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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on January 12, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-3, 10-12, 15-17, 24-26, 35 and 36 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Veijalainen et al, U.S. Patent Application Publication No. 20230345271 A1 (hereinafter Veijalainen).
Regarding Claim 1, Veijalainen discloses an information transmission method, performed by a user equipment (UE) (e.g., ¶ [0068] According to a variation of the procedure shown in FIG. 5… an exemplary method according to example embodiments may comprise an operation of forwarding said… prediction result and/or said behavior result… towards a network node), comprising: determining, through a prediction model run by the UE (e.g., ¶ [0062] As shown in FIG. 5, a procedure according to example embodiments comprises an operation of receiving (S51) information on a predictive model [e.g. an ML model] related to a radio resource management function), a prediction result of radio resource management (RRM) according to configuration information (e.g., ¶ [0058] For the explanation of example embodiments, it is assumes that a UE is configured with a ML model to run a certain radio resource management (RRM) function; e.g., ¶ [0062] an operation of obtaining (S53) difference determination information [e.g. a loss function] on difference determination with respect to a predictive model prediction and said intended behavior…determining (S55) a prediction result based on said network condition and said information on said predictive model); and reporting the prediction result to an access network device according to the configuration information (e.g., FIG. 5, ¶ [0068] According to a variation of the procedure shown in FIG. 5… forwarding said… prediction result and/or said behavior result… towards a network node).
Regarding Claim 2, Veijalainen discloses all the limitations of the method according to claim 1.
Veijalainen discloses wherein the configuration information comprises at least one of: a prediction object configuration, indicating a corresponding prediction object predicted by the prediction model; a reporting configuration, indicating a configuration for reporting the prediction result; a prediction identifier, indicating the prediction result; a prediction quantity configuration, indicating a configuration of the prediction result; a prediction start period, indicating a first time domain range of the prediction model run by the UE; a prediction window length, indicating a second time domain range corresponding to the prediction result; a report result configuration, indicating a configuration of the prediction result; or a model configuration, indicating the prediction model (e.g., ¶ [0058] UE is configured with a ML model to run a certain radio resource management (RRM) function; e.g., ¶ [0131] UE can be configured to report (or log and report) only the loss values, or average loss, for the network to decide whether it is safe to activate the model; e.g., ¶ [0136] FIG. 10 demonstrates the steps for loss calculation. First, network configures UE with the predictive handover model (step 1 of the above-outlined implementation structure) [Examiner reasons that these citations may at least be interpreted as a configured prediction object, or a model configuration, indicating the prediction model]).
Regarding Claim 3, Veijalainen discloses all the limitations of the method according to claim 2.
Veijalainen discloses wherein the prediction object configuration indicates at least one of: a cell; a frequency point; a cell blacklist, comprising an identifier of a cell not to be predicted; or a cell whitelist, comprising an identifier of a cell to be predicted (e.g., ¶ [0126] For instance, for predictive handover, according to example embodiments, the network can configure the UE to calculate a mean square error (MSE) between RSRP of the predicted cell for handover and of the strongest cell. If handovers are predicted towards weak cells, the loss would indicate that the model is probably not working as it should, and data can be collected from these areas where the model is probably not working as it should. This approximation can be further enhanced e.g. by adding penalty from number of handovers etc. which, according to example embodiments, is then part of the configuration [Examiner reasons that this citation may at least be interpreted as the configured prediction object being a cell]).
Regarding Claim 10, Veijalainen discloses all the limitations of the method according to claim 2.
Veijalainen discloses wherein the report result configuration indicates at least one of: a format of the reported prediction result; a type of the reported prediction result; a cell corresponding to the prediction result; or a frequency point corresponding to the prediction result (e.g., ¶ [0126] For instance, for predictive handover, according to example embodiments, the network can configure the UE to calculate a mean square error (MSE) between RSRP of the predicted cell for handover and of the strongest cell. If handovers are predicted towards weak cells, the loss would indicate that the model is probably not working as it should, and data can be collected from these areas where the model is probably not working as it should. This approximation can be further enhanced e.g. by adding penalty from number of handovers etc. which, according to example embodiments, is then part of the configuration [Examiner reasons that this citation may at least be interpreted as the configured prediction object being a cell]).
Regarding Claim 11, Veijalainen discloses all the limitations of the method according to claim 2.
Veijalainen discloses wherein the model configuration indicates at least one of: the prediction model; a configuration parameter of the prediction model; or initial data used for training the prediction model (e.g., ¶ [0056] As a first step towards a solution for addressing the above-discussed problems and disadvantages, for logging measurements/ML-training data, it might be considered to collect data with minimization of drive tests (MDT). This means that a UE collects the measurements all the time, or logging is triggered by measurement thresholds. The threshold could be configured to log on cell edges; e.g., ¶ [0126] For instance, for predictive handover, according to example embodiments, the network can configure the UE to calculate a mean square error (MSE) between RSRP of the predicted cell for handover and of the strongest cell. If handovers are predicted towards weak cells, the loss would indicate that the model is probably not working as it should, and data can be collected from these areas where the model is probably not working as it should. This approximation can be further enhanced e.g. by adding penalty from number of handovers etc. which, according to example embodiments, is then part of the configuration [Examiner reasons that these citations may at least be interpreted as a configuration parameter of the prediction model, or initial data used for training the prediction model]).
