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 .
DETAILED ACTION
This is a reply to the application filed on 2/27/2025, in which, claims 1-12 and 24-31 are pending. Claims 1, 24, and 30 are independent.
When making claim amendments, the applicant is encouraged to consider the references in their entireties, including those portions that have not been cited by the examiner and their equivalents as they may most broadly and appropriately apply to any particular anticipated claim amendments.
Information Disclosure Statement
The information disclosure statement (IDS) submitted is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings filed on 2/27/2025 are accepted.
Specification
The disclosure filed on 2/27/2025 is accepted.
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.
Claim(s) 1-6, 12, and 24-31 is/are rejected under 35 U.S.C. 103 as being unpatentable over WO 2022013104 A1 (hereinafter ‘Ryden’) disclosed in IDS filed 2/27/25 in view of US 20240113915 A1 (hereinafter ‘Cheema’).
As regards claim 1, Ryden (WO 2022013104 A1) discloses: A method for a user equipment (UE) to communicate in a wireless network, the method comprising: (Ryden: the method of figures 4a and 4b)
receiving, at the UE from the wireless network, one or more physical downlink shared channel (PDSCH) comprising data for a neural network (NN) model for beam management; (Ryden: (page 12, lines 16-19, "In step 410, the wireless device receive, from the RAN node, configuration information for an ML model to be executed by the wireless device. This may comprise receiving a unicast transmission of the configuration information, receiving a broadcast transmission of the configuration information or receiving a multicast transmission of the configuration information."; Neural Network as ML model is disclosed, e.g. on page 8, line 31; PDSCH is disclosed because a broadcast or multicast transmission implies a physical downlink shared channel and, in the general context of the claim, POSCH is any physical downlink shared channel; see also page 12, lines 26-35, where it is disclosed that the UE receives, among other things, a representation of the NN model; using the NN model for beam management is disclosed on page 15, lines 14-21)
Ryden does not but in analogous art, Cheeman (US 20240113915 A1) teaches: verifying, at the UE, an integrity of the NN model received from the wireless network; (Cheema: Figs. 2-8, ¶107-¶108, ¶154, ¶162-¶177, i.e., UE performing ack/nack signaling based on whether it can support the AI model)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include verifying the integrity of the model and to provide ack/nack signaling based on supporting the model as taught by Cheema with the motivation to provide its capabilities to the network node (Cheema: ¶41)
Ryden et al combination further teaches: determining, at the UE, a UE capability to support the NN model received from the wireless network; and (Ryden: page 13, lines 4-13, "Referring still to Figure 4a, in step 411, the wireless device may determine a compatibility of the ML model, configured in accordance with the received configuration information, with an operating environment of the wireless device. Compatibility of an ML model with the operating environment of a wireless device may for example require the wireless device to have memory available to store the ML model and enough computational capacity to run the ML model, and/or may require the wireless device not to have exceeded a maximum number of ML models that can or should be simultaneously configured on the wireless device. Other examples of compatibility of an ML model with the operating environment of a wireless device may be envisaged.". See also, Cheema: Figs. 2-8, ¶107-¶108, ¶168-¶177, i.e., UE performing ack/nack signaling based on whether it can support the AI model)
in response to verifying the integrity and determining the UE capability to support the NN model, transmitting a NN model transfer complete acknowledgement to the wireless network. (Cheema: Figs. 2-8, ¶107-¶108, ¶168-¶177, i.e., UE performing ack/nack signaling based on whether it can support the AI model)
Claims 24 and 30 recite substantially the same features recited in claim 1 above and are rejected based on the rationale discussed in the rejection.
As regards claim 2, Ryden et al combination further teaches the method of claim 1, further comprising: generating a compiled NN model by compiling the data for the NN model for use by the UE; and (Cheema: Figs. 1, 10) loading the compiled NN model into a NN engine of the UE. (Cheema: ¶4)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include verifying the integrity of the model and to provide ack/nack signaling based on supporting the model as taught by Cheema with the motivation to provide its capabilities to the network node (Cheema: ¶41)
Claims 25 and 31 recite substantially the same features recited in claim 2 above and are rejected based on the rationale discussed in the rejection.
As regards claim 3, Ryden et al combination further teaches the method of claim 2, wherein transmitting the NN model transfer complete acknowledgement comprises transmitting the NN model transfer complete acknowledgement from the UE to a server of the wireless network through a base station. (Ryden: page 13, lines 4-13. See also, Cheema: Figs. 2-8, ¶107-¶108, ¶168-¶177, i.e., UE performing ack/nack signaling based on whether it can support the AI model)
Claim 26 recites substantially the same features recited in claim 3 above and is rejected based on the rationale discussed in the rejection.
As regards claim 4, Ryden et al combination further teaches the method of claim 3, further comprising, after loading the compiled NN model into the NN engine of the UE, signaling, from the UE to the base station, that the NN model is ready for use at the UE. (Ryden: page 13, lines 4-13. See also, Cheema: Figs. 2-8, ¶90, ¶107-¶108, ¶168-¶177
Claim 27 recites substantially the same features recited in claim 4 above and is rejected based on the rationale discussed in the rejection.
