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 .
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.
Priority
The instant application is the national stage entry under 35 U.S.C. 371 of Application No. PCT/KR2023/008418, filed 19 June 2023 and having claims 1-15, which claims foreign priority to Korea Patent Application No. 10-2022-0077815, filed 24 June 2022. Claims 1-15 have been examined.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 20 December 2024 and 17 September 2025 was filed before the mailing date of the first action on the merits. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f):
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f), except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f), except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) because the claim limitations uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitations are: “artificial intelligence (AI) model for encoding” and “artificial intelligence (AI) model for decoding” in claims 1-3 and 10.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f), they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f), applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f).
Claim Rejections - 35 USC § 102
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 1-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Application Publication No. 2022/0149904 to Timo et al. (hereinafter Timo).
As per claim 1, Timo discloses a method of a user equipment (UE) for reporting a channel state information (CSI) in a wireless communication system (see paragraphs 38 and 125), the method comprising:
compressing CSI data estimated between a base station (BS) and the UE (see figure 3 and paragraphs 125-129) through an artificial intelligence (AI) model for encoding jointly trained with an AI model for decoding of the BS (see paragraphs 145-146).
transmitting the compressed CSI data to the BS (see paragraph 128);
transmitting, to the BS, the CSI data before compression is performed, based on a preset condition (see paragraph 263; UE configured by the BS to send periodic updates, see paragraph 266); and
receiving information for updating the AI model for encoding when the BS determines to update the AI model for encoding based on the CSI data (see paragraph 263).
As per claim 2, Timo discloses a method of a base station (BS) for reporting a channel state information (CSI) in a wireless communication system (see paragraphs 38 and 133), the method comprising:
receiving, from a UE, CSI data compressed through an AI model for encoding jointly trained with an AI model for decoding of the BS (see paragraphs 128, 133, 134, and 145-146);
receiving, from the UE, CSI data before compression is performed, based on a preset condition (see paragraph 263; UE configured by the BS to send periodic updates, see paragraph 266);
determining to update the AI model for encoding based on the CSI data (see paragraph 267); and
transmitting information for updating the AI model for encoding (see paragraphs 263-267).
As per claim 3, Timo discloses a user equipment (UE) for reporting a channel state information (CSI) in a wireless communication system (see paragraphs 38 and 125), the UE comprising:
a transceiver; and a processor (see paragraph 343) connected to the transceiver and configured to
compress CSI data estimated between a base station (BS) and the UE (see figure 3 and paragraphs 125-129) through an artificial intelligence (AI) model for encoding jointly trained with an AI model for decoding of the BS (see paragraphs 145-146),
transmit the compressed CSI data to the BS (see paragraph 128),
transmit, to the BS, the CSI data before compression is performed, based on a preset condition (see paragraph 263; UE configured by the BS to send periodic updates, see paragraph 266), and
receive information for updating the AI model for encoding when the BS determines to update the AI model for encoding based on the CSI data (see paragraph 263).
As per claim 4, Timo further discloses the processor is configured to receive, from the BS, a request for the CSI data when decoding performance of an uplink (UL) signal received by the BS fails to satisfy a preset threshold or a change in channel state is detected based on the UL signal (see paragraphs 265 and 267; decision by BS to update, triggering a request, see paragraphs 196, 219, and 302).
As per claim 5, Timo further discloses the CSI data comprises a matrix representing a state of a channel, wherein the request for the CSI data comprises at least one of a number of matrices requested by the BS for transmission or a partition indicator which specifies at least some of the matrices requested by the BS for transmission (set of matrices as per a codebook index, which necessitates a number of matrices where the set is variable, see paragraph 303).
As per claim 6, Timo further discloses the processor is configured to receive channel estimation configuration information from the BS by higher layer signaling, and transmit the CSI data based on an interval set based on the channel estimation configuration information (see paragraphs 263, 264, and 266).
