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 Objections
Claims 3-4, 7-8, 10, 15, 22, 24, and 28 are objected to because of the following informalities:
Regarding claim 3, in line 4, replace “the AI/ML process” with --an AI/ML process--.
Regarding claim 4, in lines 1-2, replace “an AI processing unit” with --an AI core-- or --an AI/ML processing unit--.
Regarding claim 7, in line 1, replace “an AI processing unit” with --an AI core-- or --an AI/ML processing unit--.
Regarding claim 8, in line 2, replace “AI processing units” with --AI cores-- or --AI/ML processing units--.
Regarding claim 10, in line 2, replace “AI processing unit” with --AI core-- or --AI/ML processing unit--.
Regarding claim 15, in line 2, replace “AI processing units” with --AI cores-- or --AI/ML processing units--.
Regarding claim 22, in line 2, replace “AI processing units” with --AI cores-- or --AI/ML processing units--.
Regarding claim 24, in line 4, replace “the performance parameter” with --a performance parameter--.
Regarding claim 28, in line 7, replace “the item” with --an item--.
Appropriate correction is required.
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 following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
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) or pre-AIA 35 U.S.C. 112, sixth paragraph, 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) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(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) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, 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) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, 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) or pre-AIA 35 U.S.C. 112, sixth paragraph, 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) or pre-AIA 35 U.S.C. 112, sixth paragraph, 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) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) 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 limitation(s) is/are: processing units or AI/ML processing units in claim 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/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 this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-30 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 1, the limitation “wherein the UE comprises a second plurality of processing units or Artificial Intelligence, AI, cores or Artificial Intelligence/Machine Learning, AI/ML, processing units for generating the prediction report” was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. It is new matter.
Regarding claim 29, the limitation “having access to a second plurality of Artificial Intelligence, AI, cores or Artificial Intelligence/Machine Learning, AI/ML, processing units for generating the prediction report” was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. It is new matter.
Regarding claim 30, the limitation “having access to a second plurality of Artificial Intelligence, AI, cores or Artificial Intelligence/Machine Learning, AI/ML, processing units for generating the prediction report” was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. It is new matter.
Other claims are automatically rejected to for the reasons as set forth in rejected independent claim 1.
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)(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, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 4, and 12-30 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Saber et al (US 2025/0132846 A1).
Regarding claim 1, Saber discloses a user device, UE (Fig. 8, electronic device 801), for a wireless communication network (Fig. 8),
wherein the UE is to perform prediction of one or more performance parameters (Fig. 7 and 167th paragraph, AI/ML based CSI prediction. Herein, the predicted CSI include CQI, RI, PMI parameters, 30th paragraph),
wherein the UE is to generate a prediction report for reporting the predictions (Fig. 7, blocks 703 and 704, the electronic device generates a predicted CSI and transmits the predicted CSI using AI/ML model),
wherein the UE is to operate a first plurality of processing cores or processing units (N_CPUs) (Fig. 7, a plurality of 3-D CNN based CSI Predictor of a Neural Network Architecture), wherein the prediction report is associated with a certain CPU occupation (O_CPU) indicating a number of processing units (N_CPUs) operated simultaneously for generating the prediction report (126th paragraph, UE report maximum number of CSI processing units it can support for AI/ML features. Each active CSI prediction functionality may occupy a certain number of CSI processing units, denoted as Ocpu. The value of Ocpu can be declared as a UE capability),
wherein the UE comprises a second plurality of processing units or Artificial Intelligence, AI, cores or Artificial Intelligence/Machine Learning, AI/ML, processing units for generating the prediction report (Fig. 5, 3D-CNN based CSI predictors running task of CSI prediction, illustrated in Fig. 7. These 3D-CNN based CSI predictors are Artificial Intelligence and Machine Learning cores, 6th paragraph).
Regarding claim 4, Saber discloses that wherein a duration of an occupation of an AI processing unit is defined by a start and an end time (Fig. 6, prediction window, performed by 3-D CNN based CSI predictor, takes 2 instances 602. The instances include first instance or start instance and second instance or end instance).
Regarding claim 12, Saber discloses that a processing unit comprising the plurality of processing cores or the plurality of AI cores (Fig. 5, neural network architecture includes plurality of 3D-CNN based CSI predictors).
Regarding claim 13, Saber discloses that wherein the UE is to scale functions to run on processing cores as well as on AI cores (115th paragraph, UE switches between models for a single functionality).
Regarding claim 14, Saber discloses that where the UE is to switch off a part of the processing cores and/or the AI cores due to processing constraints or a battery usage and/or a processing power (limitation following e.g., is not considered, please see 112nd rejection above) (142nd paragraph, UE switches from AI/ML based CSI prediction to traditional CSI reporting. Herein, AI/ML based CSI is turned off based on network configurations and/or constraints).
Regarding claim 15, Saber discloses that wherein the UE comprises a maximum of simultaneously running processing units that comprise CPU (Fig. 8, processor 820) as well as AI processing units (Fig. 5, 3-D CNN based CSI predictors).