As regards claim 5, Ryden et al combination further teaches the method of claim 2, wherein transmitting the NN model transfer complete acknowledgement comprises transmitting the NN model transfer complete acknowledgement to a base station of the wireless network. (Ryden: page 6, lines 16-18, page 13, lines 4-13. See also, Cheema: Figs. 2-8, ¶107-¶108, ¶168-¶177, i.e., UE performing ack/nack signaling based on whether it can support pcithe AI model)
Claim 28 recites substantially the same features recited in claim 5 above and is rejected based on the rationale discussed in the rejection.
As regards claim 6, Ryden et al combination further teaches the method of claim 2, further comprising generating the compiled NN model and loading the compiled NN model into the NN engine of the UE within a time gap signaled to a base station in a UE capability report. (Ryden: page 6, lines 16-18, page 13, lines 4-13. See also, Cheema: Figs. 2-8, ¶90, ¶101, ¶107-¶108, ¶168-¶177)
Claim 29 recites substantially the same features recited in claim 6 above and is rejected based on the rationale discussed in the rejection.
As regards claim 12, Ryden et al combination further teaches the method of claim 1, further comprising receiving, from the wireless network, a configuration to monitor a performance of the NN model. (Ryden: page 2, lines 9-27. See also, Cheema: ¶4-¶5)
Claim(s) 7-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ryden in view of Cheema in view of US 20230198604 A1 (hereinafter ‘Bhamri’).
As regards claim 7, Ryden et al combination further teaches the method of claim 1. However, Ryden et al do not but in analogous art, Bhamri (US 20230198604 A1) teaches: wherein the NN model is trained by the wireless network for a single cell of the wireless network, and wherein the NN model is associated with a physical cell identifier (PCI). (Bhamri: Fig. 1, ¶17-¶18, ¶29-¶31, i.e., the AI model is based on identifiers for each individual beam/cell)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include associated the AI models with each individual beam/cell using identifiers as taught by Bhamri with the motivation to enable a wireless connection between the UE and the wireless network to achieve high directional precision and high signal quality for wireless signal transmission between the UE and the wireless network (Bhamri: ¶3)
As regards claim 8, Ryden et al combination further teaches the method of claim 1. However, Ryden et al do not but in analogous art, Bhamri (US 20230198604 A1) teaches: wherein the NN model is trained by the wireless network for a single cell of the wireless network, and wherein the NN model is associated with multiple transmission reception points (mTRP) in the single cell of the wireless network. (Bhamri: Fig. 1, ¶17-¶18, ¶29-¶34, i.e., the AI model is based on identifiers for each individual beam/cell with multi-TRP)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include associated the AI models with each individual beam/cell using identifiers as taught by Bhamri with the motivation to enable a wireless connection between the UE and the wireless network to achieve high directional precision and high signal quality for wireless signal transmission between the UE and the wireless network (Bhamri: ¶3)
As regards claim 9, Ryden et al combination further teaches the method of claim 1. However, Ryden et al do not but in analogous art, Bhamri (US 20230198604 A1) teaches: wherein the NN model is trained by the wireless network for multiple cells with different geographical coverages. (Bhamri: Fig. 1, ¶17-¶18, ¶22-¶25, ¶29-¶34, i.e., the AI model is based on cells in same or different geographic regions)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include associated the AI models with each individual beam/cell using identifiers as taught by Bhamri with the motivation to enable a wireless connection between the UE and the wireless network to achieve high directional precision and high signal quality for wireless signal transmission between the UE and the wireless network (Bhamri: ¶3)
As regards claim 10, Ryden et al combination further teaches the method of claim 1. However, Ryden et al do not but in analogous art, Bhamri (US 20230198604 A1) teaches: wherein the NN model is trained by the wireless network for multiple cells associated with a same frequency band. (Bhamri: Fig. 1, ¶17-¶18, ¶22-¶25, ¶29-¶34, ¶70-¶92, i.e., the AI model is based on cells and frequency range)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include associated the AI models with each individual beam/cell using identifiers as taught by Bhamri with the motivation to enable a wireless connection between the UE and the wireless network to achieve high directional precision and high signal quality for wireless signal transmission between the UE and the wireless network (Bhamri: ¶3)
As regards claim 11, Ryden et al combination further teaches the method of claim 1. However, Ryden et al do not but in analogous art, Bhamri (US 20230198604 A1) teaches: further comprising using a compiled NN model, at the UE, to derive at least one of a reference signal received power (RSRP) and one or more beam indices. (Bhamri: Fig. 1, ¶17-¶18, ¶22-¶25, ¶29-¶34, ¶70-¶92, i.e., the AI model is based on cells RSRP and index)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Ryden to include associated the AI models with each individual beam/cell using identifiers as taught by Bhamri with the motivation to enable a wireless connection between the UE and the wireless network to achieve high directional precision and high signal quality for wireless signal transmission between the UE and the wireless network (Bhamri: ¶3)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYED A ZAIDI whose telephone number is (571)270-5995. The examiner can normally be reached Monday-Thursday: 5:30AM-5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Nickerson can be reached at (469) 295-9235. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SYED A ZAIDI/ Primary Examiner, Art Unit 2432