As per claim 7, Timo further discloses the processor is configured to transmit, to the BS, a request to update the AI model for encoding when decoding performance of a downlink (DL) signal received by the UE fails to satisfy a preset threshold or a change in channel state is detected based on the DL signal, and receive, from the BS, a request for the CSI data based on the request to update the AI model for encoding (see paragraphs 265 and 267; decision by BS to update, triggering a request, see paragraphs 196, 219, 302, and 338).
As per claim 8, Timo further discloses the information for updating the AI model for encoding comprises neural network (NN) configuration information for an AI model for encoding updated in the BS, and wherein the NN configuration information comprises information about at least one of a type of a layer included in the updated AI model for encoding (layers associated with U2 may be reconfigured, see paragraph 300), a number of layers, a number of filter kernels, a size of the filter kernel or a parameter of the filter kernel.
As per claim 9, Timo further discloses when decoding performance of a UL signal received by the BS fails to satisfy a preset threshold, the compressed CSI is identified as having an error, and the information for updating the AI model for encoding comprises an indicator indicating CSI data associated with the error among a plurality of pieces of CSI data transmitted to the BS or an indicator indicating a portion of CSI data associated with the error (if deviation is too great, compression/decompression functions may need updating, see paragraph 196, resulting in an update request, see paragraphs 196, 219, 302, and 338).
As per claim 10, Timo discloses a base station (BS) for reporting a channel state information (CSI) in a wireless communication system (see paragraphs 38 and 125), the BS comprising:
a transceiver; and a processor connected to the transceiver (see paragraph 343) and configured to
receive, from a user equipment (UE), CSI compressed through an AI model for encoding jointly trained with an AI model for decoding of the BS (see paragraphs 128, 133, 134, and 145-146),
receive, from the UE, CSI data before compression is performed, based on a preset condition, determine to update the AI model for encoding based on the CSI data (see paragraph 263; UE configured by the BS to send periodic updates, see paragraph 266), and
transmit information for updating the AI model for encoding (see paragraphs 263-267).
As per claim 11, Timo further discloses the processor is configured to transmit, to the UE, a request for the CSI data when decoding performance of an uplink (UL) signal received by the BS fails to satisfy a preset threshold or a change in channel state is detected based on the UL signal (see paragraphs 265 and 267; decision by BS to update, triggering a request, see paragraphs 196, 219, and 302).
As per claim 12, Timo further discloses the processor is configured to transmit channel estimation configuration information to the UE by higher layer signaling, and receive the CSI data based on an interval set based on the channel estimation configuration information (see paragraphs 263, 264, and 266).
As per claim 13, Timo further discloses the processor is configured to receive, from the UE, a request to update the AI model for encoding when decoding performance of a downlink (DL) signal received by the UE fails to satisfy a preset threshold or a change in channel state is detected based on the DL signal, and transmit, to the UE, a request for the CSI data based on the request to update the AI model for encoding (see paragraphs 265 and 267; decision by BS to update, triggering a request, see paragraphs 196, 219, 302, and 338).
As per claim 14, Timo further discloses the information for updating the AI model for encoding comprises neural network (NN) configuration information for an AI model for encoding updated in the BS, and wherein the NN configuration information comprises information about at least one of a type of a layer included in the updated AI model for encoding (layers associated with U2 may be reconfigured, see paragraph 300), a number of layers, a number of filter kernels, a size of the filter kernel or a parameter of the filter kernel.
As per claim 15, Timo further discloses the processor is configured to identify that there is an error in the compressed CSI when decoding performance of a UL signal received by the BS fails to satisfy a preset threshold, and wherein the information for updating the AI model for encoding comprises an indicator indicating CSI data associated with the error among a plurality of pieces of CSI data transmitted to the BS or an indicator indicating a portion of CSI data associated with the error (if deviation is too great, compression/decompression functions may need updating, see paragraph 196, resulting in an update request, see paragraphs 196, 219, 302, and 338).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent Application Publication No. 2023/0084164 discloses neural network algorithms for CSI encoding.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW E HENEGHAN whose telephone number is (571)272-3834. The examiner can normally be reached M-F 8-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael Fuelling can be reached at (571)270-1367. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATTHEW E HENEGHAN/Primary Examiner, Art Unit 3992
