DETAILED ACTION
This Action is in response to Applicant’s amendment filed on 3/30/2026. Claims 1-17 and 19-21 are still pending in the present application. This Action is made FINAL.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-17 and 19-21 are rejected under 35 U.S.C. 102(a)(2) as being
anticipated by Soldati et al. (U.S. Patent Application Publication No. 2023/0276264)
Referring to Claim 1, Soldati et al. disclose a method of performing a network function, the method comprising: receiving first information associated with a user equipment (UE) for a secondary node (SN) change or a primary secondary cell (PSCell) change (pars 129 and 201, assistance information relating to wireless device, secondary node modification; par 2, ML, inference), wherein the first information is treated as inference input for the SN change or the PSCell change; or receiving second information associated with one or more candidate nodes for the SN change or the PSCell change, wherein the second information is treated as inference input for the SN change or the PSCell change (pars 36, 129 and 133, assistance information related to configuration at secondary node, secondary node modification; par 2, ML, inference); and determining an action regarding the SN change or the PSCell change with a machine learning (ML) model by performing inference based on the first information or the second information as inference inputs to the ML model (pars 30, 36, 127 and 201, ML model, secondary RAN node modification procedure, also, acknowledgement; par 2, ML, inference).
Referring to Claim 2 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: triggering the SN change or the PSCell change based on a determined action (pars 127 and 201, secondary RAN node modification procedure).
Referring to Claim 3 as applied to Claim 1 above, Soldati et al. disclose the method, wherein the first information is received from the UE directly and/or from a master node (pars 194-201, assistance information from UE), and includes at least one of the following information: one or more measurement results of one or more candidate cells managed by the one or more candidate nodes; mobility history information; predicted quality of service (QoS), or traffic parameters of the one or more candidate nodes; QoS or traffic parameters of the one or more candidate nodes in a past time period; a predicted cell load of each of the one or more candidate cells; a cell load of each of the one or more candidate cells in a past time period; a predicted SN change frequency or a predicted PSCell change frequency; a SN change frequency or a PSCell change frequency in a past time period; and a predicted probability of accessing to the one or more candidate cells (pars 152-178, information, e.g. channel quality, etc.).
Referring to Claim 4 as applied to Claim 1 above, Soldati et al. disclose the method, wherein the second information is received from the one or more candidate nodes and/or from a master node and/or from a source SN, or determined by a source secondary node, and wherein the second information includes at least one of the following information in the one or more candidate nodes or in one or more candidate cells managed by the one or more candidate nodes: a number of active UEs in a past time period; resource utilization in the past time period; a capacity in the past time period; QoS or traffic parameters in the past time period; RRC connections in the past time period; a cell load in the past time period; SN change frequency in the past time period; a predicted number of active UEs; predicted resource utilization; a predicted capacity; predicted QoS or predicted traffic parameters; predicted RRC connections; a predicted cell load; predicted SN change frequency; and a predicted probability of being accessed by the UE (pars 133 and 152-178, information, e.g. channel quality, etc.).
Referring to Claim 5 as applied to Claim 1 above, Soldati et al. disclose the method, wherein the action includes at least one of the following information: a determination for whether performing a SN change or a PSCell change or not; a determination of a time for performing the SN change or the PSCell change; a determination for performing an inter-SN PSCell change or an intra-SN PSCell change; a determination of a target node for the SN change; a determination of a target PSCell for the PSCell change; a determination of SN change or inter-SN PSCell change parameters; a determination of PSCell change or intra-SN PSCell change parameters; and a determination for activating or deactivating a target secondary cell group corresponding to a target SN (pars 127 and 201, secondary RAN node modification procedure).
Referring to Claim 6 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: receiving a first feedback from the UE directly or indirectly, wherein the first feedback includes at least one of the following information: a time period from a time point when the UE accessed to a target SN or a target PSCell to a time point when the UE is out of a coverage of the target SN or the target PSCell; QoS level latency, a QoS level packet loss rate, or a QoS level jitter in the target SN or a target PSCell; one or more traffic patterns of the UE in the target SN or the target PSCell; resource utilization of the UE in the target SN or the target PSCell; one or more service requirements of the UE; and one or more connectivity configurations of the UE (par 132, UE performance, etc).
Referring to Claim 7 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: receiving a second feedback from a target SN and/or from a master node, or determining the second feedback, wherein the second feedback includes at least one of the following information: a time period from a time point when the UE accessed to the target SN or a target PSCell to a time point that when UE is out of a coverage of the target SN or the target PSCell; QoS level latency, a QoS level packet loss rate, or a QoS level jitter associated with the target SN or the target PSCell; radio efficiency associated with the target SN or the target PSCell; mobility history information associated with the target SN or the target PSCell; and one or more connectivity configurations applied by the target SN or the target PSCell (par 185, configuration).
Referring to Claim 8 as applied to Claim 6 above, Soldati et al. disclose the method, further comprising: retraining the ML model based on the first feedback and/or the second feedback and/or a determined action; and updating the ML model (pars 132 and 185, information, configuration, ML).