Regarding claim 16, Saber discloses that wherein the UE is to switch off one or more AI processing units (limitation following e.g., is not considered, please see 112nd rejection above) (115th paragraph, UE switches between models).
Regarding claim 17, Saber discloses that wherein the UE is to signal to a gNB or to the network, a processing architecture of the UE, a usage of the processing architecture and capabilities of the UE for enabling the gNB or network to choose one or more adequate AI algorithms to be run at the gNB side and/or at the UE side (32nd and 111th paragraphs, UE transmits capability report indicating UE supported CSI processing capabilities, maximum number of active functionalities or AI/ML model capabilities, CPU limitations, AI/ML model compatibility and supported CSI report configurations. The gNB may configure multiple functionalities for the UE based on UE capability report).
Regarding claim 18, Saber discloses that wherein each AI/ML process or report is associated with a number of occupied AI process units (O_CPU, AI) (128th paragraph, CSI report includes number of occupied CSI processing units, Ocpu).
Regarding claim 19, Saber discloses that wherein the UE is to report, e.g., to a gNB using a UE capabilities report, the number of processing units or AI processing units, being occupied (O_TPU, AI) (137th paragraph, the UE’s capability report includes number of occupied CSI processing units).
Regarding claim 20, Saber discloses that wherein the report has to fulfill CSI processing criteria and the AI/ML processing criteria (32nd paragraph, UE transmits capability report indicating UE supported CSI processing capabilities, maximum number of active functionalities or AI/ML model capabilities, CPU limitations, AI/ML model compatibility and supported CSI report configurations).
Regarding claim 21, Saber discloses that wherein the UE is to indicate to a gNB, a processing state of the UE, depending on one or more criteria or a battery usage or another ongoing signal processing on at the UE or a moving speed of the UE (limitation following e.g., is not considered, please see 112nd rejection above) (137th paragraph, the UE’s capability report includes number of occupied CSI processing units).
Regarding claim 22, Saber discloses that wherein the UE comprises a graphical processing unit, GPU, and wherein one or more or all of the AI processing units are part of the GPU (177th paragraph, processor includes CPU, GPU (graphic processing unit), ISP, and CP).
Regarding claim 23, Saber discloses that wherein the certain CPU operation (O_CPU) is set to a number that depends on one or more criteria (128th paragraph, Ocpu is set to be equal to less than Ncpu. This condition ensures that the number of CSI processing units occupied does not exceed the number of available CSI processing units for AI/ML operation).
Regarding claim 24, Saber discloses that wherein the one or more performance parameters comprise one or more of the following:
one or more beams, which are transmitted by a network entity of the wireless communication system and received at the UE, a performance value indicating a measured or predicted strength of a beam at the UE,
a reference signal received power, RSRP, the performance value indicating the measured or predicted RSRP,
a reference signal received quality, RSRQ, the performance value indicating the measured or predicted RSRQ,
a signal to noise ratio, SNR, the performance value indicating the measured or predicted SNR,
a rank (30th paragraph),
a PMI (30th paragraph),
a signal to noise and interference ration, SINR, the performance value indicating the measured or predicted SINR,
a ratio signal strength indicator RSSI, the performance value indicating the measured or predicted RSSI,
an interference level, the performance value indicating the measured or predicted interference level,
a doppler parameter, the performance value indicating the measured or predicted doppler parameter,
a delay, the performance value indicating the measured or predicted doppler delay,
a packet loss rate, the performance value indicating the measured or predicted packet loss rate,
one or more parameters reported from higher layers, the performance value indicating the measured or predicted values for the one or more parameters.
Regarding claim 25, Saber discloses that wherein a beam ID comprises one out of the following:
TCI state
TCI index
CSI-RS index or CRI (53rd paragraph, CRI)
SSB index, or SSBRI, or SBB ID
DRMS index
SRS index.
Regarding claim 26, Saber discloses that wherein the UE comprise one or more of a power-limited UE, or a hand-held UE, like a UE used by a pedestrian, or a Vulnerable Road User, VRU, or a Pedestrian UE, P-UE, or an on-body or hand-held UE used by public safety personnel and first responders, and referred to as Public safety UE, PS-UE, or an IoT UE or Ambient IoT UE or a sensor, or an actuator or a UE provided in a campus network to carry out repetitive tasks and requiring input from a gateway node at periodic intervals, or a mobile terminal, or a stationary terminal, or a cellular IoT-UE, an industrial IoT-UE, IIoT, or a SL UE, or a vehicular UE, or a vehicular group leader UE, GL-UE, or a scheduling UE, S-UE, or an IoT or narrowband IoT, NB-IoT, device, a NTN UE, or a WiFi device or WiFi station, STA, or a ground based vehicle, or an aerial vehicle, or a drone, or a moving base station, or road side unit, RSU, or a building, or device provided with network connectivity enabling the device to communicate using the wireless communication network or a sensor or actuator, or device provided with network connectivity enabling the device to communicate using a sidelink the wireless communication network or a sensor or actuator, or any sidelink capable network entity (Fig. 9, UE 905).
