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 January 10, 2025, 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 1-15 are pending in this application and are under examination in this Office Action. No claims have been allowed.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. FIG. 1, step 102, recites "acquiring a first signal spectrum and a first power spectrum corresponding to the first test" and omits the word "signal" after "first test." Claim 1 and the written description, including paragraphs [0048]-[0049], identify the recited feature as a first signal spectrum and a first power spectrum corresponding to a first test signal.
Thus, FIG. 1 does not accurately show the claimed and described first test signal at step 102. The drawing should be corrected so that step 102 accurately recites the first test signal.
No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application.
Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended.
The figure or figure number of an amended drawing should not be labeled as "amended." If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures.
Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either "Replacement Sheet" or "New Sheet" pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action.
The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
paragraph [0074]
states that the optical communication system "determines the dimension according to the noise spectrum and the second signal spectrum corresponding to the second test signal," even though the surrounding disclosure concerns determining and improving the frequency response of the Wiener filter.
paragraph [0181]
states that the disclosed combinations are "within the scope of this manual," which is inconsistent with the terminology used throughout the patent disclosure. These informalities render the affected passages unclear and should be corrected to use accurate and consistent terminology. Appropriate correction is required.
Claim Objections
Claim 1 is objected to because of the following informality: the limitation "acquiring a second signal spectrum corresponding to the second test signal" uses the definite article "the" upon the first introduction of the second test signal and therefore lacks explicit antecedent basis for "the second test signal." The intended referent is otherwise reasonably ascertainable from the claim, so this matter is treated as a claim-form informality rather than as a rejection under 35 U.S.C. 112(b). Appropriate correction is required, for example by introducing "a second test signal" at its first occurrence.
Claim Interpretation - 35 U.S.C. § 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) ELEMENT IN CLAIM FOR A COMBINATION.—An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The limitations "noise spectrum determination module," "second spectrum acquisition module," and "filter determination module" of claim 10, and "received signal acquisition module" and "filtering module" of claim 11, are interpreted under 35 U.S.C. 112(f). Because claim 10 recites only "a first spectrum acquisition module" without a complete recitation of the function performed by that element, and claim 10 is separately rejected under 35 U.S.C. 112(b), no definitive 35 U.S.C. 112(f) construction of that isolated limitation is necessary at this time.
Regarding claims 10 and 11,
MPEP § 2181 applies 35 U.S.C. 112(f) when (1) a claim uses "means," "step," or a generic placeholder/nonce term as a substitute for "means," (2) the term is modified by functional language, and (3) the term is not modified by sufficient structure, material, or acts for performing the claimed function. Here, the term "module" is a generic black-box placeholder and the recited modifiers merely state the functions to be performed noise spectrum determination, second-spectrum acquisition, filter determination, received-signal acquisition, and filtering without reciting circuitry or other sufficiently definite structure.
Accordingly, the above functional module limitations satisfy the three-prong analysis and are construed under 35 U.S.C. 112(f).
The specification provides corresponding structure and acts for these computer-implemented functions.
Paragraphs [0131] and [0137]-[0138] disclose that the modules may be implemented in hardware or as software stored in memory and executed by a processor/computer, while the detailed method embodiments associated with FIGS. 1-6 disclose the algorithms performed, including sampling and spectrum acquisition, power-spectrum estimation, spectral subtraction, difference/sum/ratio calculations for the Wiener response, spectral decomposition, and filtering.
Thus, the corresponding structure is the disclosed processor/computer and/or dedicated hardware programmed or configured to execute the disclosed algorithms, and equivalents thereof.
No separate rejection is made for failure to disclose corresponding structure or acts for the above 35 U.S.C. 112(f) limitations.
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.
Claim 10 is 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, or for pre-AIA the applicant regards as the invention.
Regarding claim 10,
Claim 10 recites "a first spectrum acquisition module" and then recites "a noise spectrum determination module, configured to determine a noise spectrum of the first test signal according to the first signal spectrum and the first power spectrum." However, claim 10 does not previously introduce "the first test signal," "the first signal spectrum," or "the first power spectrum," and the recited first spectrum acquisition module is not expressly configured to acquire any of those recited spectra.
As written, it is unclear whether the first spectrum acquisition module is required to acquire both the first signal spectrum and the first power spectrum later used by the noise spectrum determination module, whether those spectra are supplied by some other unspecified component, and what first test signal the recited spectra correspond to.
The omission is substantive because the claim does not state the functional relationship between the first spectrum acquisition module and the first signal spectrum and first power spectrum upon which the subsequently recited noise spectrum determination module expressly operates.
The intrinsic disclosure confirms that a material limitation appears to be missing from claim 10.
Paragraph [0020] and paragraph [0121] expressly describe a first spectrum acquisition module configured to acquire a first signal spectrum and a first power spectrum corresponding to a first test signal, wherein the first test signal is an optical signal after the signal transmitting end modulates first test data and transmits the first test data through the optical fiber.
FIG. 9 likewise identifies first spectrum acquisition module 902. Although the specification appears to disclose the intended relationship, limitations from the specification cannot be imported into claim 10 to supply claim language that is absent from the claim.
