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 .
This communication is response to claims filed on 10/04/24.
Claims 1-20 are presented for examination.
Information Disclosure Statement’s
4. The information disclosure statement(s) submitted on 10/04/24 & 04/21/26 have being considered by the examiner and made of record in the application file.
Drawing
5. The drawings filed on 10/04/24 are accepted by the examiner.
Specification Objections
6. The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter.
7. Claim 11, in part, recites, "a non-transitory computer readable medium" and the specification fails to have antecedent basis for the terms in the claims. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o).
8. Claim 20 is also objected for the same reason as set forth above for claim 11.
Appropriate Correction is required.
Claims Objections
9. Claims 1-10 are objected to because of minor informalities:
10. Claim 1, recites, “a method comprising: communicating, within a radio access network (RAN) of a wireless communication network and between a user equipment (UE) and a network device, one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters, the communicating comprising: communicating a subset of the plurality of subsets of the AI/ML parameters according to a transmission configuration, by the network device, for the subset”.
11. Claim 1 recites “a method” in preamble. Thus, the preamble fail to identify “who” , “where”, or “which component” is performing this management method.
The body recite:
-communicating…” this step does not identify such method is performed by a device”; and
-determining… this step does not identify such method is performed by a device”.
12. When considering individual step or as a whole, one cannot identify “who” , “where”, or “which component(s)” is/are performing “A method”.
Thus, for clarity, it is suggested to insert, at least in the preamble, “ who” , “where”, or “which component(s)” is performing “a method”.
13. Claims 2-10 are also objected since they are depend upon objected independent claim set forth above.
Claim Rejections - 35 USC § 112
14. 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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
15. Claims 1-20 are rejected under 35 U.S.C. 112(b), second paragraph, 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.
16. Regarding claim 1: the limitation reciting “communicating a subset of the plurality of subsets of the AI/ML parameters according to a transmission configuration, by the network device, for the subset” renders the scope of the claim unclear.
Specifically, the claim previously recites “one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters.” It is unclear what is meant by subsequently reciting “a subset of the plurality of subsets of the AI/ML parameters.” The phrase may refer to one of the previously recited plurality of subsets of AI/ML parameters, or alternatively may refer to a further subset selected from the plurality of subsets. Accordingly, it is unclear what set of AI/ML parameters is required to be communicated by the claimed method.
Additionally, the recitation “according to a transmission configuration, by the network device, for the subset” does not clearly identify the relationship between the transmission configuration and “the subset,” because the antecedent scope of “the subset” is unclear in view of the preceding recitation.
Therefore, one of ordinary skill in the art would not be able to ascertain with reasonable certainty the scope of the claimed subject matter.
17. Claims 11 & 20 are also rejected for the same reason as set forth above for claim 1.
18. Claims 2-10 & 12-19 are rejected for the same reasons as stated above by virtue of their dependency on a rejected based claim.
For the purpose of examination, examiner will interpret the claims as best understood.
Claim Rejections - 35 USC § 103
19. 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 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 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
20. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (hereinafter referred as Wang) US Patent Application publication No. 2021/0158151 A1, in view of Thierry et al. (hereinafter referred as Thierry) International Publication Application No. WO 2022/033804 A1 (as disclosed in the IDS).
Regarding claims 1 & 11: Wang discloses an apparatus (See FIG. 7; a base station)/a method comprising:
at least one processor (See FIG. 7 & Para. 0041; the base station includes processor(s)); and
a non-transitory computer readable storage medium (See FIG. 7 & Para. 0041; the base station includes memory/storage), coupled to the at least one processor, storing programming for execution by the at least one processor, the programming including instructions to cause the apparatus to perform operations including:
communicating, within a radio access network (RAN) of a wireless communication network and between a user equipment (UE) and a network device (See FIG. 7 & Para. 0099; signaling and control transaction diagram 700 between a base station and a user equipment in accordance with one or more aspects of neural network formation configurations in wireless communication), neural network formation configurations (See Para. 0103-0104; the base station 120 (and/or the core network server 302) selects the neural network formation configuration from multiple neural network formation configurations. the base station 120 communicates the neural network formation configuration to the UE 110),
wherein/communicating a subset of the plurality of subsets of the AI/ML parameters is communicated according to a transmission configuration, by the network device, for the subset (See Para. 0118 & 0120; the base station transmits the neural network table using layer 3 messaging (e.g., Radio Resource Control (RRC) messages. portions or all of the signaling and control transactions described with reference to the signaling and control transaction diagram 900 correspond to signaling and control transactions described with reference to FIG. 7).
Wang does not explicitly discloses one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters.
However, Thierry from the same field of endeavor discloses one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters (See Para. 0096; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 2 & 12: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Wang discloses an apparatus/a method, the operations further comprising: communicating the transmission configuration from the network device to the UE via radio resource control (RRC) signaling, medium access control (MAC) control element (MAC-CE) signaling, or downlink control information (DCI) signaling (See Para. 0120; RRC message).
