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 .
Response to Arguments
Applicant's arguments filed 02/04/2026 have been fully considered but they are not persuasive. Applicant argues, on page 6 first paragraph, that 3GPP does not teach after the generation of UE1 analytics, the H-NWDAF further analyses the UE1 Analytics. The examiner respectfully disagrees. 3GPP teaches Collecting data in section 6.38.2.1 by the HPLMN and further teaches analyzing the collected data (by generating the analytics and updating the “UE analytics profile”) in section 6.38.2.2 step 2, then filtering the “UE analytics profile” in section 6.38.2.2 step 7 .
Applicant argues, on page 6 last paragraph, that the action of analyzing is a prerequisite for and distinct from the action of filtering. Since 3GPP step 2 is a prerequisite for and distinct from step 7, 3GPP teaches this argued feature. Thus, 3GPP teaches all the argued limitations of claim 1, and claim 1 is maintained rejected by considering 3GPP as a whole and adding extra relevant portions of 3GPP in the current rejection.
Applicant argues, on page 7 last paragraph, that the above comments apply to independent claims 6, 10, and 13, and concludes that claims 6, 10, and 13 are novel. The examiner respectfully disagrees. As shown above in response to arguments regarding claim 1, 3GPP teaches all the argued limitations. Therefore, independent claims 6, 10, and 13 are not novel and are maintained rejected.
Applicant argues, on page 7 las paragraph, that dependent claims 2-4, 7-8, 11-12, and 14-15 are novel by virtue of the claim’s dependency on one of the independent claims. The examiner respectfully disagrees. Since the independent claims are maintained rejected, dependent claims 2-4, 7-8, 11-12, and 14-15 are maintained rejected.
Claim Rejections - 35 USC § 102
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 6-8, and 13-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by 3GPP TR 23.700-81 v0.3.0 (Study of Enablers for Network Automation for 5G 5G System (5GS); Phase 3 (Release 18), 2022-05).
Regarding claim 6, 3GPP teaches A method performed by a network node of a Visited network operator (6.38.2.2 the V-NWDAF), the method comprising:
transmitting via a core network of the Visited network operator, a request to a Home network operator (3GPP6.38.2.2 3-5. When UE1 attaches to the VPLMN, the V-NWDAF contacts H-NWDAF to retrieve the "UE analytics profile" for UE1), requesting data regarding usage patterns of a subscriber (3GPP6.38.1.3 The UE analytics profile may contain: ... - UE Data usage patterns) that has moved from the Home network to the Visited network ((3GPP 6.38.1.2 A UE from HPLMN roams in a VPLMN network);
acquiring analyzed (3GPP6.38.2.2 2. H-NWDAF generates UE1 analytics or predictions and based on them creates or updates the "UE analytics profile" for UE1)and filtered data (3GPP 6.38.2.2 7. H-NWDAF retrieves VPLMN specific user consent, operator or regulatory filters from UDM and applies them to the retrieved "UE analytics profile" of UE1 to generate a "VPLMN UE analytics profile") regarding requested usage patterns of the subscriber (3GPP 6.38.2.2 8. H-NWDAF provides the "VPLMN UE analytics profile" of UE1 to the V-NWDAF); and
analyzing the acquired information and adapting core network resources and radio network resources for providing services to the subscriber in the Visited network (3GPP 6.38.2.2 9. V-NWDAF uses the obtained "VPLMN UE analytics profile" of UE1 to extract information related to the UE1. V-NWDAF uses this information, as well as data obtained in the VLPMN related to the UE1, to generate analytics related to the UE1 and provide analytics reports to its consumers.) .
Regarding claim 7, 3GPP teaches the method according to claim 6, wherein the analyzed and filtered data includes one or more of the following: usage times, information on radio access technologies, data usage 3GPP6.38.1.3 The UE analytics profile may contain: ... - UE Data usage patterns, video usage, uplink usage, quality-of service 3GPP6.38.1.3 The UE analytics profile may contain: ... - UE QoS / Congestion Experience patterns), slicing network information, and capabilities of a user device of the subscriber.