As written, the claim does not provide reasonably certain boundaries as to the required relationship among the first spectrum acquisition module, the first test signal, the first signal spectrum, and the first power spectrum.
Accordingly, the metes and bounds of claim 10 are not reasonably certain, and claim 10 is indefinite under 35 U.S.C. 112(b).
Claim Rejections - 35 U.S.C. § 101
The following is a quotation of 35 U.S.C. 101:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to nonstatutory subject matter that does not fall within one of the four statutory categories of process, machine, manufacture, or composition of matter.
Regarding claim 15,
Claim 15 recites a “computer program product, including a computer program,” wherein the computer program implements the steps of the method of claim 1 when executed by a processor.
As presently drafted, claim 15 does not recite a computer-readable storage medium, a memory, a processor as part of the claimed product, a physical article, or another tangible structure in which the computer program is embodied. Rather, the claimed product is defined by the computer program itself and by the function that the program performs when it is later executed by a processor.
MPEP § 2106.03 explains that the machine, manufacture, and composition-of-matter categories require a physical or tangible product, and specifically identifies a computer program per se claimed as a product without structural recitations as outside the statutory categories. The MPEP states:
“Products that do not have a physical or tangible form, such as information (often referred to as “data per se”) or a computer program per se (often referred to as “software per se”) when claimed as a product without any structural recitations;” [MPEP § 2106.03(I), Eligibility Step 1: The Four Categories of Statutory Subject Matter].
MPEP § 2106.03 further explains that software expressed as code or a set of instructions detached from any medium lacks physical embodiment, and that a product claim to a software program that does not contain at least one structural limitation has no physical or tangible form and therefore does not fall within any statutory category. See Microsoft Corp. v. AT&T Corp., 550 U.S. 437, 449 (2007); Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1348-50 (Fed. Cir. 2014); In re Ferguson, 558 F.3d 1359, 1364 (Fed. Cir. 2009).
The phrase “when executed by a processor” does not supply structure to the claimed “computer program product.” It merely defines what the intangible program is capable of doing if a processor later executes it.
The processor is not recited as a component of the claimed product, and claim 15 therefore remains directed to software per se rather than to a statutory machine or manufacture.
This is distinct from claim 14, which expressly recites a “computer-readable storage medium” on which a program is stored. Accordingly, under the broadest reasonable interpretation, claim 15 is directed to a computer program per se without a structural recitation establishing a physical or tangible form.
Claim 15 therefore does not fall within any of the four statutory categories and is rejected under 35 U.S.C. 101.
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.
The key to supporting a rejection under 35 U.S.C. § 103 is a clear articulation of the reason or reasons why the claimed invention would have been obvious, with an articulated reasoning having a rational underpinning.
The analysis below identifies the teachings relied upon for each limitation and states a claim-specific reason for the proposed combination.
This application names a single inventor, Ning Cheng. Except where otherwise indicated, the applied references below were publicly available before the July 12, 2022 foreign priority date presently claimed and are relied upon under 35 U.S.C. 102(a)(1). Kim et al. (US 11,742,947 B1), relied upon below in the rejection of claims 5-7, is a U.S. patent naming a different inventive entity and was filed on March 9, 2022, before the presently claimed July 12, 2022 effective filing date; Kim is therefore relied upon under 35 U.S.C. 102(a)(2), subject to any applicable exception under 35 U.S.C. 102(b)(2).
Claims 1-4 are rejected under 35 U.S.C. § 103 as being unpatentable over Gariepy et al. (US 2012/0201533 A1) in view of Qi et al. (CN 112583478 A), further in view of He et al. (CN 106100751 A), Shirai et al. (JP 2010-278753 A), and Arslan et al. (US 6,263,307 B1).
Claim 1
Gariepy expressly teaches optical spectral acquisition and mathematical separation of a signal contribution from a noise contribution on an optical communication link.
“In step 402, an optical spectrum trace P(ω) of the SUT to be characterized is obtained... Trace P(ω) comprises a data-carrying signal contribution S(ω) ... and a noise contribution N(ω) within the optical signal bandwidth of the SUT.” [Gariepy, ¶ [0051]].
“In step 404, a reference optical spectrum trace R(ω) is obtained. The reference signal has a signal contribution ... representative of the shape Sh(ω) of the signal contribution S(ω) of the SUT, and has a noise contribution ... which is at least approximately known over the optical signal bandwidth.” [Gariepy, ¶ [0052]].
“In steps 406, 408 and 410, the signal contribution S(ω) and the noise contribution N(ω) of the SUT are mathematically discriminated from one another over the optical signal bandwidth using a mathematical comparison of traces R(ω) and P(ω).” [Gariepy, ¶ [0052]].
“In step 410, the noise contribution N(ω) of the SUT is calculated using the ratio K, for example as follows: N(ω)=P(ω)-KSh(ω).” [Gariepy, ¶ [0057]].
Thus, Gariepy teaches acquiring a measured optical signal spectrum containing both signal and noise, obtaining a corresponding signal-only spectral representation from a reference signal, and determining the noise spectrum by subtracting the estimated signal contribution from the measured optical spectrum. Gariepy does not, by itself, expressly teach the claimed first/second optical-test-signal sequence, the requirement that the second test-data period exceed the first, or use of the resulting spectra to implement the frequency response of a Wiener filter in a PAM optical receiver.
