/degrees (step 506). In an exemplary embodiment, information about the node, address card ID/location, etc. may be encoded in an output signal of the topology wavelength. This card ID signal is combined with the WDM channels using an Add filter and then broadcast to the other ROADM cards via a lxN splitter. The other ROADM cards can then discover which cards they are connected to by toggling the WSS at λ96 between their different inputs and reading the card ID signal from each input port (step 508). Note, e.g. in FIG. 2, that the WSS output is followed by a 1x3 splitter, with one output going to the OCM, one to the local λ96 receiver and one to the output fiber connected to the next node. Since λ96 (i.e., the topology wavelength) is within the gain bandwidth of the optical amplifiers, the card ID signal will propagate to the next node, where it is dropped to another λ96receiver, thus providing information about node-to-node connectivity. In this way, the entire mesh optical network can be mapped without disrupting the data traffic. Additionally, interconnection data between the ROADM nodes may be sent via a data communications link to an NMS, EMS, etc. and stored therein in a database or the like” [ARCHAMBAULT ¶[0024]]. A POSITA would have used centralized NMS/EMS to aggregate spectrum/connection information from multiple monitors because centralized aggregation is standard in optical networks for improving reliability and diagnostic accuracy. Therefore, it would have been obvious for the network management device to acquire first and second spectrum information and assess switch state based on both, particularly to improve confidence and aid troubleshooting across multiple monitored points.
Claim 7 and 20 are rejected under 35 U.S.C. §103 as being unpatentable over SAKAMOTO in view of ICHIKAWA and further in view of KWON and HESTER (US7046929B1).
Claim 7
Claim 7 depends from claim 1 and further recites that when the propagation light includes only ASE, the switching state is assessed from alarm information indicating occurrence of a failure and the optical spectrum information.
With respect to claim 7, all limitations of claim 1 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, except for expressly using alarm information together with spectrum information in the “only ASE” condition. SAKAMOTO teaches generating an abnormality/NG indication based on spectrum evaluation (e.g., missing expected spectral peak) (SAKAMOTO, ¶¶[0059]–[0060]). HESTER teaches generating and using network alarm/issue information (e.g., problem lists/issue summaries identifying failed equipment/impacted channels) for diagnosing network switching/connection problems (HESTER, col. 11–12).
claim 7 requires that when the propagation light includes only ASE, the switching state is assessed from alarm information indicating occurrence of a failure together with optical spectrum information.
HESTER also, teaches fault detection and isolation that correlates system faults and initiates restoration actions such as line switches or equipment switches “ Each problem entry in the problem list may have an associated entry describing additional information from other nodes that can be correlated (compared) with the local loss of signal in order to isolate the problem to one or more likely causes. However, in some cases there may be insufficient information to uniquely isolate the problem to a single cause. In this case, the node may attempt a local solution (e.g., a line switch or an equipment switch) that is the most likely to restore traffic. If the restoration event does not result in a restoration of the dropped channel (s), then this failure may be reported to other nodes (e.g., a list of faulty components published) in order to assist those nodes to make an appropriate equipment switch or line switch. As an illustrative example, a first node may build a list of potentially failed components within the first node based upon information from a channel map (a list of active channels at various locations in the network) distributed through the OSC and the dropped channel(s) observed by sensors coupled to the first node. The first node may then attempt an equipment switch of one or more of the components in the its problem list of potentially failed components. If the equipment switch does not restore the dropped traffic (i.e., restore the dropped channel(s)) the node forwards a summary of the failed equipment switch event that may assist other nodes to detect and isolate the problem. For example, the summary of the failed equipment switch event may include a list of dropped channel(s), the components in the first node suspected of having failed, and the result of the equipment switch (e.g., which of the dropped channels the equipment switch did not restore) ” [HESTER, Column 11-12]
A POSITA would have incorporated HESTER’s fault/alarm-driven restoration assessment into SAKAMOTO’s monitoring workflow when only ASE/no-signal is observed, because combining alarm context with measurement context provides more reliable state assessment and is a predictable improvement in optical network operations. It would have been obvious to use HESTER’s alarm/failure information in combination with SAKAMOTO’s spectrum information when the measured spectrum lacks signal features (e.g., only background/ASE-like behavior), because combining spectrum-based indicators with alarm context yields a predictable and well-understood improvement in accurately diagnosing the switch state/failure condition.