Referring to Claim 9 as applied to Claim 6 above, Soldati et al. disclose the method, further comprising: at least transmitting the first feedback, or the second feedback or a determined action, to a host which provides the ML model, for retraining the ML model (pars 132 and 185, information, configuration, ML).
Referring to Claim 10 as applied to Claim 9 above, Soldati et al. disclose the method, further comprising: receiving an updated ML model (pars 132, 185, and 191, ML model, update).
Referring to Claim 11 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: at least transmitting a first request to a master node or to the UE for the first information; and/or at least transmitting a second request to a master node or to the one or more candidate nodes for the second information (pars 133 and 201, request).
Referring to Claim 12 as applied to Claim 11 above, Soldati et al. disclose the method, wherein the one or more candidate nodes are determined based on the first information (pars 132, 143 and 148, second).
Referring to Claim 13 as applied to Claim 11 above, Soldati et al. disclose the method, wherein the first request and the second request are transmitted in one message or transmitted in two different messages (pars 133 and 201, request).
Referring to Claim 14 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: at least transmitting a third request to the UE, or a master node (MN), or a target SN, for a first feedback; and/or at least transmitting a fourth request to the MN or the target SN for a second feedback (par 131, request).
Referring to Claim 15 as applied to Claim 14 above, Soldati et al. disclose the method, wherein the third request and the fourth request are transmitted in one message or transmitted in two different messages (par 131, request).
Referring to Claim 16 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: transmitting a fifth request for the ML model to a host which trains the ML model for SN change or PSCell change (pars 132, 133, 185, 191, and 201. Request, ML model, update).
Referring to Claim 17 as applied to Claim 1 above, Soldati et al. disclose the method, further comprising: applying the ML model associated with the SN change or the PSCell change of the UE (pars 30, 36, 127 and 201, ML model, secondary RAN node modification procedure).
Referring to Claim 19, Soldati et al. disclose an apparatus for performing a network function, the apparatus comprising: at least one memory (figures 13 and 15); and at least one processor (figures 13 and 15) coupled with the at least one memory and configured to cause the apparatus to: receive first information associated with a user equipment (UE) for a secondary node (SN) change or a primary secondary cell (PSCell) change, wherein the first information is treated as inference input for the SN change or the PSCell change (pars 129 and 201, assistance information relating to wireless device, secondary node modification; par 2, ML, inference); or receive second information associated with one or more candidate nodes for the SN change or the PSCell change, wherein the second information is treated as inference input for the SN change or the PSCell change (pars 36, 129 and 133, assistance information related to configuration at secondary node, secondary node modification; par 2, ML, inference); and determine an action regarding the SN change or the PSCell change with a machine learning (ML) model by performing inference based on the first information or the second information as inference inputs to the ML model (pars 30, 36, 127 and 201, ML model, secondary RAN node modification procedure, also, acknowledgement; par 2, ML, inference).
Referring to Claim 20 as applied to Claim 19 above, Soldati et al. disclose the apparatus, further comprising: triggering the SN change or the PSCell change based on a determined action (pars 127 and 201, secondary RAN node modification procedure).
Referring to Claim 21 as applied to Claim 19 above, Soldati et al. disclose the apparatus, wherein the first information is received from the UE directly and/or from a master node (pars 194-201, assistance information from UE), and includes at least one of the following information: one or more measurement results of one or more candidate cells managed by the one or more candidate nodes; mobility history information; predicted quality of service (QoS), or traffic parameters of the one or more candidate nodes; QoS or traffic parameters of the one or more candidate nodes in a past time period; a predicted cell load of each of the one or more candidate cells; a cell load of each of the one or more candidate cells in a past time period; a predicted SN change frequency or a predicted PSCell change frequency; a SN change frequency or a PSCell change frequency in a past time period; and a predicted probability of accessing to the one or more candidate cells (pars 152-178, information, e.g. channel quality, etc.).
Response to Arguments
Applicant's arguments filed 3/30/2026 have been fully considered but they are not persuasive. Applicant argues on pages 11 and 12 of the Remarks that Soldati et al. do not disclose the inference inputs as claimed, as Soldati et al. discloses an inference phase but not such specific inputs. Examiner respectfully disagrees. Soldati et al. discloses in par 2 that ML involves an inference phase. Pars 133 and 201 shows information received and SN modification being performed. Further, par 129 shows updating existing procedures such as secondary node change to include exchange of ML related information.
Examiner would like to further point out that Soldati’s information reception and change implementation itself (e.g. in par 201) reads on the claimed “inference input for SN change/ PSCell change”. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
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 extension fee 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 SUHAIL KHAN whose telephone number is (571)270-7187. The examiner can normally be reached on M-TH 8:30am-6:30pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rafael Perez-Gutierrez can be reached on 5712727915. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, Applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
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/Suhail Khan/
Primary Examiner, Art Unit 2642
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