Within analogous optical-receiver test art, Qi expressly teaches using distinct first and second optical test signals and measuring corresponding output/signal power spectra at an optical receiver.
“a first signal generating part 111, which generates a first test signal with at least one notch ... [and] the first power measuring part 113 ... measuring the output power spectrum of the coherent light receiver; and a second determining unit 114 ... determining ... nonlinear noise power.” [Qi, p. 5].
“a second signal generating unit 130, which generates a second test signal ... [and] the second power measuring part 140 ... [uses] the second test signal ... to obtain the coherent light receiver signal power spectrum.” [Qi, pp. 7-8].
Qi therefore supplies an express two-test-signal optical-receiver characterization architecture and separate spectrum acquisition for the first and second test signals. In combination with Gariepy’s optical spectral discrimination, the first-test measurement provides the measured spectrum and corresponding signal contribution from which noise is isolated, while the second-test measurement provides the separately acquired signal spectrum used in the later filter-response calculation.
Further, within the same optical-communication field, He expressly teaches a Wiener-filter implementation in a high-speed PAM4 optical-fiber link using a training signal and a receiver-side Wiener filter.
“The invention claims a Wiener filtering method for high-speed light pulse amplitude modulation, the Mach-Zehnder modulator PAM4 for modulating the electric signal back to the 1.5 microns laser through single-mode optical fibre transmission, and to realize signal demodulation at the receiving end through interpolation reconstruction and Wiener filtering.” [He, p. 2].
“The Wiener filter whose filter parameters [are obtained] by calculating inverse matrix multiplication of the receiving end receives the signal obtained after interpolation and resampling of the digital signal and the training signal cross correlation matrix between the pulse sequences of the autocorrelation matrix...” [He, p. 2; see also claim 1, p. 4].
He therefore supplies the expressly optical PAM environment missing from Gariepy: test/training data are modulated onto an optical carrier, transmitted through single-mode optical fiber, received, sampled, and Wiener-filtered.
He also demonstrates that determining Wiener-filter parameters from received/training signals in a PAM4 optical link was known before the effective filing date.
Further, Shirai expressly teaches optical-receiver testing with periodic pseudo-random test patterns of different sequence lengths, including the exact short/long PRBS relationship disclosed as exemplary in the present application.
“As a test pattern for the optical receiver, PRBS7 is used for GE-PON and PRBS31 is used for 10GE-PON. The features of the PRBS31 code are that the code continuation becomes longer...” [Shirai, p. 2].
A PRBS31 sequence has a substantially greater sequence period than a PRBS7 sequence. Shirai therefore established that, in optical-receiver testing, selecting a first relatively short periodic PRBS test sequence and a second longer periodic PRBS test sequence was a known test-pattern choice, not a newly discovered type of optical test data.
Finally, Arslan expressly teaches the conventional frequency-domain relationship used to determine the frequency response of a Wiener filter from signal and noise power spectra.
“The Lim and Oppenheim article also describes an alternative noise suppression approach using noncausal Wiener filtering which minimizes the mean-square error... H(ω)=Ps(ω)/[Ps(ω)+Pn(ω)] ... This Wiener filter generalizes to: H(ω)=[Ps(ω)/(Ps(ω)+αPn(ω))]β.” [Arslan, col. 4, ll. 19-31].
When C=1, the conventional Wiener response is the desired-signal power divided by the sum of desired-signal power and noise power.
Equivalently, where the measured spectrum represents signal-plus-noise and the noise spectrum is known, the desired-signal component is the difference between the measured spectrum and the noise spectrum and the Wiener response is determined from those quantities.
One of ordinary skill in the art would have been motivated to combine Gariepy with Qi because both are directed to spectral characterization of optical communication/receiver signals. Gariepy provides a known mathematical technique for separating an optical signal contribution from its noise contribution, while Qi provides a known first/second-test-signal measurement architecture in which separate optical test signals are generated and corresponding output/signal power spectra are measured. Applying Gariepy’s spectral discrimination to Qi’s first-test measurement, and retaining Qi’s separate second-test spectrum, would predictably provide the two spectrum data sets needed for subsequent filter design without changing the operating principle of either reference.
One of ordinary skill in the art would further have been motivated to implement the combined Gariepy/Qi measurement architecture in He’s known PAM4 single-mode-fiber Wiener-filter receiver because He already determines Wiener-filter parameters from received/training signals in precisely the optical PAM environment of the claim. The combination would use measured optical signal/noise spectra, rather than an assumed noise model, as the information from which the Wiener response is determined, yielding the predictable benefit of adapting the MMSE filter to the actual received link conditions. One of ordinary skill would also have had a reasonable expectation of success because each reference operates on receiver-side sampled/spectral representations of communication signals and the combination changes the source of the filter-design data, not the underlying transmitter, fiber, or receiver architecture.
