Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. It would be of great assistance to the office if all incoming papers pertaining to a filed application carried the following items:
i. Application number (checked for accuracy, including series code and serial no.).
ii. Group art unit number (copied from most recent Office communication).
iii. Filing date.
iv. Name of the examiner who prepared the most recent Office action.
v. Title of invention.
vi. Confirmation number (See MPEP § 503).
Response to Arguments
3. Applicant's arguments with respect to claims have been considered but are moot in view of the new ground(s) of rejection.
4. The Examiner has pointed out particular references contained in the prior art of record within the body of this action for the convenience of the Applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages, paragraph and figures may apply. Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
5. Claim interpretation: When multiple limitations are connected with “OR”, one of the limitations doesn’t have any patentable weight since both of the limitations are optional.
Claim Rejection- 35 USC § 103
6. The following is a quotation of 35 U.S.C. 103 which forms the basis for all 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 of this title, 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.
Claims 1-2, 5-7, 12-13, 17 & 20-21 are rejected under 35 U.S.C. 103 as being unpatentable over Shima (Pub No. 2018/0324595) and further in view of Govea et al (Pub No. 2020/0327397).
Regarding claim 1, Shima discloses a method of identifying one or more unused or underused portions of a wireless radio frequency (RF) spectrum (Para. 35 & 92: Identifying unused/ underused portions of RF spectrum), the method comprising the steps of: providing a multi-label multi-class machine learning classifier trained using a set of RF transmission data (Para. 35-38 & 92-93: Deep neural network/ cognitive radio for configuring and train RF signals); receiving, by a receiver, wireless RF signals in an environment suspected of containing unused or underused portions of said RF spectrum (Para. 7-8: Receive RF signals in an environment containing unused or underused spectrum) & (Para. 92 & 107-108); and identifying unused or underused portions of said RF spectrum (Para. 7-8 & 92: selecting unused frequencies).
Shima also does not explicitly disclose providing unprocessed I/Q samples of the received wireless RF signals as input to the classifier to cause the classifier to classify the received wireless RF signals.
Govea et al discloses providing unprocessed I/Q samples of the received wireless RF signals as input to the classifier to cause the classifier to classify the received wireless RF signals (Para. 54: Classify signals & Para. 72: Classify when using raw IQ data & Para. 89).
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the invention to use the radio signal classification system of Govea’s disclosure with the spectral sensing and allocation using deep learning, as taught by Shima. Doing so would have resulted in effectively determine the band in the wireless system and allocation band to reduce interference in the system. The device classify signal properly to allows communications systems to support a broad frequency range for robust RF data communication.
Regarding claim 2, Shima remains as applied above and continue to discloses generating said set of RF transmission data for use in training said classifier by: collecting over the air RF signals (Para. 7: Collecting and identifying RF signals); generating a larger set of RF signals by stitching together the collected RF signals (Para. 28: large frequency swath of the chirps signals) & (Para. 68: 400 takes in a large channel of RF data 406).
Regarding claim 5, Shima remains as applied above and continue to discloses the wireless RF signals in the environment suspected of containing unused or underused portions of said RF spectrum are received by a first receiver (Para. 7 & 92: unused or underused portions of RF spectrum); and the over the air RF signals are collected by a second receiver (Para. 36: White spaces and grey spaces spectrum for secondary users device).
Regarding claim 6, Shima remains as applied above and continue to discloses the wireless RF signals in the environment suspected of containing unused or underused portions of said RF spectrum are received by a first receiver; and the over the air RF signals are collected by the first receiver (Para. 7 & 92: unused or underused portions of RF spectrum).
Regarding claim 7, Shima teaches pre-processing the collected over the air RF signals in a pre-processing pipeline (Para. 50: Prepossess data) & (Para. 42).
Regarding claim 12, Shima remains as applied above and continue to discloses generating a larger set of RF signals by stitching together the collected RF signals is performed in a dataset generator pipeline and further comprises: generating a random number of signals to be injected into an observable bandwidth (Para. 7: Collecting and identifying RF signals & Para. 28: large frequency swath of the chirps signals) & (Para. 68: 400 takes in a large channel of RF data 406) & (Para. 76).
Regarding claim 13, Shima remains as applied above and continue to discloses generating a larger set of RF signals by stitching together the collected RF signals further comprises: assigning a target class, a corresponding signal type, and a corresponding central frequency to each of the random number of signals to be injected into the observable bandwidth (Para. 7 & Para. 68 & 76: 400 takes in a large channel of RF data 406) & (Para. 76 & Fig. 4).
Regarding claim 17, Claim 17 corresponds to claim 1 and is analyzed accordingly.
