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 .
Priority
This application is a 371 of PCT/CN2021/124971 filed on 10/20/2021.
The present application does not claim for foreign priority.
Information Disclosure Statement
The information disclosure statements (IDS) were submitted on 4/18/2024 and 7/1/2025. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Claim Objections
Claims 1, 5-7, 14, 30, 34, and 62 are objected because of the following informalities:
In claim 1, it is suggested to replace “with” with “by” to read A first device, comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the first device to: …” for clarity.
In claims 5-7, 14, and 34, it is suggested to replace “with the second device” with “by the second device” for grammatical correction and for clarity.
In claims 6 and 7, it is suggested to amend to add missing phrase to read “…, wherein the instructions, when executed with the at least one processor, further cause the first device to: determine …” for clarity.
In claim 30, it is suggested to amend to read “receiving, by a first device and from a second device, a second message indicating …” for clarity.
In claim 62, it is suggested to amend the claim for clarity to read:
62. (Currently Amended) A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors of an apparatus, cause the apparatus to perform the method of claim 30.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
Claims 9 and 13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 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.
Regarding claim 9:
Claim 9 recites a limitation “the apparatus” in line 2. There is insufficient antecedent basis for the limitation in the claim. It is suggested to replace “the apparatus” with “the first device”.
Regarding claim 13:
It is unclear from the claim language which device performs the recited “perform a finetuning for the trained combining model and the trained beamforming model.” While the claim first recites that the first device transmits a trigger to the second device indicating that the second device is to perform a finetuning for the trained compression model, the subsequent limitation merely recites “perform a finetuning” without specifying whether the finetuning is performed by the first device or by the second device in response to the transmitted trigger. Although claim 13 is directed to a first device, the immediately preceding limitation introduces the second device as the recipient of the finetuning trigger, thereby creating ambiguity regarding the actor that performs the subsequent finetuning operation. Accordingly, the metes and bounds of claim 13 cannot be determined with reasonable certainty.
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 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 14-17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Vitthaladevuni et al. (US 2023/0246693 A1, hereinafter Vitthaladevuni).
Regarding claim 14:
Vitthaladevuni teaches a second device (see, Vitthaladevuni: Fig. 9, First Device 905; Fig. 15, Apparatus 1505), comprising: at least one processor (see, Vitthaladevuni: Fig. 15, Processor 1520); and at least one memory (see, Vitthaladevuni: Fig. 15, Computer-Readable Medium/Memory 1525) storing instructions that, when executed with the at least one processor, cause the second device to:
determine a second message indicating a second channel state according to a trained compression model (see, Vitthaladevuni: Fig. 9 and para. [0151], “As shown by reference number 950, in some aspects, the first device 905 may determine CSI corresponding to the second reference signal and, as shown by reference number 955, may determine a differential CSI. The differential CSI may be based at least in part on the CSI corresponding to the first reference signal and the CSI corresponding to the second reference signal. In some aspects, the CSI corresponding to the first reference signal may have a first CSI type, and the CSI corresponding to the second reference signal may have a second CSI type. For example, the first CSI type may include a Type-I CSI, a Type-II CSI, or a Type-III CSI. The second CSI type may include a Type-I CSI, a Type-II CSI, or a differential neural network based CSI.”; para. [0042], “According to aspects of the techniques and apparatuses described herein, an encoding device may be configured to save CSF that corresponds to a first reference signal for a specified period of time. The encoding device may use the saved CSF to facilitate transmitting a differential CSF based at least in part on a second reference signal. In some aspects, an encoding device may be configured to refrain from transmitting an additional CSF for a specified time period after transmitting a neural network based CSF. In some aspects, neural networks may be used for compressing and encoding channel information and interference information to provide robust CSF so that information sent in an initial CSF may be sufficient for a specified period of time, or so that the information may be supplemented by a differential CSF rather than a full CSF transmission.”), the second message having a second length less than a first length of a first message indicating a first channel state (see, Vitthaladevuni: para. [0152], “The first device 905 may generate a differential CSF based at least in part on the second CSF and a stored first CSF. In some aspects, the first device 905 may use a first neural network to generate the first CSF and a second neural network to generate the differential CSF.”), the first message being previously determined with the second device (see, Vitthaladevuni: para. [0149], “As shown by reference number 925, the first device 905 may determine CSI corresponding to the first reference signal. As shown by reference number 930, the first device 905 may encode the CSI corresponding to the first reference signal to generate CSF. In some aspects, for example, the first device 905 may use a first neural network to generate the CSF.”); and
transmit, to a first device (see, Vitthaladevuni: Fig. 9, Second Device 910; Fig. 17, Apparatus 1705), the second message (see, Vitthaladevuni: Fig. 9 and para. [0155], “As shown by reference number 965, the first device 905 may transmit, and the second device 910 may receive, a differential CSF. The differential CSF may be based at least in part on the CSF and a second reference signal carried on the downlink channel, as explained above.”).