One of ordinary skill in the art would further have been motivated to use Shirai’s known PRBS7 and PRBS31 optical-receiver test patterns as the respective first and second test data because those are established periodic optical-receiver test sequences with different sequence lengths; PRBS31 necessarily has a period greater than PRBS7. Selecting the longer-period PRBS31 for the second measurement would have been a predictable test-design choice to obtain a different, denser periodic spectral sampling than the shorter first sequence while using conventional optical test data. Finally, Arslan’s Wiener-transfer-function equations are reasonably pertinent analogous art even though Arslan addresses speech, because the particular problem for which Arslan is cited computing an MMSE Wiener response from desired-signal and noise power spectra is a medium-independent signal-processing problem. An optical DSP engineer seeking to calculate the Wiener response from the spectra supplied by Gariepy/Qi/He would logically have consulted and applied this conventional Wiener relationship. The combination therefore uses known optical spectrum measurement, known two-signal optical receiver testing, known PAM4 fiber Wiener filtering, known optical PRBS test patterns, and a known Wiener spectral transfer function according to their established functions.
Accordingly, the combined teachings render obvious every limitation of claim 1: Gariepy teaches measured optical signal/noise spectral separation; Qi teaches distinct first and second optical test signals and spectrum measurements; He teaches modulation/training data transmitted through single-mode optical fiber and receiver-side Wiener filtering in a PAM4 system; Shirai teaches optical-receiver PRBS7/PRBS31 test patterns establishing a longer-period
second test sequence; and Arslan teaches determining the Wiener frequency response from desired-signal and noise power spectra.
Claim 2
With respect to claim 2, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, and Arslan as set forth with respect to claim 1, except wherein claim 2 additionally expressly requires acquiring a first difference between the second signal spectrum and the noise spectrum of the first test signal, acquiring a sum between that first difference and the noise spectrum, and determining the Wiener-filter frequency response according to the first difference and the sum. However, within reasonably pertinent signal-processing art, Arslan expressly teaches these additional mathematical relationships.
“If speech were also a stationary process ... the power spectral densities would add due to the lack of correlation... The power spectral density Pn(ω) of the noise signal can be estimated by detection during noise-only periods, so the speech power spectral estimate becomes |S*(ω)|²=|Y(ω)|²-|N(ω)|²=Py(ω)-Pn(ω), which is the spectral subtraction.” [Arslan, col. 3, ll. 18-65; col. 4, ll. 1-6].
“The Lim and Oppenheim article also describes ... Wiener filtering which minimizes the mean-square error... H(ω)=Ps(ω)/[Ps(ω)+Pn(ω)].” [Arslan, col. 4, ll. 19-31].
Under Arslan’s conventional signal-plus-noise model, subtracting the known noise spectrum from the measured second spectrum produces the desired-signal spectrum, i.e., the claimed “first difference.” Adding that desired-signal spectrum back to the noise spectrum reconstructs
the total signal-plus-noise spectrum, i.e., the claimed “sum.” The Wiener response is then determined from the desired-signal component and the signal-plus-noise sum.
One of ordinary skill in the art would have been motivated to perform these straightforward spectral arithmetic operations in the combined optical system because Gariepy already separates measured optical signal and noise contributions by spectral subtraction, while Arslan expressly uses the resulting desired-signal and noise powers to define the Wiener transfer function. The claimed sequence therefore amounts to applying the standard Wiener power-spectrum relationship to the optical spectra already obtained by the claim-1 combination, with the predictable result of an MMSE Wiener response.
Claim 3
With respect to claim 3, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, and Arslan as set forth with respect to claim 2, except wherein claim 3 additionally expressly requires determining a ratio of the first difference to the sum as the frequency response of the Wiener filter. However, within analogous art, Arslan expressly teaches the ratio form of the Wiener transfer function.
“H(ω)=Ps(ω)/[Ps(ω)+Pn(ω)].” [Arslan, col. 4, ll. 19-31].
For the conventional case C=1, the numerator Ps(ω) is the desired-signal spectrum obtained by subtracting the noise spectrum from the measured spectrum, and the denominator Ps(ω)+Pn(ω) is the sum of the desired-signal and noise spectra. This is the same ratio recited in claim 3.
One of ordinary skill in the art would have been motivated to use this ratio because it is the conventional closed-form Wiener frequency response for minimum-mean-square-error suppression.
Once the first difference and the sum of claim 2 have been calculated, forming their ratio is not an independent inventive step; it is the known Wiener transfer-function calculation expressly taught by Arslan and would have predictably yielded the claimed response.
Claim 4
With respect to claim 4, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, and Arslan as set forth with respect to claim 1, except wherein claim 4 additionally expressly requires acquiring a second difference between the first signal spectrum and the first power spectrum and using the second difference as the noise spectrum of the first test signal. However, within analogous optical measurement art, Gariepy expressly teaches the additional limitation.
“In step 410, the noise contribution N(ω) of the SUT is calculated using the ratio K, for example as follows: N(ω)=P(ω)-KSh(ω).” [Gariepy, ¶ [0057]].
Gariepy’s P(ω) is the measured optical signal spectrum containing both the data-carrying signal and noise, while KSh(ω) is the estimated corresponding signal contribution. The difference is expressly used as the noise spectrum. Under the broadest reasonable interpretation, this teaches the claimed first-signal-spectrum minus first-power-spectrum operation.