Claim 20
Claim 20 depends from claim 14 and corresponds to claim 7 in method form (assessing switch state from alarm information and optical spectrum information when only ASE is determined).
With respect to claim 20, all limitations of claims 14 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON except Claim 20 adds alarm information + optical spectrum information when only ASE is present. HESTER teaches correlating system faults/alarms and initiating restoration switching “ The first node may then attempt an equipment switch of one or more of the components in the its problem list of potentially failed components. If the equipment switch does not restore the dropped traffic (i.e., restore the dropped channel(s)) the node forwards a summary of the failed equipment switch event that may assist other nodes to detect and isolate the problem. For example, the summary of the failed equipment switch event may include a list of dropped channel(s), the components in the first node suspected of having failed, and the result of the equipment switch (e.g., which of the dropped channels the equipment switch did not restore) ” [HESTER, Column 11-12].
Claim 10 is rejected under 35 U.S.C. §103 as being unpatentable over SAKAMOTO in view of ICHIKAWA and further in view of KWON, GARIEPY and MUSUMECI (WO 2019170873 A1).
Claim 10
Claim 10 depends from claim 9 and further recites assessing the switching state by use of a discrimination algorithm by machine learning.
With respect to claim 10, all limitations of claim 9 are taught by SAKAMOTO in view of ICHIKAWA and further in view of KWON, GARIEPY and MUSUMECI except for expressly using machine learning for the discrimination/assessment. MUSUMECI teaches applying a machine-learning classifier (e.g., support vector machine, artificial neural networks, or other supervised ML) to extracted features derived from optical signal measurements for classifying/identifying a condition/state (MUSUMECI, Abstract). Claim 10 requires assessing by use of a discrimination algorithm by machine learning.
MUSUMECI also, teaches applying an identification algorithm comprising a classifier configured to identify a failure cause based on measurements using a machine learning technique “The method involves measuring a transmission parameter of an optical channel for a pre-defined measuring time interval at a receiver. Presence of anomaly in the measurements is checked on the basis of the measurements of transmission parameter in the time interval, where the anomaly is indicative of a subsequent failure of a system. An identification algorithm is applied to the measurements in the presence of the anomaly, where the algorithm comprises a classifier that is configured to identify a cause of a failure on the basis of the measurements based on a machine learning technique. DESCRIPTION - An INDEPENDENT CLAIM is also included for a monitoring unit for an optical communication system. USE - Method for monitoring an optical communications system. ADVANTAGE - The method enables implementing cross-validation technique to avoid over-fitting and to reduce error on test examples to allow a rapid detection of a soft-failure before occurring such that a network operator can quickly implement specific failure repair procedures to guarantee a quality of service (QoS) agreed with customers. The method enables continuously measuring transmission parameters at the receivers and collecting data for the learning examples to obtain a highly adaptive and flexible process with respect to the dynamic conditions of the monitored system .” [MUSUMECI abstract]
One of ordinary skill in the art would have been motivated to apply MUSUMECI’s ML-based classifier to spectral-shape features derived as taught by GARIEPY in the monitoring framework of SAKAMOTO, because ML classifiers improve discrimination accuracy in complex measurement spaces and yield predictable improvements in state classification. It would have been obvious to apply MUSUMECI’s ML-based discrimination approach to the spectrum-shape features/metrics derived from GARIEPY/SAKAMOTO spectrum information in order to automate and improve the robustness of switch-state classification, because ML classifiers are known to provide predictable improvements in discrimination accuracy for multi-feature optical monitoring problems.
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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Mohammed Abdelraheem, whose telephone number is (571) 272-0656. The examiner can normally be reached Monday–Thursday.
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/MOHAMMED ABDELRAHEEM/Examiner, Art Unit 2635
/DAVID C PAYNE/Supervisory Patent Examiner, Art Unit 2635