Regarding claim 8, 3GPP teaches the method according to claim 6, wherein the network node of the Visited network operator further comprises an Artificial Intelligence/Machine Learning (AI/ML) platform for big data analysis (3GPP 6.1.1 TS 23.288 [5] assumes that the NWDAF containing AnLF has a single ML model for inferring analytics).
Regarding claim 13, 3GPP teaches A network node of a Visited network operator (6.38.2.2 the V-NWDAF)comprising a memory and a processor executing instructions from the memory, wherein the network node is configured to:
transmit via a core network of the Visited network operator, a request to a Home network operator (3GPP6.38.2.2 3-5. When UE1 attaches to the VPLMN, the V-NWDAF contacts H-NWDAF to retrieve the "UE analytics profile" for UE1), requesting data regarding usage patterns of a subscriber (3GPP6.38.1.3 The UE analytics profile may contain: ... - UE Data usage patterns) that has moved from the Home network to the Visited network ((3GPP 6.38.1.2 A UE from HPLMN roams in a VPLMN network);
acquire analyzed (3GPP6.38.2.2 2. H-NWDAF generates UE1 analytics or predictions and based on them creates or updates the "UE analytics profile" for UE1)and filtered data (3GPP 6.38.2.2 7. H-NWDAF retrieves VPLMN specific user consent, operator or regulatory filters from UDM and applies them to the retrieved "UE analytics profile" of UE1 to generate a "VPLMN UE analytics profile") regarding requested usage patterns of the subscriber (3GPP 6.38.2.2 8. H-NWDAF provides the "VPLMN UE analytics profile" of UE1 to the V-NWDAF); and
analyze the acquired information and adapting core network resources and radio network resources for providing services to the subscriber in the Visited network (3GPP 6.38.2.2 9. V-NWDAF uses the obtained "VPLMN UE analytics profile" of UE1 to extract information related to the UE1. V-NWDAF uses this information, as well as data obtained in the VLPMN related to the UE1, to generate analytics related to the UE1 and provide analytics reports to its consumers.) . .
Regarding claim 14, 3GPP teaches the network node according to claim 13, further comprising an Artificial Intelligence/Machine Learning (AI/ML) platform for big data analysis (3GPP 6.1.1 TS 23.288 [5] assumes that the NWDAF containing AnLF has a single ML model for inferring analytics). .
Regarding claim 15, 3GPP teaches the network node according to claim 13, further comprising a 5G network data analytics function (NWDAF) (6.38.2.2 the V-NWDAF).
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.
Claim(s) 1-4, and 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP TR 23.700-81 v0.3.0 (Study of Enablers for Network Automation for 5G 5G System (5GS); Phase 3 (Release 18), 2022-05) in view of Yuan et al. (CN 106572482 A).
Regarding claim 1, 3GPP teaches A method performed by a network node of a Home network operator (3GPP 6.38.1.1 NWDAF of HPLMN), the method comprising:
Collecting data regarding usage patterns of a subscriber of said Home network operator (3GPP6.38.2.1 HPLMN collecting data from VPLMN, Figure 6.38.2.1-1: HPLMN collecting data from VPLMN
... H-NWDAF requests data collection via V-NWDAF data retrieval service. It indicates as reporting target one or several UE(s)... and the desired data types or events.
...