One of ordinary skill in the art would have been motivated to use Gariepy’s subtraction in the combined optical Wiener system because the resulting noise spectrum is exactly the quantity needed by the Wiener response taught by Arslan and because subtracting the known/estimated noise-free spectral component from the measured spectrum is a direct, predictable way to isolate the noise present on the optical link.
Claim 4 therefore would have been obvious.
Claims 5-7 are rejected under 35 U.S.C. § 103 as being unpatentable over Gariepy et al. in view of Qi et al., He et al., Shirai et al., and Arslan et al., and further in view of Smith et al. (US 2017/0230119 A1), Anderson (US 5,929,982), and Kim et al. (US 11,742,947 B1).
Claim 5
With respect to claim 5, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, and Arslan as set forth with respect to claim 1, except wherein claim 5 additionally expressly requires acquiring a received-noise spectrum that characterizes noise of the signal receiving end itself and determining an MPI-noise spectrum according to the first-test-signal noise spectrum and the received-noise spectrum. However, within analogous optical-communication/measurement art, Smith, Anderson, and Kim teach the additional receiver-noise baseline and component-separation concepts.
“A noise contribution nk is added at 404 to produce a received sample rk... In addition, yk, rk, and the MPI interference component can be modelled... [and] the additive noise nk models other sources of noise in the channel.” [Smith, ¶¶ [0022]-[0029]].
Smith therefore expressly models MPI as an interference component distinct from other additive receiver/channel noise. This establishes the physical decomposition underlying claim 5: total received impairment includes an MPI component plus a non-MPI noise component.
“The controller ... receives the output of the optical receiver and determines the system noise of the receiver for the various bias control values.” [Anderson, Abstract].
“The important thing to remember about the noise floor used in determining OTDR dynamic range is that it is defined past the end of the fiber under test, where there is no optical signal in the APD. Consequently, the dynamic range of the OTDR is a function of the backscatter level and the dark system noise of the OTDR’s optical receiver.” [Anderson, col. 8, ll. 37-50].
Anderson thus teaches separately characterizing the optical receiver’s own system/dark noise independently of an incoming optical signal. Arslan additionally teaches representing a noise-only measurement as a power spectral density. Together, these teachings provide the claimed received-noise spectrum representing the receiving end itself.
Kim independently reinforces the use of a no-signal baseline and subtraction of measured optical noise levels. Kim teaches that “the first noise level may be measured when no optical signal is being transmitted along the frequency channel” and that “the intra-channel noise level may be a difference between the first noise level and the second noise level.” [Kim, US 11,742,947 B1, cols. 4-9].
Kim is relied upon for the known optical-noise calibration/difference technique, while Smith supplies the MPI-specific optical context and Anderson supplies receiver-intrinsic noise. The combined teachings therefore provide a direct evidentiary basis for separately measuring a receiver/noise baseline and removing that baseline from a total measured impairment to isolate the remaining optical interference component.
One of ordinary skill in the art would have been motivated to combine Smith, Anderson, and Kim with the claim-1 optical spectrum/Wiener system because Smith expressly identifies MPI and other additive noise as distinct contributions at the optical receiver, Anderson provides a known no-optical-input technique for measuring the receiver’s own system/dark noise, and Kim demonstrates the known optical practice of measuring a no-signal baseline and determining an additional noise component by difference. Separately measuring the receiver-generated noise in the same frequency-domain framework prevents that receiver noise from being incorrectly attributed to optical-link MPI and predictably improves the accuracy of the MPI estimate.
Once the total noise spectrum of the first test signal is available from Gariepy/Arslan and the receiver-only noise spectrum is measured according to Anderson and represented spectrally, one of ordinary skill would have determined the remaining MPI spectrum from those two quantities because Smith expressly treats MPI and other additive noise as separate received components and Kim teaches extracting an additional optical-noise contribution from a measured baseline by subtraction. The result is a predictable component-separation calculation, not a change in the principle of operation.
Claim 6
With respect to claim 6, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, Arslan, Smith, Anderson, and Kim as set forth with respect to claim 5, except wherein claim 6 additionally expressly requires acquiring a second power spectrum corresponding to a detection signal, using that second power spectrum as the received-noise spectrum, and defining the detection signal as noise generated by the signal receiving end when no optical signal is input. However, within analogous optical-receiver and signal-processing art, Anderson, Kim, and Arslan expressly teach the additional limitations.
“measuring a system noise level of the optical receiver for each bias control value using the receiver output with the output being generated without an optical signal being present on the avalanche photo-diode.” [Anderson, claim 10; see also col. 7, ll. 33-41].
“the first noise level may be measured when no optical signal is being transmitted along the frequency channel.” [Kim, cols. 4-9].
“The power spectral density Pn(ω) of the noise signal can be estimated by detection during noise-only periods...” [Arslan, col. 4, ll. 1-6].
