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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7 January 2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4 November 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
Applicant’s amendment, filed 7 January 2026, has been entered and carefully considered.
Claims 1, 5, 10, 14, 15, 19 and 20 are amended.
Claims 4, 16 and 17 are canceled.
Claims 1-3, 5-15 and 18-20 are currently pending.
The outstanding objections to Claims 1, 19 and 20 are withdrawn in light of Applicant’s amendment to said claims.
The outstanding rejection of Claims 1-3, 5-15 and 18-20 under 35 U.S.C. 103 is withdrawn in light of Applicant’s amendment to at least Claims 1, 19 and 20.
Response to Arguments
Applicant’s arguments with respect to claims 1, 8, 15, 19 and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
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 1-3, 5-7, 9-15 and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dao et al (WIPO Publication 2020/069662), hereinafter Dao ‘662, in view of Dao et al (United States Pre-Grant Publication 20190253917), hereinafter Dao ‘917, and Wang et al (United States Pre-Grant Publication 20210076250), hereinafter Wang.
Regarding Claim 1, Dao ‘662 discloses an apparatus, comprising:
at least one memory (Figure 9, 920 and paragraph 0251); and
at least one processor (Figure 9, 910 and paragraph 0251) coupled with the at least one memory (Figure 9 and paragraph 0251) and configured to cause the apparatus to:
receive an actual and expected characteristics of a user equipment (“UE”) that describes a context of the UE (paragraphs 0141-0142 – the NWDAF receives travel route information of the UE including one or multiple ordered road segments)
obtain, based on the actual or expected characteristic of the UE, a data analytics model describing at least one expected network condition of a radio access network (“RAN”) node (paragraph 0141 – the NWDAF performs data analytics to provide statistic network QoS information according to the current and future geographical location)
determine an expected quality of service (“QoS”) adaptation pattern, based on the obtained data analytics model, at a mobile edge computing entity within a service area of the UE, the QoS adaptation pattern comprising a sequence of QoS profiles to be associated with a QoS flow for the UE over a time interval, wherein each of the QoS profile comprises a set of QoS attributes, and wherein the sequence of QoS profiles indicates a time duration or geographical area over which a corresponding set of QoS attributes is to be applied (paragraphs 0142-0146 - the network may provide network QoS information for each road segment of each route, such as road segments on proposed alternative routes (see paragraphs 0143-0145), where, the network QoS information comprises QoS parameters, statistics, and critical road sub-segments where the QoS may drop below a critical threshold; the claimed alternative limitation “time duration or geographical area” is met by this disclosure);
and communicate the expected QoS adaptation pattern for the QoS flow of the UE to the UE and/or at least one network node associated with the QoS flow (paragraph 0168 and Figure 6, wherein the network QoS information response is sent to the UE via the SMF, AMF and RAN).
However, Dao ‘662 does not disclose the QoS configuration parameters comprise a QoS flow identity ("ID"), a list of QoS profiles, and priorities of QoS profiles or determining the QoS adaptation pattern on the QoS configuration parameters. In an analogous art, Dao ‘917 discloses this. Specifically, Dao ‘917 discloses an SMF providing one or more QoS profiles to a RAN node, where the profiles include parameters such as a QoS Identifier and an Allocation and Retention Priority (paragraph 0101). Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine Dao ‘662 and Dao ‘917. One would have been motivated to do so in order to improve reporting of events in which QoS parameters of delay critical GBR QoS flows are violated (refer to paragraph 0005 of Dao ‘917).
However, the aforementioned references do not disclose receiving the QoS configuration parameters from a serving RAN node within a service area of an edge data network. In an analogous art, Wang discloses this. Specifically, Wang discloses a UE receiving QoS configuration from a RAN in the service area of a Mobile Edge Computing server (Figure 8 and paragraphs 0056-0058). Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine Dao ‘662 / Dao ‘917 with Wang. One would have been motivated to do so in order to lower latency in 5G networks (refer to paragraph 0003 of Wang).
Regarding Claim 2, Dao ‘662 further discloses the at least one processor is configured to cause the apparatus to receive a subscription request from the entity to be notified of the expected QoS adaptation pattern (paragraphs 0047-0049, wherein the SMF may request or subscribe for statistical QoS values based on values previously provided to the NWDAF).