3. V-NWDAF collects the data from different NFs/DCCF and aggregates the collected data.
4. V-NWDAF anonymizes or restricts the data based on VPLMN operator polices (that may depend on the HPLMN).
5. V-NWDAF sends the processed data to H-NWDAF. );
analyzing the collected data (3GPP6.38.2.2 2. H-NWDAF generates UE1 analytics or predictions and based on them creates or updates the "UE analytics profile" for UE1)and filtering the collected data (3GPP 6.38.2.2 7. H-NWDAF retrieves VPLMN specific user consent, operator or regulatory filters from UDM and applies them to the retrieved "UE analytics profile" of UE1 to generate a "VPLMN UE analytics profile" with information on the UE1 that can be exposed to the VPLMN.);
receiving, via the core network (3GPP Figure 6.38.2.2-1: VPLMN consuming analytics profile generated by HPLMN), a request from a network node of a Visited network operator (3GPP 6.38.2.2 3-5. When UE1 attaches to the VPLMN, the V-NWDAF contacts H-NWDAF to retrieve the "UE analytics profile" for UE1), requesting data regarding usage patterns of the subscriber (3GPP6.38.1.3 The UE analytics profile may contain: ... - UE Data usage patterns) that has moved from the Home network to the Visited network (3GPP 6.38.1.2 A UE from HPLMN roams in a VPLMN network); and
providing the network node of the Visited network operator, via the core network (3GPP Figure 6.38.2.2-1: VPLMN consuming analytics profile generated by HPLMN), the analyzed and filtered collected data regarding requested usage patterns of the subscriber (3GPP 6.38.2.2 8. H-NWDAF provides the "VPLMN UE analytics profile" of UE1 to the V-NWDAF), for enabling the network node of the Visited network operator to adapt core network resources and radio network resources for providing services to the subscriber in the Visited network (3GPP 6.38.2.2 9. V-NWDAF uses the obtained "VPLMN UE analytics profile" of UE1 to extract information related to the UE1. V-NWDAF uses this information, as well as data obtained in the VLPMN related to the UE1, to generate analytics related to the UE1 and provide analytics reports to its consumers.) . .
3GPP does not explicitly teach
Collecting the data from at least one radio network node of a radio access network, and from a core network.
In a similar endeavor, Yuan et al. teach
Collecting the data from at least one radio network node of a radio access network, and from a core network (Yuan [0017]-[0019] The step of obtaining network element information and user information of the core network includes: Acquire network element information from each network element of the core network, where the network element information includes at least operation status information of the network element; Obtain user signaling information from various network elements in the core network, [0067] Obtain the user's signaling information from each network element of the core network; that is, collect the user's signaling information, such as signaling type and signaling frequency, from each network element of the EPC (eNodeB, HSS/HLR, MME/SGSN, SAE GW/GGSN, PCRF); among which, key information in the signaling message such as user identification and user location is collected.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the examined application to have modified 3GPP by incorporating Yuan et al. collected information to arrive at the invention
The motivation of doing so would have collected useful information.
Regarding claim 2, the combination of 3GPP and Yuan et al. teaches the method according to claim 1, wherein the analyzed and filtered collected data provided to the network node of the Visited network operator includes one or more of the following: usage times, information on radio access technologies, data usage 3GPP6.38.1.3 The UE analytics profile may contain: ... - UE Data usage patterns, video usage, uplink usage, quality-of service 3GPP6.38.1.3 The UE analytics profile may contain: ... - UE QoS / Congestion Experience patterns), slicing network information, and capabilities of a user device of the subscriber.
Regarding claim 3, the combination of 3GPP and Yuan et al. teaches the method according to claim 1, wherein filtering the collected data includes removing subscriber data information considered irrelevant for the Visited network operator (3GPP6.38.2.2 7. H-NWDAF retrieves VPLMN specific user consent, operator or regulatory filters from UDM and applies them to the retrieved "UE analytics profile" of UE1 to generate a "VPLMN UE analytics profile" with information on the UE1 that can be exposed to the VPLMN)..
Regarding claim 4, the combination of 3GPP and Yuan et al. teaches the method according to claim 1, wherein the network node of the Home network operator comprises an Artificial Intelligence/Machine Learning (AI/ML) platform for big data analysis (3GPP 6.1.1 TS 23.288 [5] assumes that the NWDAF containing AnLF has a single ML model for inferring analytics). .
Regarding claim 10, 3GPP teaches A network node of a Home network operator (3GPP 6.38.1.1 NWDAF of HPLMN) comprising a memory and a processor executing instructions from the memory (Note: inherent in a network node), wherein the network node is configured to:
collect data regarding usage patterns of a subscriber of said Home network operator (3GPP6.38.2.1 HPLMN collecting data from VPLMN, Figure 6.38.2.1-1: HPLMN collecting data from VPLMN
... H-NWDAF requests data collection via V-NWDAF data retrieval service. It indicates as reporting target one or several UE(s)... and the desired data types or events.