Regarding Claim 12, Veijalainen discloses all the limitations of the method according to claim 1.
Veijalainen discloses wherein the prediction result comprises at least one of: a prediction result of RRM of the UE; a prediction result of RRM of a serving cell where the UE is located; or a prediction result of RRM of a neighboring cell of the UE, wherein the prediction result of RRM of the neighboring cell of the UE comprises a probability that handover failure occurs when the UE is handed over to the neighboring cell (e.g., ¶ [0058] For the explanation of example embodiments, it is assumes that a UE is configured with a ML model to run a certain radio resource management (RRM) function; e.g., ¶ [0062] an operation of obtaining (S53) difference determination information [e.g. a loss function] on difference determination with respect to a predictive model prediction and said intended behavior…determining (S55) a prediction result based on said network condition and said information on said predictive model; e.g., ¶ [0099] [0099] 1. The UE is provided with ML model… responsible of an RRM function; e.g., ¶ [0124] a standard might define that the UE should be able to evaluate a channel prediction validity with a certain accuracy. In this case, according to example embodiments, the UE feedbacks capability of validating a certain RRM function. In response thereto, according to example embodiments, the network may associate the UE implemented validity function with a ML model [Examiner reasons that these citations may at least be interpreted as a configuration parameter of the prediction model with respect to RRM measurements]).
Regarding Claim 15, Veijalainen discloses an information transmission method, performed by an access network device, comprising: sending configuration information, wherein the configuration information is used by a prediction model run by a user equipment (UE) to determine a prediction result of radio resource management (RRM) (e.g., FIG. 6, steps S6-S63, ¶ [0080] network node (e.g., FIGS. 3-4) transmits, towards a mobile terminal, information on radio resource management function predictive model [with associated configuration]).
Regarding Claim 16, Veijalainen discloses all the limitations of the method according to claim 15.
The functional limitations of Claim 16 are similar to claim 2. Therefore, the reasoning used in the examination of claim 2 shall be applied to claim 16.
Regarding Claim 17, Veijalainen discloses all the limitations of the method according to claim 16.
The functional limitations of Claim 17 are similar to claim 3. Therefore, the reasoning used in the examination of claim 3 shall be applied to claim 17.
Regarding Claim 24, Veijalainen discloses all the limitations of the method according to claim 16.
The functional limitations of Claim 24 are similar to claim 10. Therefore, the reasoning used in the examination of claim 10 shall be applied to claim 24.
Regarding Claim 25, Veijalainen discloses all the limitations of the method according to claim 16.
The functional limitations of Claim 25 are similar to claim 11. Therefore, the reasoning used in the examination of claim 11 shall be applied to claim 25.
Regarding Claim 26, Veijalainen discloses all the limitations of the method according to claim 15.
The functional limitations of Claim 26 are similar to claim 12. Therefore, the reasoning used in the examination of claim 12 shall be applied to claim 26.
Regarding Claim 35, Veijalainen discloses a user equipment (UE), comprising: a processor; and a memory storing instructions executable by the processor (e.g., FIGS. 1, 2, ¶ [0030] apparatus of a mobile terminal, the apparatus comprising at least one processor, at least one memory including computer program code, and at least one interface configured for communication with at least another apparatus, the at least one processor, with the at least one memory and the computer program code) wherein the processor is configured to perform operations that are functionally similar to the method of claim 1. Therefore, the reasoning used in the examination of claim 1 shall be applied to claim 35.
Regarding Claim 36, Veijalainen discloses an access network device, comprising: a processor; and a memory storing instructions executable by the processor (e.g., FIGS. 3, 4, ¶ [0031] an apparatus of a network node, the apparatus comprising at least one processor, at least one memory including computer program code, and at least one interface configured for communication with at least another apparatus, the at least one processor, with the at least one memory and the computer program code) wherein the processor is configured to perform the method according to claim 15.
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.
The factual inquiries 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.
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.
Claims 5, 7, 8, 19, 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Veijalainen in view of DaSilva et al, U.S. Patent Application Publication No. 20230025432 A1 (hereinafter DaSilva.
Regarding Claim 5, Veijalainen discloses all the limitations of the method according to claim 2.
Veijalainen does not expressly disclose wherein the reporting configuration indicates a criterion for reporting the prediction result, and the criterion for reporting the prediction result comprises at least one of: a period for reporting the prediction result; a number of times for reporting the prediction result a tripper signaling triggering reporting of the prediction result; or a trigger event triggering reporting of the prediction result.
