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 .
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-6 and 8-15 are rejected under 35 U.S.C. 102(a) as being anticipated by WO 2023/082280 (cited on IDS)[R1].
For claim 1, R1 discloses obtaining at least one prototype radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, pages 2-3, and 5-11 of attached translation the gNB configures one of multiple channel generators for the LOS/NLOS, indoor/outdoor, delay power spectrum, multiple path, angles, speed, a preconfigured channel generator for a given type basically is a prototype for that class); extracting at least one statistical parameter model based at least on the at least one prototype radio channel model, wherein the at least one statistical parameter model corresponds to at least one parameter of the at least one prototype radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, pages 2-3, and 5-11 of attached translation indicator features and mathematically process datasets to obtain a dataset corresponding to the channel type/indicators a parameter model from the chosen prototype/generators); generating at least one synthetic radio channel model realization based at least on the at least one statistical parameter model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, pages 2-3, and 5-11 of attached translation random noise, generator G and synthetic channel samples used in training); and training a wireless model using the at least one synthetic radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, pages 2-3, and 5-11 of attached translation wireless ML model is trained using the generated channel dataset).
For claim 2, R1 discloses validating the trained wireless model using at least one validation radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 3, R1 discloses refining the at least one statistical parameter model based on the validation of the trained wireless model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 4, R1 discloses the at least one prototype radio channel model comprises at least one existing radio channel model and/or at least one radio channel measurement (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 5, R1 discloses the extracting the at least one statistical parameter model based at least on the at least one prototype radio channel model comprises: identifying at least one key parameter of the at least one prototype radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ]; and extracting the at least one statistical parameter model based at least on the identified at least one key parameter, wherein the at least one statistical parameter model corresponds to the at least one key parameter of the at least one prototype radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 6, R1 discloses evaluating the at least one statistical parameter model by comparing samples from the at least one statistical parameter model and samples from the at least one prototype radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 8, R1 discloses the extracting the at least one statistical parameter model based at least on the at least one prototype radio channel model comprises assigning a probability distribution for the at least one parameter of the at least one prototype radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 9, R1 discloses the training the wireless model using the at least one synthetic radio channel model comprises: generating at least one synthetic radio channel model parameter realization based at least on the at least one synthetic radio channel model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ]; generating a training dataset using the at least one synthetic radio channel model parameter (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ]realization; and training the wireless model based at least on the training dataset (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 10, R1 discloses the wireless model comprises a radio receiver model, a radio transmitter model, a physical layer receiver model, and/or a physical layer transmitter model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 11, R1 discloses the at least one parameter of the at least one prototype radio channel model comprises at least one of: a line of sight indicator; a number of clusters or multipaths; an azimuth angle spread of departure; an azimuth angle spread of arrival; a zenith angle spread of departure; a zenith angle spread of arrival; a cross-polarization ratio; a delays of the clusters or multipath; a powers of the clusters or multipath; an azimuth angle of departure for each cluster or multipath; an azimuth angle of arrival for each cluster or multipath; a zenith angle of arrival for each cluster or multipath; and/or a zenith angle of departure for each cluster or multipath (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ].
For claim 12, R1 discloses at least one processor; and at least one memory including computer program code and a trained wireless model obtained using the method according claim 1 (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, and 5-11 of attached translation ]; the at least one memory and the computer program code configured to, with the at least one processor, cause the radio device to: receive and/or transmit a radio signal using the trained wireless model (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, 24-25, and 5-11 of attached translation ].
For claim 13, R1 discloses a client device comprising the radio device according to claim 12 (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, 24-25, and 5-11 of attached translation ].
For claim 14, R1 discloses a network node device comprising the radio device according to claim 12 (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, 24-25, and 5-11 of attached translation ].
For claim 15, R1 discloses non-transitory computer-readable medium storing instructions, which when executed by a computer, causes the computer to perform the method of claim 1 (page 1 lines 36-44, page 5 lines 25-end, step 204, page 36-44, step 1003, page 7 lines 4-18, page 11 mod.271, Tables 1-2, claims 24-25,66-67, of untranslated document, [or pages 2-3, 24-25, and 5-11 of attached translation ].
Claim Rejections - 35 USC § 103
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 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 nonobviousness.
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 CFR 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.
Claim 7 is rejected under 35 U.S.C. 102(a)(1) as anticipated by R1 or, in the alternative, under 35 U.S.C. 103 as obvious over R1.
For claim 7, R1 discloses the comparing samples from the at least one statistical parameter model and samples from the at least one prototype radio channel model comprises comparing the samples from the at least one statistical parameter model and the samples from the at least one prototype radio channel model using Kolmogorov–Smirnov test (page 1 lines 36-44, page 5 lines 25-end, page 36-44, step1003, page 7 lines 4-18, page 11 mod.271, Tbls 1-2, clms 24-25,66-67).
However, Examiner takes Official Notice that the use of the comparing samples from the at least one statistical parameter model and samples from the at least one prototype radio channel model comprises comparing the samples from the at least one statistical parameter model and the samples from the at least one prototype radio channel model using Kolmogorov–Smirnov test was common and well known in the art prior to the effective filing date. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify R1 to use the comparing samples from the at least one statistical parameter model and samples from the at least one prototype radio channel model comprises comparing the samples from the at least one statistical parameter model and the samples from the at least one prototype radio channel model using Kolmogorov–Smirnov test. The technical reasoning to combine would be to use a commonly used model test for standardization, and design choice.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Yoo et al (US 20220405602) discloses A.I. channel models.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER R CROMPTON whose telephone number is (571)270-3678. The examiner can normally be reached 10AM-4PM ET M-Th.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Asad Nawaz can be reached at (571)272-3988. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER R CROMPTON/Primary Examiner, Art Unit 2463
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