DETAILED ACTION
1. The following Office Action is based on the application filed on August 9, 2024, having claims 1-12 and drawing figures 1-3.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
3. Acknowledgment is made of applicant's claim for foreign priority based on an application filed in India on 11 August 2023. It is noted, however, that applicant has not filed a certified copy of the foreign application as required by 37 CFR 1.55.
4. Acknowledgment is made of applicant's claim for foreign priority based on an application filed in India on 29 September 2023. It is noted, however, that applicant has not filed a certified copy of the foreign application as required by 37 CFR 1.55.
Specification
5. The abstract of the disclosure is objected to because of the following informalities:
The acronyms AI/ML, CSI, and ID must be defined the first time they are recited in the abstract.
The phrase “is computed” (abstract, line 7) must be replaced by the phrase “are computed” to conform with English grammar rules.
A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
6. Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
Claim Objections
7. Claims 1-3, 5 and 10-12 are objected to because of the following informalities:
The acronyms AI/ML, CSI, and ID must be defined the first time they are recited in claims 1 and 12.
The acronym UE must be written as “user equipment (UE)” the first time it is recited in claim 2.
The phrase “and/or” recited in line 2 of claim 3 must be replaced by the phrase “at least one of” to render the claim affirmative.
The acronym ID recited in claim 5 must be written as “identifier (ID)” the first time it is recited in the claim.
The phrase “models/parameters/data” recited in line 2 of claim 10 must be written as “at least one of models, parameters, and data” to render the claim definite.
The acronyms NW and UE must be written as “network (NW)” and “user equipment (UE)” respectively in claim 10.
The acronym UE must be written as “user equipment (UE)” the first time it is recited in claim 11.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
8. 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-8 and 10-12 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kim et al. (US 2026/0291578 A1).
For claims 1 and 12, Kim discloses a user equipment (Fig 1A, UE 110 or Fig 1B, apparatus 180) comprising: a processor (Fig 1B, processor 120); and a memory (Fig 1B, memory 125) coupled to the processor, wherein the processor is configured to perform:
transmit an initial capability report to a base station (Fig 7, step 1, UE reports its capabilities to the base station);
receive an initial network configuration from the base station (Fig 7, step 2 and 720, UE receives RRC configuration from base station);
transmit an AI-specific AI/ML CSI capability report to the base station (Fig 7, step 1, the reported UE capabilities comprise its ML-based CSI reporting scheme(s));
receive a CSI report configuration consisting of AI/ML model specific configuration parameters and CSI reporting parameters (Fig 7, step 3 and 730, UE receives Model ID and other CSI report configuration parameters from the base station);
receive CSI-Reference signals from the base station (Fig 7, step 4, UE receives CSI-related reference signals from the base station);
compute AI-CSI parameter based on the CSI report configuration (Fig 7, step 5, preparation of CSI feedback; Fig 7, 740, CSI measurements and AI-encoded PMI with associated eigenvalues); and
transmit a CSI report,
wherein the CSI report configuration is transmitted according to an information element (IE) consisting of a pairing ID (Fig 7, 730, the CSI configuration information comprises a Model ID (pairing ID)), and the AI- CSI parameter is computed based on AI/ML model indicated by the pairing ID and other CSI reporting parameters included in the CSI report configuration (Fig 7, 740, CSI measurements and AI-encoded PMI with associated eigenvalues).
For claim 2, Kim discloses the initial capability report indicates: the capability of a UE to support the AI/ML assisted CSI feedback compression; and information about the factors supporting AI/ML assisted CSI feedback compression, wherein the factors may include at least environment, frequency-domain, antennas, variables pertaining to model development (Fig 7, 720, the UE capabilities include AIML feedback CSI compression).
For claim 3, Kim discloses receiving, from the base station, configurations for the AI/ML capabilities and/or model IDs or model parameters or any other data for updating AI/ML models (Fig 7, 730, the configurations from the BS comprises Model ID, feedback payload size, eigenvector values, etc.).
For claim 4, Kim discloses the AI/ML model specific configuration parameters include at least one of the following parameters: • Model ID indicating identified model (Fig 7, 730, the CSI configuration information comprises a Model ID (pairing ID)); • Model input type indicating raw channel or eigenvector; • Model input size such as Tx antenna ports, Sub-band size; • Compression ratio; • Quantization type; and • Additional Quantization parameters depending on the quantization type.
For claim 5, Kim discloses the pairing ID indicates the most compatible model out of a plurality of AI/ML models (Fig 7, 730, the CSI configuration information comprises a Model ID (pairing ID)).
For claim 6, Kim discloses the pairing information is generated based on the type of training method adopted for a two-sided model (Fig 7, 750, the pairing information is generated based on two-sided model training phase).
For claim 7, Kim discloses the pairing information is generated from training dataset or dataset ID in Type 3 training method ([0057] type 3 training method; [0061] table showing RAN1#110 agreement).
For claim 8, Kim discloses the pairing information is generated from joint training information and joint training instance in in Type 1 and Type 2 training methods ([0055] type 1 and type2 training methods; [0061] table, joint training for types 1 and 2).
For claim 10, Kim discloses the pairing information is generated during exchange of models/parameters/data between NW and UE (online collaboration) (Fig 7, 750, collaboration between UE and NW/gNB to exchange generated parameters, models, and other data).
For claim 11, Kim discloses generating the pairing information during exchange of models or parameters or data between base station and UE (Fig 7, 750, collaboration between UE and NW/gNB to exchange generated parameters, models, and other data).
Allowable Subject Matter
9. Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892 form.
11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Elisabeth B Magloire whose telephone number is (571)272-5601. The examiner can normally be reached M-F 8 AM-5 PM ET.
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, Sujoy K Kundu can be reached at 571-272-8586. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ELISABETH BENOIT MAGLOIRE/Primary Examiner, Art Unit 2471
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