Regarding claims 3 & 13: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, wherein the transmission configuration indicates transmission of only one of the plurality of subsets of the AI/ML parameters (See Para. 0096; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the transmission configuration indicates transmission of only one of the plurality of subsets of the AI/ML parameters as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 4 & 14: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, wherein the plurality of subsets comprises multiple subsets that include common AI/ML parameters (See Para. 0096; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the plurality of subsets comprises multiple subsets that include common AI/ML parameters as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 5 & 15: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, the communicating comprises: communicating an indication of first AI/ML parameters and values of the first AI/ML parameters in a first subset of the plurality of subsets (See Para. 0096 & 0153; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include the communicating comprises: communicating an indication of first AI/ML parameters and values of the first AI/ML parameters in a first subset of the plurality of subsets as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 6 & 16: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, wherein the indication indicates one or more AI/ML model layers for which associated parameters are communicated (See Para. 0096 & 0153; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the indication indicates one or more AI/ML model layers for which associated parameters are communicated as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 7 & 17: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, wherein the indication comprises a connection bitmap that indicates whether the first AI/ML parameters in the first subset include weights for connections between respective pairs of AI/ML model layers (See Para. 0096 & 0153; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the indication comprises a connection bitmap that indicates whether the first AI/ML parameters in the first subset include weights for connections between respective pairs of AI/ML model layers as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 8 & 18: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, wherein the indication comprises a connection group bitmap that indicates whether the first AI/ML parameters in the first subset include weights for consecutive connections between respective series of AI/ML model layers (See Para. 0096 & 0153; the AI/ML model is partitioned in several unitary chunks).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the indication comprises a connection group bitmap that indicates whether the first AI/ML parameters in the first subset include weights for consecutive connections between respective series of AI/ML model layers as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 9 & 19: The combination of Wang and Thierry disclose an apparatus/a method.
Furthermore, Thierry discloses an apparatus/a method, wherein the indication indicates a connection start location and a connection length of connections in an AI/ML model for which the first AI/ML parameters in the first subset include connection weights (See Para. 0096 & 0153; the AI/ML model is partitioned in several unitary chunks).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include wherein the indication indicates a connection start location and a connection length of connections in an AI/ML model for which the first AI/ML parameters in the first subset include connection weights as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Regarding claims 20: Wang discloses a non-transitory computer readable medium (See FIG. 7 & Para. 0041; the base station includes memory/storage) having instructions stored thereon that, when executed by an apparatus (See FIG. 7 & Para. 0041; the base station includes processor(s)), cause the apparatus to perform operations, the operations comprising:
communicate, within a radio access network (RAN) of a wireless communication network and between a user equipment (UE) and a network device (See FIG. 7 & Para. 0099; signaling and control transaction diagram 700 between a base station and a user equipment in accordance with one or more aspects of neural network formation configurations in wireless communication), neural network formation configurations (See Para. 0103-0104; the base station 120 (and/or the core network server 302) selects the neural network formation configuration from multiple neural network formation configurations. the base station 120 communicates the neural network formation configuration to the UE 110),
wherein/communicating a subset of the plurality of subsets of the AI/ML parameters is communicated according to a transmission configuration, by the network device, for the subset (See Para. 0118 & 0120; the base station transmits the neural network table using layer 3 messaging (e.g., Radio Resource Control (RRC) messages. portions or all of the signaling and control transactions described with reference to the signaling and control transaction diagram 900 correspond to signaling and control transactions described with reference to FIG. 7).
Wang does not explicitly discloses one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters.
However, Thierry from the same field of endeavor discloses one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters (See Para. 0096; the AI/ML model is partitioned in several unitary chunks, as shown in FIG. 7. the base station raises a signalling bit to inform UE that a chunk is available).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include one or more of a plurality of subsets of artificial intelligence/machine learning (AI/ML) parameters as taught by Thierry in the system of Wang to provide several AI/ML model split to generate model subsets/chunks for different model architecture (See abstract; lines 6-7).
Conclusion
21. The prior art of record and not relied upon is considered pertinent to applicant’s disclosure.
A. Fang et al. 2026/0206082 A1 (Title: Multi-AP MLD network reliability improvement…) (See Abstract, Para. 0012 & 0037-0038).
B. Zhang et al. 2026/0156509 A1 (Title: Method for signaling between network and UE) (See abstract, Para. 0006 & 00813-0016).
C. NAIK et al. 2025/0365662 A1 (Title: Non-primary channel access coordination…) (See FIG. 1, Para. 0046, 0050 & 0160).
22. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEWALE A AMBAYE whose telephone number is (571)270-1076. The examiner can normally be reached on M.F 6a.m.-2p.m..
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ian Moore can be reached on (571)272-3085. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MEWALE A AMBAYE/Primary Examiner, Art Unit 2469
Prosecution Insights