...
3. V-NWDAF collects the data from different NFs/DCCF and aggregates the collected data.
4. V-NWDAF anonymizes or restricts the data based on VPLMN operator polices (that may depend on the HPLMN).
5. V-NWDAF sends the processed data to H-NWDAF. );
analyze the collected data (3GPP6.38.2.2 2. H-NWDAF generates UE1 analytics or predictions and based on them creates or updates the "UE analytics profile" for UE1)and filtering the collected data (3GPP6.38.2.2 7. H-NWDAF retrieves VPLMN specific user consent, operator or regulatory filters from UDM and applies them to the retrieved "UE analytics profile" of UE1 to generate a "VPLMN UE analytics profile" with information on the UE1 that can be exposed to the VPLMN.);;
receiving, , via the core network (3GPP Figure 6.38.2.2-1: VPLMN consuming analytics profile generated by HPLMN), a request from a network node of a Visited network operator (3GPP 6.38.2.2 3-5. When UE1 attaches to the VPLMN, the V-NWDAF contacts H-NWDAF to retrieve the "UE analytics profile" for UE1), requesting data regarding usage patterns of the subscriber (3GPP6.38.1.3 The UE analytics profile may contain: ... - UE Data usage patterns) that has moved from the Home network to the Visited network (3GPP 6.38.1.2 A UE from HPLMN roams in a VPLMN network); and
provide the network node of the Visited network operator, via the core network (3GPP Figure 6.38.2.2-1: VPLMN consuming analytics profile generated by HPLMN), the analyzed and filtered collected data regarding requested usage patterns of the subscriber (3GPP 6.38.2.2 8. H-NWDAF provides the "VPLMN UE analytics profile" of UE1 to the V-NWDAF), for enabling the network node of the Visited network operator to adapt core network resources and radio network resources for providing services to the subscriber in the Visited network (3GPP 6.38.2.2 9. V-NWDAF uses the obtained "VPLMN UE analytics profile" of UE1 to extract information related to the UE1. V-NWDAF uses this information, as well as data obtained in the VLPMN related to the UE1, to generate analytics related to the UE1 and provide analytics reports to its consumers.) .
3GPP does not explicitly teach
Collecting the data from at least one radio network node of a radio access network, and from a core network.
In a similar endeavor, Yuan et al. teach
Collecting the data from at least one radio network node of a radio access network, and from a core network (Yuan [0017]-[0019] The step of obtaining network element information and user information of the core network includes: Acquire network element information from each network element of the core network, where the network element information includes at least operation status information of the network element; Obtain user signaling information from various network elements in the core network, [0067] Obtain the user's signaling information from each network element of the core network; that is, collect the user's signaling information, such as signaling type and signaling frequency, from each network element of the EPC (eNodeB, HSS/HLR, MME/SGSN, SAE GW/GGSN, PCRF); among which, key information in the signaling message such as user identification and user location is collected.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the examined application to have modified 3GPP by incorporating Yuan et al. collected information to arrive at the invention
The motivation of doing so would have collected useful information.
Regarding claim 11, the combination of 3GPP and Yuan et al. teaches the network node according to claim 10, further comprising an Artificial Intelligence/Machine Learning (AI/ML) platform for big data analysis (3GPP 6.1.1 TS 23.288 [5] assumes that the NWDAF containing AnLF has a single ML model for inferring analytics). .
Regarding claim 12, the combination of 3GPP and Yuan et al. teaches the network node according to claim 10, further comprising a 5G network data analytics function (NWDAF) (3GPP 6.38.1.1 NWDAF of HPLMN).
Allowable Subject Matter
Claim 5 and 9 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.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 5, the combination of 3GPP and Yuan et al. teaches the method according to claim 1, but fails to teach
further comprising informing the subscriber about the data information provided to the network node of the Visited network operator.
Regarding claim 9, 3GPP teaches the method according to claim 6, but fails to teach
further comprising providing the subscriber in the Visited network with information on services in the Visited network, which services are adapted according to the acquired information on usage patterns of the subscriber.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/SAID M ELNOUBI/Examiner, Art Unit 2644