Regarding claim 27, Saber discloses a wireless communication network (Fig. 8) comprising a one or more user devices, UEs, of claim 1 (limitation following e.g., is not considered, please see 112nd rejection above) (see rejection of claim 1).
Regarding claim 28, Saber discloses one or more base stations, BSs, wherein the base station may comprises one or more of a macro cell base station, or a small cell base station, or a central unit of a base station, or a distributed unit of a base station, or an Integrated Access and Backhaul, IAB, node, or a road side unit, RSU, or a WiFi access point, AP, or a UE, or a SL UE, or a group leader UE, GL-UE, or a relay or a remote radio head, a satellite payload, an item or device being provided with network connectivity to communicate using the wireless communication network (Fig. 9, gNB 910).
Regarding claim 29, Saber discloses method for operating a user device, UE, for a wireless communication network (Fig. 7), comprising:
performing prediction of one or more performance parameters (Fig. 7 and 167th paragraph, AI/ML based CSI prediction. Herein, the predicted CSI include CQI, RI, PMI parameters, 30th paragraph),
generating a prediction report for reporting the predictions (Fig. 7, blocks 703 and 704, the electronic device generates a predicted CSI and transmits the predicted CSI using AI/ML model),
operating a first plurality of processing cores or processing units (N_CPUs) (Fig. 7, a plurality of 3-D CNN based CSI Predictor of a Neural Network Architecture), wherein the prediction report is associated with a certain CPU occupation (O_CPU) indicating a number of processing units (N_CPUs) operated simultaneously for generating the prediction report (126th paragraph, UE report maximum number of CSI processing units it can support for AI/ML features. Each active CSI prediction functionality may occupy a certain number of CSI processing units, denoted as Ocpu. The value of Ocpu can be declared as a UE capability),
having access to a second plurality of processing units, like Artificial Intelligence, AI, cores or Artificial Intelligence/Machine Learning, AI/ML, processing units for generating the prediction report (Fig. 5, 3D-CNN based CSI predictors running task of CSI prediction, illustrated in Fig. 7. These 3D-CNN based CSI predictors are Artificial Intelligence and Machine Learning cores, 6th paragraph).
Regarding claim 30, Saber discloses a non-transitory digital storage medium having a computer program stored (Fig. 8, memory 830 storing computer executable instructions) thereon to perform a method for operating a user device, UE, for a wireless communication network (Fig. 7), the method comprising:
performing prediction of one or more performance parameters (Fig. 7 and 167th paragraph, AI/ML based CSI prediction. Herein, the predicted CSI include CQI, RI, PMI parameters, 30th paragraph),
generating a prediction report for reporting the predictions (Fig. 7, blocks 703 and 704, the electronic device generates a predicted CSI and transmits the predicted CSI using AI/ML model),
operating a first plurality of processing cores or processing units (N_CPUs) (Fig. 7, a plurality of 3-D CNN based CSI Predictor of a Neural Network Architecture), wherein the prediction report is associated with a certain CPU occupation (O_CPU) indicating a number of processing units (N_CPUs) operated simultaneously for generating the prediction report (126th paragraph, UE report maximum number of CSI processing units it can support for AI/ML features. Each active CSI prediction functionality may occupy a certain number of CSI processing units, denoted as Ocpu. The value of Ocpu can be declared as a UE capability),
having access to a second plurality of Artificial Intelligence, AI, cores or Artificial Intelligence/Machine Learning, AI/ML, processing units for generating the prediction report (Fig. 5, 3D-CNN based CSI predictors running task of CSI prediction, illustrated in Fig. 7. These 3D-CNN based CSI predictors are Artificial Intelligence and Machine Learning cores, 6th paragraph),
wherein said computer program is run by a computer (Fig. 8, instructions stored in memory 830 are executable by processor 820 of electronic device or UE).
Allowable Subject Matter
Claims 2-3 and 5-11 are 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.
Response to Arguments
Applicant's arguments filed February 25, 2026 have been fully considered but they are not persuasive.
Applicant argues in page 10 that Saber fails to disclose that wherein the prediction report is associated with a certain CPU occupation (O_CPU) indicating a number of processing units (N_CPUs) operated simultaneously for generating the prediction report. Examiner respectfully disagrees. Saber discloses UE report maximum number of CSI processing units it can support for AI/ML features. Each active CSI prediction functionality may occupy a certain number of CSI processing units, denoted as Ocpu. The value of Ocpu can be declared as a UE capability (126th paragraph). Claim 1 recites an association of the prediction report and the number of processing units generating the prediction report. It is not the prediction report including the O_CPU indicating a number of processing units (N_CPUs) operated simultaneously for generating the prediction report. Herein, UE capability constraint is associated with the predicted CSI.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANH VU H LY whose telephone number is (571)272-3175. The examiner can normally be reached M-F 8am-5pm.
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ANH VU H. LY
Primary Examiner
Art Unit 2472
/ANH VU H LY/Primary Examiner, Art Unit 2472