Regarding claim 15:
As discussed above, Vitthaladevuni teaches all limitations in claim 14.
Vitthaladevuni further teaches wherein the instructions, when executed with the at least one processor, further cause the second device to:
receive, from the first device, reference signal configuration information, the reference signal configuration information comprising a time offset indicating a time interval between the second message and the first message (see, Vitthaladevuni: Fig. 9 and para. [0148], “the CSI feedback configuration may include an indication to report at least one neural network based CSI based at least in part on determining that a differential neural network based reporting threshold is satisfied. In some aspects, the CSI feedback configuration may include an indication to refrain from transmitting a second CSF for a specified time period after transmitting a first CSF that includes neural network based CSI.”).
Regarding claim 16:
As discussed above, Vitthaladevuni teaches all limitations in claim 14.
Vitthaladevuni further teaches wherein the instructions, when executed with the at least one processor, further cause the second device to:
receive, from the first device, a first reference signal at a first timeslot (see, Vitthaladevuni: Fig. 9 and para. [0149], “As shown by reference number 920, the second device 910 may transmit, and the first device 905 may receive, a first reference signal. In some aspects, for example, the first reference signal may include a CSI-RS.”; para. [0145], “As shown by reference number 915, the second device 910 may transmit, and the first device 905 may receive, a CSI feedback configuration that includes an indication to save, for a specified time period, a CSF that corresponds to a first reference signal carried on a downlink channel. In some aspects, the CSF may include channel information and interference information. In some aspects, the specified time period may include a number of slots or a number of milliseconds. In some aspects, the CSI feedback configuration may be carried in a radio resource control (RRC) message, a medium access control (MAC) control element (MAC-CE), and/or the like.” Accordingly, receiving a first reference signal at a first timeslot is inherent.);
determine first channel state information based on the first reference signal (see, Vitthaladevuni: Fig. 9 and para. [0149], “As shown by reference number 925, the first device 905 may determine CSI corresponding to the first reference signal.”); and
determine the first message according to the trained compression model and based on the first channel state information (see, Vitthaladevuni: Fig. 9 and para. [0149], “As shown by reference number 930, the first device 905 may encode the CSI corresponding to the first reference signal to generate CSF. In some aspects, for example, the first device 905 may use a first neural network to generate the CSF.”).
Regarding claim 17:
As discussed above, Vitthaladevuni teaches all limitations in claim 16.
Vitthaladevuni further teaches wherein the instructions, when executed with the at least one processor, further cause the second device to:
receive, from the first device, a second reference signal at a second timeslot after the first timeslot (see, Vitthaladevuni: Fig. 9 and para. [0150], “As shown by reference number 945, the second device 910 may transmit, and the first device 905 may receive, a second reference signal. In some aspects, for example, the second reference signal may include a CSI-RS.” As shown in Fig. 9, receiving a second reference signal at a second timeslot after the first timeslot is inherent wherein the second reference signal 945 is received after the first reference signal 920.); and
determine second channel state information based on the second reference signal (see, Vitthaladevuni: Fig. 9, Steps 950 and 955; and para. [0151], “As shown by reference number 950, in some aspects, the first device 905 may determine CSI corresponding to the second reference signal and, as shown by reference number 955, may determine a differential CSI. The differential CSI may be based at least in part on the CSI corresponding to the first reference signal and the CSI corresponding to the second reference signal.”.);
wherein determining the second message comprises: determining the second message according to the trained compression model and based on a difference between the second channel state information and the first channel state information (see, Vitthaladevuni: Fig. 9, Steps 950 and 955; and para. [0151], “As shown by reference number 950, in some aspects, the first device 905 may determine CSI corresponding to the second reference signal and, as shown by reference number 955, may determine a differential CSI. The differential CSI may be based at least in part on the CSI corresponding to the first reference signal and the CSI corresponding to the second reference signal.”).
Claim Rejections - 35 USC § 103
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
Claims 1-3, 5, 8, 9, 30-32, 34, and 62 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (US 2018/0278315 A1, hereinafter Wu) in view of Mo et al. (US 2023/0032241 A1, hereinafter Mo) claiming benefit to and fully-supported by US provisional applications 63/227,741 filed Jul. 30, 2021.