Anderson supplies the precise no-optical-input receiver condition recited in claim 6 and identifies the resulting output as receiver system noise. Kim independently confirms no-optical-signal baseline measurement in an optical network, and Arslan supplies the conventional representation of noise-only data as a power spectral density. Under the broadest reasonable interpretation, acquiring the power spectrum/PSD of the receiver output under the no-optical-input condition provides the claimed second power spectrum and using that spectrum as the receiver-noise spectrum is the direct spectral representation of the measured receiver noise.
One of ordinary skill in the art would have been motivated to make the receiver-noise measurement under a no-optical-input condition because doing so removes signal-dependent and link-dependent optical contributions and leaves the intrinsic receiver noise to be calibrated. The artisan would have represented that measured noise in the same spectral domain as the total signal/noise spectrum because the subsequent Wiener and spectral-subtraction operations are frequency-domain operations.
Using the noise-only power spectrum as the receiver-noise spectrum would therefore have been an obvious and predictable implementation.
Claim 7
With respect to claim 7, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, Arslan, Smith, Anderson, and Kim as set forth with respect to claim 5, except wherein claim 7 additionally expressly requires acquiring a third difference between the noise spectrum of the first test signal and the received-noise spectrum and using that third difference as the MPI-noise spectrum. However, within analogous optical-communication art, Smith and Kim, together with Arslan’s spectral-subtraction teaching, make this additional limitation explicit and predictable.
“A noise contribution nk is added ... [and] the MPI interference component can be modelled... [while] the additive noise nk models other sources of noise in the channel.” [Smith, ¶¶ [0022]-[0029]].
“At block 410, an intra-channel noise level may be determined. The intra-channel noise level may be a difference between the first noise level and the second noise level.” [Kim, col. 9].
Because Smith separates MPI from other additive noise in the received optical signal, the total first-test noise spectrum can be treated as comprising an MPI component plus a receiver/additive-noise component.
Anderson supplies the independently measured receiver-noise baseline, and Kim expressly teaches determining an additional optical noise component as the difference between two measured noise levels.
Applying the same known difference operation in the frequency domain gives MPI spectrum = total first-test noise spectrum - receiver-noise spectrum, which is the claimed third difference.
One of ordinary skill in the art would have been motivated to perform this subtraction because the express objective of the combined system is to isolate the impairment attributable to the optical multipath path rather than the receiver itself.
Subtracting an independently calibrated receiver-noise spectrum from the measured total noise spectrum is the direct mathematical inverse of the additive-component model taught by Smith and is reinforced by Kim’s optical-noise difference measurement. The operation would predictably leave the MPI component and therefore would have rendered claim 7 obvious.
Claims 8 and 10-12 are rejected under 35 U.S.C. § 103 as being unpatentable over Gariepy et al. in view of Qi et al., He et al., Shirai et al., and Arslan et al., and further in view of Smith et al.
Claim 8
Claim 8 recites a method for suppressing multipath interference noise at the receiving end of an optical communication system by acquiring a received signal, filtering the received signal according to the frequency response of the Wiener filter to obtain a filtered target signal, and implementing the Wiener-filter frequency response according to claim 1. The claim-1 frequency-response implementation is taught by Gariepy, Qi, He, Shirai, and Arslan for the reasons set forth above. Smith expressly teaches receiver-side MPI mitigation of a received PAM optical signal.
“A circuit and method for mitigating multi-path interference in direct detection optical systems is provided. Samples of an optical signal having a pulse amplitude modulated (PAM) E-field are processed... The error samples are lowpass filtered to produce estimates of multi-path interference (MPI). For each sample, one of the estimates of MPI is combined with the sample to produce an interference-mitigated sample.” [Smith, Abstract].
“for each sample, combining one of the estimates of MPI with the sample to produce an interference-mitigated sample.” [Smith, claim 1].
Smith therefore teaches acquiring a received PAM optical signal and filtering/processing it at the receiver to obtain an MPI-mitigated target signal. He independently teaches receiver-side Wiener filtering of a PAM4 signal after optical-fiber transmission. The only distinction is that Smith uses an MPI-estimation filter rather than the specific Wiener response of claim 1.
One of ordinary skill in the art would have been motivated to use the claim-1 Wiener frequency response in Smith’s receiver-side MPI suppression path because both filters are directed to reducing noise/interference in a direct-detection optical PAM receiver. The claim-1 combination supplies a Wiener response based on measured signal/noise spectra, while Smith supplies the receiver-side MPI suppression architecture and objective. Substituting the known MMSE Wiener response for the known receiver interference filter would have been a predictable use of a known filter according to its established function, with the expected result of suppressing the measured MPI/noise component and producing a filtered target signal.
Claim 10
For purposes of the prior-art rejection only, and without withdrawing the 35 U.S.C. 112(b) rejection of claim 10, claim 10 is interpreted consistently with the specification as requiring the “first spectrum acquisition module” to acquire the first signal spectrum and first power spectrum corresponding to the first test signal.
Under that interpretation, the functional limitations of claim 10 are the apparatus counterparts of the steps of claim 1. Consistent with the 35 U.S.C. 112(f) construction above, the relevant corresponding structure is a processor/computer or dedicated hardware executing the
disclosed spectrum-acquisition, noise-determination, and Wiener-response algorithms, and equivalents thereof.