DaSilva discloses wherein the reporting configuration indicates a criterion for reporting the prediction result, and the criterion for reporting the prediction result comprises at least one of: a period for reporting the prediction result; a number of times for reporting the prediction result; a tripper signaling triggering reporting of the prediction result; or a trigger event triggering reporting of the prediction result (e.g., ¶ [0213] The UE 101 may report mobility prediction information periodically, where the first network node 403a may have configured periodicity and/or pre-determined slots where these predictions are to be reported. This may be configured via RRC signaling from a network, for example, in a ReportConfig structure where there may be a new report type called periodicalPredictions; e.g., ¶ [0214] The parameters configured, e.g. in PeriodicalPredictionReportConfig above, indicate what is to be predicted and comprised in the measurement report predictions [Examiner reasons that these citations may at least be interpreted as the configuration indicating a period for reporting the prediction result; a number of times for reporting the prediction result]).
It would have been obvious to one of ordinary skill in the art at the time of the filing date to combine the disclosure of determining, through a prediction model run by the UE, a prediction result and reporting the prediction result to an access network device according to the configuration information, as disclosed by Veijalainen, with the disclosure of the configuration comprising at least a period for reporting the prediction result, or a periodicity for reporting the prediction result, as disclosed by DaSilva. The motivation to combine would have been to improve the robustness at handover (DaSilva: e.g., ¶ [0066]).
Regarding Claim 7, Veijalainen discloses all the limitations of the method according to claim 2.
Veijalainen does not expressly disclose wherein, a prediction identifier indicates the prediction object and at least one of following in a correspondence: the reporting configuration; the prediction quantity configuration; the prediction start period; the prediction window length; the report result configuration; or a model configuration.
DaSilva discloses wherein, the prediction identifier indicates the prediction object and at least one of following in a correspondence: the reporting configuration; the prediction quantity configuration; the prediction start period; the prediction window length; the report result configuration; or a model configuration (e.g., ¶ 0214] [0222] Regarding the configuration of measurement reporting predictions, the UE may be configured to perform measurements and report measurement periodically, e.g. by being configured in ReportConfigNR with report type periodical, and in addition to perform predictions and comprise measurement predictions in the periodic measurement reports e.g. based on an additional configuration in PeriodicalPredictionReportConfig [Examiner reasons that these citations may at least be interpreted as the configuration indicating a prediction identifier indicating the prediction identifier (i.e., an identifier for the measurement report that associates with the predicted measurements) and reporting configuration (e.g., periodicity)]).
It would have been obvious to one of ordinary skill in the art at the time of the filing date to combine the disclosure of determining, through a prediction model run by the UE, a prediction result and reporting the prediction result to an access network device according to the configuration information, as disclosed by Veijalainen, with the disclosure of the configuration comprising an identifier and at least a period for reporting the prediction result, or a periodicity for reporting the prediction result, as disclosed by DaSilva. The motivation to combine would have been to improve the robustness at handover (DaSilva: e.g., ¶ [0066]).
Regarding Claim 8, Veijalainen discloses all the limitations of the method according to claim 2.
Veijalainen does not expressly disclose wherein, the prediction quantity configuration indicates a type of the prediction result; or the prediction start period indicates a period for running the prediction model run by the UE.
DaSilva discloses wherein, the prediction quantity configuration indicates a type of the prediction result; or the prediction start period indicates a period for running the prediction model run by the UE (e.g., ¶ [0213] The UE 101 may report mobility prediction information periodically, where the first network node 403a may have configured periodicity and/or pre-determined slots where these predictions are to be reported. This may be configured via RRC signaling from a network, for example, in a ReportConfig structure where there may be a new report type called periodicalPredictions, as shown below: [Examiner reasons that these citations may at least be interpreted as type of the prediction result]).
It would have been obvious to one of ordinary skill in the art at the time of the filing date to combine the disclosure of determining, through a prediction model run by the UE, a prediction result and reporting the prediction result to an access network device according to the configuration information, as disclosed by Veijalainen, with the disclosure of the configuration comprising a type of prediction result, as disclosed by DaSilva. The motivation to combine would have been to improve the robustness at handover (DaSilva: e.g., ¶ [0066]).
Regarding Claim 19, Veijalainen discloses all the limitations of the method according to claim 16.
The functional limitations of Claim 19 are similar to claim 5. Therefore, the reasoning used in the examination of claim 5 shall be applied to claim 19.
Regarding Claim 21, Veijalainen discloses all the limitations of the method according to claim 16.
The functional limitations of Claim 21 are similar to claim 7. Therefore, the reasoning used in the examination of claim 7 shall be applied to claim 21.
Regarding Claim 22, Veijalainen discloses all the limitations of the method according to claim 16.
The functional limitations of Claim 22 are similar to claim 8. Therefore, the reasoning used in the examination of claim 8 shall be applied to claim 22.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. References considered relevant to this application are listed in the attached "Notice of References Cited” (PTO-892).
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/VLADISLAV Y AGUREYEV/Examiner, Art Unit 2471