Regarding claim 1:
Wu teaches a first device (see, Wu: Fig. 4, Base Station 110), comprising: at least one processor (see, Wu: Fig. 4, Controller/Processor 440); and at least one memory (see, Wu: Fig. 4, Memory 442) storing instructions that, when executed with the at least one processor, cause the first device to:
receive, from a second device, a second message indicating a second channel state (see, Wu: Fig. 9, Step 904 and para. [0095], “At 904, the BS receives one or more second feedback components associated with at least one second CSI feedback from the UE.”; Fig. 10, Step 1006 and para. [0108], “At 1006, for the second CSI feedback stage, the UE subsequently performs a second CSI calculation and reports the 2nd CSI feedback to the BS.”), a second length of the second message is less than a first length of a first message indicating a first channel state previously received from the second device (see, Wu: para. [0107], “FIG. 10 is a call flow diagram 1000 illustrating example signaling and differential CSI feedback reporting over multiple CSI feedback stages (e.g., at least two CSI feedback stages), in accordance with certain aspects of the present disclosure. Each CSI feedback stage (or instance) may refer to a different instance in time in which the UE reports CSI feedback. The CSI feedback reported in a given CSI feedback stage may be based in part, on CSI feedback reported in a previous CSI feedback stage and/or a received CSI-RS (e.g., in the case of the first CSI feedback stage).”);
obtain combined beamforming features (e.g., precoding) of the second device according to a trained combining model associated with the second device (see, Wu: para. [0099], “The differential CSI feedback described herein may include multiple CSI feedback reports, where each CSI feedback report depends in part on a previous CSI feedback. By using a differential CSI feedback scheme, in which each CSI feedback report depends in part on a previous CSI feedback, the BS can more efficiently acquire full channel information (e.g., the combined PMI as well as the CQI) for an accurate approximation of the channel, without performing additional calculations typically associated with CSI feedback schemes in which each CSI feedback report is independent.”, wherein acquiring the combined PMI using the differential CSI feedback scheme is equivalent to the trained combining model.) and based on the second message and historical beamforming features of the second device (see, Wu: Fig. 10, Step 1008 and para. [0108], “At 1008, the BS acquires the 2nd CSI report and sets PMI=PMI1+PMI2. Although not shown, the UE may continue to perform CSI calculations and send CSI reports (e.g., 3rd CSI report, 4th CSI report, and so on) in additional CSI feedback stages (e.g., 3rd CSI feedback stage, 4th feedback stage, and so on). Similarly, although not shown, the BS may receive the CSI reports in the additional CSI feedback stages and determine PMI based on the CSI report received in the current CSI feedback stage and the CSI report(s) received in the previous CSI feedback stage(s).”); and
generate a beam weight for the second device based on the combined beamforming features (see, Wu: Fig. 9, Step 906 and para. [0095], “At 906, the BS determines a precoding to use for MIMO communications based on the first feedback components and the second feedback components. The BS may perform MIMO communications with the UE based on the determined precoding.”; para. [0114], “The PMI codebook may include a weighted combination of L beams.”; Para. [0081], “CSI feedback is generally based on a pre-defined codebook. This may be referred to as implicit CSI feedback. Precoding may be used for beamforming in multi-antenna systems. Codebook based precoding uses a common codebook at the transmitter and receiver. The codebook includes a set of vectors and matrices. The UE calculates a precoder targeting maximum single-user (SU) multiple input multiple output (MIMO) spectrum efficiency. The implicit CSI feedback can include a rank indicator (RI), a PMI, and associated channel quality indicator (CQI) based on the PMI. The PMI includes a W1 precoding matrix and a W2 precoding matrix.”).
Wu does not explicitly teach wherein generating a beam weight for the second device according to a trained beamforming model.
In the same field of endeavor, Mo teaches wherein generating a beam weight for the second device according to a trained beamforming model (see, Mo: para. [0104], “Through training, the system iteratively updates the parameters in the ANN (which are w) to further reduce or minimize the cross-entropy loss. Upon convergence of the machine learning algorithm after iterating, the system extracts the parameters w of the first hidden layer of the ANN as the beamforming weights for the composite beam. Here, system may train the model 800 for each of a plurality of composite beams and directions and encode the determined beamforming weights in a composite beam codebook for use in the network 101.”, supports are found in Fig. 7 and page 14 of 63/227,741.).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Wu in combination of the teachings of Mo in order to identify one or more beamforming weights for transmitting the composite beam wherein the one or more beamforming weights are determined based on machine learning (see, Mo: Abstract and para. [0104], supports are found in Fig. 7 and page 14 of 63/227,741.).