Gariepy teaches the optical spectrum measurement and signal/noise discrimination operations; Qi teaches first- and second-test-signal generation, first/second power-measuring parts, determining parts, and a processing device that may be implemented by a computer or by the DSP of the coherent optical receiver; He teaches a receiving module that performs photoelectric conversion, interpolation, resampling, and Wiener filtering; Arslan teaches the Wiener transfer-function calculation; and Shirai supplies the different-period optical test patterns.
“the nonlinear characteristic test device 100 ... include[s] ... a second signal generating unit 130 ... [and] the second power measuring part 140 ... [and] calculating part 150...” and “the function of the processing device 940 may be ... computer execution [or] ... digital signal processor (DSP) of the receiver.” [Qi, pp. 7 and 9 (English translation)].
“In step 402, an optical spectrum trace P(ω) ... is obtained... In step 404, a reference optical spectrum trace R(ω) is obtained... [and] the signal contribution S(ω) and the noise contribution N(ω) ... are mathematically discriminated from one another...” [Gariepy, ¶¶ [0051]-[0052]].
It would have been obvious to implement the known acquisition, noise-determination, second-spectrum-acquisition, and Wiener-response-determination operations using the processor/DSP and measurement structures taught by Qi and He because those structures perform the same algorithmic functions as the corresponding structures disclosed in the present specification.
Under 35 U.S.C. 112(f), Qi’s processing device/DSP and He’s receiver processing module are, at minimum, structural equivalents for performing the same spectrum-processing and Wiener-filter operations. Combining those known structures with Gariepy’s and Arslan’s known algorithms would have yielded the predictable device of claim 10.
Claim 11
Claim 11 is directed to a device counterpart of claim 8. The claim-1 Wiener-filter frequency response is taught by the base combination, while Smith expressly teaches receiver-side structures corresponding to a received-signal acquisition path and an MPI filtering/mitigation module.
“Referring now to FIG. 5A, shown is a block diagram of an optical receiver including a MPI mitigation circuit 500... Block RX1 501 represents any input signal processing that is performed prior to the MPI mitigation circuit 500... Block RX2 510 represents receive signal processing that is performed after the MPI mitigation circuit 500.” [Smith, ¶ [0033]].
“a circuit for processing a plurality of samples of an optical signal having a pulse amplitude modulated (PAM) E-field... [including] a low-pass filter that filters the error samples to produce estimates of multi-path interference (MPI); [and] a combiner that ... combines one of the estimates of MPI with the sample to produce an interference-mitigated sample.” [Smith, ¶ [0019]].
Smith’s RX1 input-processing path and explicit MPI mitigation circuit 500 including error generator 506, low-pass filter 508, compensation combiner 504, and the associated receiver hardware provide definite receiver-side structure for acquiring/processing the received signal and filtering it to produce an interference-mitigated output. Those structures perform the same claimed functions and constitute structural equivalents under the 35 U.S.C. 112(f) construction above.
One of ordinary skill would have been motivated to configure that filtering module to use the claim-1 Wiener response for the same reasons discussed for claim 8: the known Wiener response is an MMSE filter directed to suppression of measured noise/interference, and substituting it for the known receiver-side MPI mitigation filter predictably produces the filtered target signal. Claim 11 therefore would have been obvious.
Claim 12
Claim 12 recites an optical communication system having a signal transmitting end that modulates transmission data to generate an optical signal, an optical fiber that transmits the optical signal, and a signal receiving end that receives and filters the optical signal using the Wiener response of claim 1. He expressly teaches this system architecture.
“The invention claims a Wiener filtering method for high-speed light pulse amplitude modulation, the Mach-Zehnder modulator PAM4 for modulating the electric signal back to the 1.5 microns laser through single-mode optical fibre transmission, and to realize signal
demodulation at the receiving end through interpolation reconstruction and Wiener filtering.” [He, p. 2].
“the device comprises a Mach-Zehnder modulator and carrier ... for transmitting the modulated signal of the single mode optical fibre and a signal receiving end of a photoelectric detector.” [He, claim 5, p. 4].
Smith additionally shows a transmitter connected to a receiver through optical cables/connectors and receiver-side MPI mitigation.
Thus, the transmitter, optical-fiber path, receiver, and receiver-side filtering limitations are all taught in the same field.
The claim-1 combination supplies the particular Wiener response used by the receiver.
One of ordinary skill would have been motivated to configure He’s known PAM4 transmitter/fiber/receiver system to calculate and use the claim-1 response because He already uses a Wiener filter at that receiver; the modification merely supplies a known measured-spectrum technique for determining the filter response and predictably improves adaptation to the actual noise environment.
Claim 9 is rejected under 35 U.S.C. § 103 as being unpatentable over Gariepy et al. in view of Qi et al., He et al., Shirai et al., Arslan et al., and Smith et al., as applied to claim 8, and further in view of Ephremides et al. (WO 2009/134444 A1).
