DETAILED ACTION
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 .
Request for Continued Examination (RCE)
2. The request filed on 09/10/2026, for a Request for Continued Examination (RCE) under 37 CFR 1.114 based on parent Application # 18/652827 is acceptable and an RCE has been established. An action on the RCE follows.
Claim Rejections - 35 USC § 103
3. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
4. Claim(s) 16, 17 and 20 are rejected under 35 U.S.C. 102 (a)(2) as being anticipated by Feki et al. (US2026/0012399)(hereafter Feki) in view of Dekel et al. (US 2024/0419382)(hereafter Dekel) and further in view of Li et al. (US 2026/0205212)(hereafter Li).
Regarding claim 16, Feki discloses a method, comprising: obtaining, by a processor of an apparatus, a data input sample (see, para [0005]);
performing, by the processor, a data augmentation to generate an augmented training data based on the data input sample (see, para [0005], augmented data for training a positioning model, [0062], model training with data augmentation, [0052], data augmentation to increase amount of training data);
performing, by the processor, a model training on a positioning model based on the augmented training data (see, para [0050], [0051], model training], [0061], see, Fig. 3, the model training using data augmentation, 300, see, fig. 7, the determine augmented data, 7015 and train the positioning model, 7025 using such augmented data); and
determining, by the processor, a position information of the apparatus by the positioning model (see, para [0155], Fig. 13, LMF, 1310, calculate the position of the first wireless device based on positioning model or assistance information).
But Feki does not disclose data augmentation is performed by one or more of a jittering augmentation method and a timing shift augmentation method.
However, in same field of endeavor, Dekel teaches in para [0087], train the object detector on a single scale using jitter-augmentation integrated landmark localization information through joint multi-task learning to improve the performance and accuracy of end-to-end object detection.
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to combine the teachings of Dekel with the Feki, as a whole, so as to use the jitter augmentation method to perform data augmentation, the motivation is to improve the accuracy of the localization.
But the combined teachings do not explicitly disclose crossed-out limitations.
However, in same field of endeavor, Li teaches in para [0079], In the simulations in FIG. 4A (which used the log from a gNodeB field test and get more than 26 thousands data samples, in which 23 thousands data samples are used for training the ML or AI model and three thousands data samples are used for the verification), using RSRP, RSRQ and DOA as input parameters may achieve the best performance.
Therefore, it would have been obvious to one of ordinary skilled in the art before the effective filing date of the claimed invention to combine the teachings of Li with the Feki and Dekel, as a whole, so as to perform data augmentation using the RSRP as input parameters, the motivation is to achieve the best performance (see, para [0079]).
Regarding claim 17, Feki further discloses the method, wherein the apparatus comprises at least one of a positioning reference unit (PRU), a user equipment (UE), a base station, a location management function (LMF), a server and a network node (see, para [0047], Fig. 8, Fig. 9).
Regarding claim 20, Feki further discloses the method, wherein the position information comprises an estimated location of the apparatus or a soft information related to the estimated location (see, para [0081], The augmented data 520 can be estimated for the locations. [0082], The device 410 trains 4040 the positioning model based on a combination of the measured data and the augmented data. For example, the combination of the measured data and the augmented data may indicate data at a certain position is measured and data at another certain position is interpolated (i.e., augmented)).
Allowable Subject Matter
5. Claims 1-15 are allowed.
The following is an examiner’s statement of reasons for allowance: The closest prior arts, in combination of the other limitations of the claim, fail to explicitly disclose transmitting, by a training entity, a request for an assistance data to a data collection entity, wherein the request comprises a first data augmentation indicator indicating a data augmentation method; receiving, by the training entity, the assistance data from the data collection entity, wherein the assistance data comprises a set of augmented training data and a set of second data augmentation indicators for the augmented training data, and each second data augmentation indicator indicates whether data augmentation is performed on a corresponding sample and which data augmentation method is used for the corresponding sample; selecting, by the training entity, samples for model training according to the set of second data augmentation indicators; performing, by the training entity, a model training on a positioning model based on the assistance data including the selected samples; and determining, by the training entity, a position information by the positioning model, as amended, render the claim allowable over prior arts.
The closest prior arts, in combination of the other limitations of the claim, fail to explicitly disclose, receiving, by a data collection entity, a request for an assistance data from a training entity, wherein the request comprises a first data augmentation indicator indicating a data augmentation method; generating, by the data collection entity, the assistance data according to the request, wherein the assistance data is generated by performing a data augmentation to train a positioning model; wherein the data augmentation generates a set of augmented training data, and wherein generating the assistance data further comprises adding a respective second data augmentation indicator to each sample to indicate whether data augmentation is performed on the sample and which data augmentation method is used for the sample; and transmitting, by the data collection entity, the assistance data to the training entity, wherein the assistance data comprisesthe set of augmented training data; and a set of data augmentation indicators for the augmented training data, as amended, render the claims allowable over prior arts.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DHAVAL V PATEL whose telephone number is (571)270-1818. The examiner can normally be reached Monday to Friday (8:00am-4:30pm).
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/DHAVAL V PATEL/Primary Examiner, Art Unit 2631
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