Regarding claim 2:
As discussed above, Wu in view of Mo teaches all limitations in claim 1.
Wu further teaches wherein the historical beamforming features of the second device are obtained based on the first message (see, Wu: para. [0092], “At 808, the UE determines, for at least one second CSI feedback stage, one or more second feedback components associated with at least one second CSI feedback based in part on the first feedback components.”; para. [0095], “At 906, the BS determines a precoding to use for MIMO communications based on the first feedback components and the second feedback components. The BS may perform MIMO communications with the UE based on the determined precoding.”; para. [0099], “The differential CSI feedback described herein may include multiple CSI feedback reports, where each CSI feedback report depends in part on a previous CSI feedback. By using a differential CSI feedback scheme, in which each CSI feedback report depends in part on a previous CSI feedback, the BS can more efficiently acquire full channel information (e.g., the combined PMI as well as the CQI) for an accurate approximation of the channel, without performing additional calculations typically associated with CSI feedback schemes in which each CSI feedback report is independent”).
Regarding claim 3:
As discussed above, Wu in view of Mo teaches all limitations in claim 1.
Wu further teaches wherein the instructions, when executed with the at least one processor, further cause the first device to: update the historical beamforming features of the second device based on the second message (see, Wu: para. [0099], “The differential CSI feedback described herein may include multiple CSI feedback reports, where each CSI feedback report depends in part on a previous CSI feedback. By using a differential CSI feedback scheme, in which each CSI feedback report depends in part on a previous CSI feedback, the BS can more efficiently acquire full channel information (e.g., the combined PMI as well as the CQI) for an accurate approximation of the channel, without performing additional calculations typically associated with CSI feedback schemes in which each CSI feedback report is independent”).
Regarding claim 5:
As discussed above, Wu in view of Mo teaches all limitations in claim 1.
Wu further teaches wherein the instructions, when executed with the at least one processor, further cause the first device to: transmit, to the second device, a reference signal (e.g., CSI reference signal (CSI-RS)) to be used for determining channel state information; with the second device (see Wu: para. [0034], “a UE may receive a CSI reference signal (CSI-RS) from a BS, determine, for a first CSI feedback stage, first feedback component(s) associated with first CSI feedback based on the CSI-RS, and report the first feedback components to the BS.”).
Regarding claim 8:
Claim 8 recites similar features to claim 1 from the perspective of the base station and another UE (i.e., the third device of the instant application) in the network. Therefore, claim 8 is rejected by applying the similar rationale used to reject claim 1 above.
Regarding claim 9:
As discussed above, Wu in view of Mo teaches all limitations in claim 8.
Mo further teaches wherein the instructions, when executed with the at least one processor, cause the apparatus to generate the beam weight for the second device and a further beam weight for the third device according to the trained beamforming model and based on the combined beamforming features of the second device and the combined beamforming features of the third device (see, Mo: para. [0104], “Through training, the system iteratively updates the parameters in the ANN (which are w) to further reduce or minimize the cross-entropy loss. Upon convergence of the machine learning algorithm after iterating, the system extracts the parameters w of the first hidden layer of the ANN as the beamforming weights for the composite beam. Here, system may train the model 800 for each of a plurality of composite beams and directions and encode the determined beamforming weights in a composite beam codebook for use in the network 101.”, supports are found in Fig. 7 and page 14 of 63/227,741.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention that when the trained beamforming model receives the combined beamforming features of both the second device and the third device as input for generating both beam weights, the beam weight generated for the second device is necessarily determined in view of the beam forming features of the third device. In other words, because the beamforming model jointly processes the combined beamforming features of both devices to generate their respective beam weights, the beam weight for the second device is not generated in dependently of the third device, but instead is generated in consideration of the third device. Such joint optimization is a predictable implementation of multi-user beamforming and would have been obvious to a person of ordinary skill in the art.
Regarding claim 30:
Claim 30 recites the method which corresponds to the first device of claim 1, and contains no additional limitations. Therefore, claim 30 is rejected by applying the similar rationale used to reject claim 1 above.
Regarding claim 31:
Claim 31 is directed towards the method of claim 30 that is further limited to perform the features of claim 2. Therefore, claim 31 is rejected by applying the similar rationale used to reject claim 2 above.
Regarding claim 32:
Claim 32 is directed towards the method of claim 30 that is further limited to perform the features of claim 3. Therefore, claim 32 is rejected by applying the similar rationale used to reject claim 3 above.