Claim 9
With respect to claim 9, all the claim limitations of the invention are taught by Gariepy, Qi, He, Shirai, Arslan, and Smith as set forth with respect to claim 8, except wherein claim 9 additionally expressly requires performing spectral decomposition on the Wiener-filter frequency response to acquire the frequency response of a causal Wiener filter and filtering the received signal according to the causal Wiener-filter response. However, within analogous filter-design art, Ephremides expressly teaches causal Wiener filtering implemented through spectral factorization.
“Wiener filtering is based on a statistical approach... Wiener filters are characterized by the following: ... 2. The filter may be physically realizable, i.e. causal; 3. Performance criterion: minimum mean-square error (MMSE).” [Ephremides, ¶¶ [0048]-[0051]].
“The estimated ‘message’ is obtained by passing yi through a causal LTI filter K ... The coefficients ... are assumed to be 0 for negative j since the filter is causal.” Ephremides then explains that, “In order to construct the Wiener filter ... [the method] performs a spectral factorization.” [Ephremides, ¶¶ [0052]-[0054]].
Ephremides therefore teaches the precise relationship underlying claim 9: a Wiener filter intended for real-time/physical implementation is made causal, and spectral factorization is used in constructing the causal Wiener filter.
The reference also expressly teaches receiving a signal, performing Wiener filtering, and providing a real-time output.
One of ordinary skill in the art would have been motivated to apply Ephremides’s causal spectral-factorization technique to the Wiener response of claim 8 because a receiver filter intended for real-time physical implementation must be causal.
Ephremides is reasonably pertinent analogous art to the specific problem of converting Wiener/MMSE spectral information into a physically realizable causal filter, regardless of the underlying communication medium.
Applying that known causal realization technique to the Wiener response used in Smith/He’s real-time optical receiver would have predictably produced a causal Wiener response suitable for actual filtering while preserving the MMSE objective.
Applying that technique in Smith/He’s real-time optical receiver would have predictably produced a causal Wiener response suitable for actual filtering, exactly as recited in claim 9.
Claims 13-15 are rejected under 35 U.S.C. § 103 as being unpatentable over Gariepy et al. in view of Qi et al., He et al., Shirai et al., and Arslan et al., as applied to claim 1, and further in view of Huang et al. (US 2020/0067595 A1).
Claim 13
Claim 13 recites a computer device including a memory and processor, the memory storing a computer program, with the processor executing the program to implement the steps of claim 1. The substantive claim-1 method is taught by Gariepy, Qi, He, Shirai, and Arslan as discussed above. Huang expressly teaches the conventional processor/memory computer implementation of optical MPI-detection methods.
“the terminal apparatus 1000 includes a processor 1010 and a transceiver 1020... [and] further includes a memory 1030 connected to the processor 1010... The memory 1030 may be configured to store an instruction. The processor 1010 is configured to execute the instruction stored in the memory 1030...” [Huang, ¶ [0184]].
“A software module may be located in a ... storage medium ... The storage medium is located in the memory, and a processor reads information in the memory and completes the steps in the foregoing methods in combination with hardware of the processor.” [Huang, ¶ [0187]].
One of ordinary skill in the art would have been motivated to implement the spectral acquisition, subtraction, and Wiener-response calculations of claim 1 in the known processor/memory architecture of Huang because those operations are digital signal-processing calculations and He already performs interpolation, resampling, and Wiener filtering at the optical receiver.
A processor executing stored instructions is a conventional and predictable implementation of such numerical algorithms. Claim 13 therefore would have been obvious.
Claim 14
Claim 14 recites a computer-readable storage medium storing a computer program that implements the steps of claim 1 when executed by a processor. The substantive method is taught by the claim-1 combination.
Huang expressly teaches the storage-medium implementation.
“According to a fifth aspect, a computer readable medium is provided, and where the computer readable medium stores a computer program, and the computer program is executed by a computer to implement the method in the first aspect or any one of the possible implementations of the first aspect.” [Huang, ¶ [0070]].
One of ordinary skill in the art would have been motivated to store the program instructions for the claim-1 signal-processing method on a computer-readable storage medium because Huang expressly uses that conventional implementation for optical MPI processing and because software-based storage permits deployment, updating, and execution of the same receiver DSP algorithm on known processor hardware.
The implementation changes only the form in which the known algorithm is stored, not its operation or result.
Claim 14 therefore would have been obvious.
Claim 15
Claim 15 recites a computer program product including a computer program that implements the steps of claim 1 when executed by a processor. The substantive method is taught by the claim-1 combination.
Huang expressly teaches a computer program product implementation in substantially the same terms.
“According to a sixth aspect, a computer program product is provided, where the computer program product is executed by a computer to implement the method in the first aspect or any one of the possible implementations of the first aspect.” [Huang, ¶ [0071]].
One of ordinary skill in the art would have been motivated to embody the claim-1 processing steps as a computer program product because the spectral calculations and Wiener-filter determination are software-suitable DSP operations and Huang expressly recognizes a computer program product as a routine vehicle for implementing optical MPI methods.
The modification would have been no more than the predictable software implementation of the already obvious method.
Accordingly, claim 15 would have been obvious over the cited combination, independently of the separate 35 U.S.C. 101 rejection set forth above.
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
/DAVID C PAYNE/Supervisory Patent Examiner, Art Unit 2635