Regarding claim 20, Shima teaches the dataset generator including: a pre-processing pipeline configured to pre-process collected over the air RF signals (Para. 50: Prepossess data) & (Para. 42) and a dataset generator pipeline configured generate a larger set of RF signals by stitching together the pre-processed collected over the air RF signals (Para. 7: Collecting and identifying RF signals & Para. 28: large frequency swath of the chirps signals) & (Para. 68: 400 takes in a large channel of RF data 406) & (Para. 76).
Regarding claim 21, Shima teaches the multi-label multi-class machine learning classifier is a deep learning classifier (Abstract & Fig. 4).
Claims 3-4 & 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Shima (Pub No. 2018/0324595), in view of Govea et al (Pub No. 2020/0327397) and further in view of Soto et al (Pub No. 2022/0276094).
Regarding claim 3 & 18, Shima is silent regarding the step of classifying comprises a semantic spectrum segmentation process, wherein a plurality of signals are simultaneously classified and localized in both time and frequency at the IQ level using unprocessed IQ samples.
Soto et al discloses the step of classifying comprises a semantic spectrum segmentation process, wherein a plurality of signals are simultaneously classified and localized in both time and frequency at the IQ level using unprocessed IQ samples (Para. 89: signals are simultaneously classified) & (Par. 65 & 83: IQ data sample and wideband IQ signals).
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the invention to use the simultaneous classification system to classify signals properly to analyze the spectrum of the system.
Regarding claim 4 & 19, Shima teaches a non-local block to combine spatial features of the received RF signals (Para.72: combine spatial features of the received RF signals).
Claims 8-11 & 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Shima (Pub No. 2018/0324595), in view of Govea et al (Pub No. 2020/0327397) and further in view of Tachibana (Pub No. 2010/0056198).
Regarding claim 8, Shima is silent regarding: cropping the each over the air RF signal to remove a silence period before and/or after a signal transmission; and applying a bandpass filter to each cropped over the air RF signal extract a signal of interest.
Tachibana discloses cropping the each over the air RF signal to remove a silence period before and/or after a signal transmission (Para. 11: Mute signal cancellation & Para. 89); and applying a bandpass filter to each cropped over the air RF signal extract a signal of interest (Para. 27-28: applying a bandpass filter to each cropped signals) & (Para. 51: extracting).
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the invention to use the frequency adjust system to achieve better quality signals in the wireless system.
Regarding claim 9, Shima teaches converting the signal of interest, by a Fast Fourier Transform, to a filtered signal in a frequency domain (Para. 08 & 74: Fourier transform the signal).
Regarding claim 10, Shima teaches the step of pre-processing further comprises pruning the filtered signal to remove any frequency components outside of a frequency band of interest to produce a processed signal (Para. 71: Filtering signals).
Regarding claim 11, Shima teaches adding the processed signal to a signal bank (Fig. 3-4: adding signal spectrum for neural network).
Regarding claim 14, Shima is silent regarding: generating a larger set of RF signals by stitching together the collected RF signals further comprises: extracting, for each of the random number of signals to be injected into the observable bandwidth, a signal from a signal bank corresponding to the assigned target class.
Tachibana discloses generating a larger set of RF signals by stitching together the collected RF signals further comprises: extracting, for each of the random number of signals to be injected into the observable bandwidth, a signal from a signal bank corresponding to the assigned target class (Para. 11: Mute signal cancellation & Para. 89 & Para. 27-28: applying a bandpass filter to each cropped signal) & (Para. 51: extracting).
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the invention to use the frequency adjust system to achieve better quality signals in the wireless system.
Regarding claim 15, Shima teaches generating a larger set of RF signals by stitching together the collected RF signals further comprises: stitching the extracted signals together by combining the extracted signals via an additive operation (Para. 28: large frequency swath of the chirps signals) & (Para. 68: 400 takes in a large channel of RF data 406).
Regarding claim 16, Shima teaches producing one or more labels corresponding to each of the stitched extracted signals (Para. 72: labeled data); and storing the stitched extracted signals and the produced labels in a training dataset (Para. 85: allocation stored).
Another Prior Art
7. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Another prior art, Memik et al (US 2011/0028097) discloses scanning radio frequencies within an initial portion of the radio frequency spectrum and analyzing the frequencies scanned within the initial portion. Detecting white space frequency for further communications.
CONCLUSION
Applicant’s amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication from the examiner should be directed to Patent Examiner Md Talukder whose telephone number is (571) 270-3222. The examiner can normally be reached on Mon-Th 8:00 am to 4:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisors, Wesley Kim can be reached on 571-272-7867.
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/MD K TALUKDER/Primary Examiner, Art Unit 2648
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