Regarding claim 34:
Claim 34 is directed towards the method of claim 30 that is further limited to perform the features of claim 5. Therefore, claim 34 is rejected by applying the similar rationale used to reject claim 5 above.
Regarding claim 62:
Claim 62 is directed towards a non-transitory program storage device (see, Wu: Fig. 4, Memory 442) readable with an apparatus (see, Wu: Fig. 4, Base Station 110), tangibly embodying a program of instructions executable with the apparatus for causing an apparatus to perform at least the method of claim 30. Therefore, claim 62 is rejected by applying the similar rationale used to reject claim 30 above.
Claims 6, 7, and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Mo further in view of Vitthaladevuni.
Regarding claim 6:
Claim 6 recites similar features to claim 16. Thus, claim 6 is rejected based on at least the same ground applied to claim 16 above.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Wu in view of Mo in combination of the teachings of Vitthaladevuni in order to perform differential channel state feedback (CSF) (see, Vitthaladevuni: Abstract and para. [0006]).
Regarding claim 7:
Claim 7 recites similar features to claim 17. Thus, claim 7 is rejected based on at least the same ground applied to claim 17 above.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Wu in view of Mo in combination of the teachings of Vitthaladevuni in order to perform differential channel state feedback (CSF) (see, Vitthaladevuni: Abstract and para. [0006]).
Regarding claim 33:
Claim 33 recites similar features to claim 15. Thus, claim 33 is rejected based on at least the same ground applied to claim 15 above.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Wu in view of Mo in combination of the teachings of Vitthaladevuni in order to perform differential channel state feedback (CSF) (see, Vitthaladevuni: Abstract and para. [0006]).
Claims 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Wu in view of Mo further in view of Narayanan Thangaraj et al. (US 2023/0409963 A1, Narayanan Thangaraj).
Regarding claim 12:
As discussed above, Wu in view of Mo teaches all limitations in claim 1.
Wu in view of Mo teaches wherein the instructions, when executed with the at least one processor cause the first device to: receive, from the second device, performance information indicating transmission performance between the second device and the first device (e.g., CQI) (see, Wu: para. [0081], “The implicit CSI feedback can include a rank indicator (RI), a PMI, and associated channel quality indicator (CQI) based on the PMI.”).
Wu in view of Mo does not explicitly teach wherein determining a finetuning indication based on the performance information.
In the same field of endeavor, Narayanan Thangaraj teaches wherein determining a finetuning indication based on the performance information (see, Narayanan Thangaraj: para. [0201], “Based on a condition on the outcome of the third AI component, initiate a training procedure”; para. [0113], “In a solution, the online training procedure may be a fine-tuning procedure. For example, fine tuning a preexisting model to achieve a better performance/accuracy.”).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the teachings of Wu in view of Mo in combination of the teachings of Narayanan Thangaraj in order to achieve a better performance by fine-tuning procedure (see, Narayanan Thangaraj: para. [0113].).
Regarding claim 13:
As discussed above, Wu in view of Mo and Narayanan Thangaraj teaches all limitations in claim 12.
Narayanan Thangaraj further teaches wherein the instructions, when executed with the at least one processor, further cause the first device to:
in accordance with a determination that the finetuning indication indicates to perform a finetuning, transmit, to the second device, a trigger indicating to perform a finetuning for a trained compression model of the second device (see, Narayanan Thangaraj: para. [0145], “The WTRU may be configured to monitor for an explicit or implicit trigger from the network to use the AI component with updated learned parameters from online training. Possibly the trigger may be based on explicit indication carried in a RRC signaling, MAC CE or a DCI. Possibly the trigger may be based on implicit trigger, for e.g. based on indication associated with the identity and/or version of the remote AI component. Possibly such identity may indicate that the network has updated the decoder weights and the WTRU may apply the new encoder weights.”); and perform a finetuning for the trained combining model and the trained beamforming model (see, Narayanan Thangaraj: para. [0118], “Possibly the WTRU may determine from implicit/explicit indication from the network if the decoder weights at the WTRU are outdated. Possibly such indication may be modeled like a toggling bit (e.g. new data indicator (NDI) bit or the like). The WTRU may be configured to utilize at least one aspect of the decoder weights to perform online training. The WTRU may be configured to perform backpropagation over the decoder and encoder components. The WTRU may be configured to update the learned parameters (e.g. encoder and decoder weights) based on online training. The WTRU may be configured to report the updated decoder weights to the network entity.”).
Conclusion
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/JI-HAE YEA/Primary Examiner, Art Unit 2471
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