Regarding Claim 3, Dao ‘662 discloses the subscription request comprises a type of data analytics model to be used, types of QoS analytics to be used, an expected accuracy for the data analytics model or training configuration for the data analytics model (paragraphs 0042 and 0047-0049, wherein the SMF may request or subscribe for statistical QoS values based on values previously provided to the NWDAF, and include information such as type of QoS flow, current QoS parameters in use (i.e., types of QoS analytics to be used)).
Regarding Claim 5, Dao ‘662 further discloses the QoS configuration parameters further comprise a geographical area, a time validity, a hysteresis threshold, or a single network slice selection assistance information (“S-NSSAI”) (paragraphs 0047-0049, wherein the SMF may request or subscribe for statistical QoS values based on values previously provided to the NWDAF, such as S-NSSAI, thereby meeting the claimed alternative limitation).
Regarding Claim 6, Dao ‘662 further discloses the at least one processor is configured to cause the apparatus to receive one or more radio parameters from a serving RAN node within the service area of an edge data network and updating the data analytics model with latest channel information (paragraphs 00104, wherein then NWDAF receives current network conditions (such as QoS levels) in order to perform data analytics).
Regarding Claim 7, Dao ‘662 further discloses the one or more radio parameters comprise channel state information (“CSI”) measurements, radio resource management (“RRM”) measurements, radio link monitoring (“RLM”) measurements, radio resource control (“RRC”) parameters for a user, RRC parameters for a cell, RRM function outputs, parameters for a network slice, or UE context parameters (paragraph 0047, wherein network slice information (e.g., S-NSSAI) and network slice instance identifier (NSI ID) are provided).
Regarding Claim 9, Dao ‘662 further discloses the actual or expected characteristics of the UE comprises a UE mobility pattern, the UE mobility pattern comprising at least one of the following parameters: a sequence of location coordinates for the UE for different time instances within a given area, a sequence of cell handovers for different time instances within a given area, an estimated trajectory of the UE, a high definition (“HD”) location map, and an expected speed or velocity of the UE (paragraphs 0045-0046, wherein the travel distance, speed, and location information for the UE are provided; paragraph 0141 – the NWDAF performs data analytics to provide statistic network QoS information according to the current and future geographical location).
Regarding Claim 10, Dao ‘662 further discloses the expected QoS adaptation pattern indicates one of: a current QoS profile is expected to remain the same for a particular time duration within the time interval or geographical area; a current QoS profile is expected to downgrade to a different QoS profile at a particular time instance, within the time interval, for a particular time duration or geographical area; and a current QoS profile is expected to upgrade to a different QoS profile at a particular time instance, within the time interval, for a particular time duration or geographical area (paragraph 0049, wherein locations/road segments where the UE may experience lower QoS than a QoS threshold are provided; paragraphs 0142-0146 - the network may provide network QoS information for each road segment of each route, such as road segments on proposed alternative routes (see paragraphs 0143-0145)).
Regarding Claim 11, Dao ‘662 further discloses the expected QoS adaptation pattern is communicated to the RAN node that serves the UE (paragraph 0041, wherein the QoS information is provided to/from the UE via the radio access node (RAN)).
Regarding Claim 12, Dao ‘662 further discloses the at least one processor is configured to cause the apparatus to apply QoS flow remapping for the QoS flow of the UE based on the sequence of QoS profiles of the expected QoS adaptation pattern at the RAN node (paragraph 0058, the QoS notification control message from the RAN indicates new values of supported QoS parameters).
Regarding Claim 13, Dao ‘662 further discloses the expected QoS adaptation pattern is communicated to an application client executing on the UE (Figure 9, paragraphs 0251-0253, wherein the UE comprises a processor, memory, storage, I/O interface, network interface, and transceiver to perform the disclosed QoS adaptation)
Regarding Claim 14, Dao ‘662 further discloses the at least one processor is configured to cause the apparatus to update local QoS policies on the UE in response to receiving the expected QoS adaptation pattern (paragraph 0058, the QoS notification control message from the RAN indicates new values of supported QoS parameters), wherein updating the local QoS policies comprises at least one of: sending a PDU session modification request to an access and mobility management function (“AMF”) or session management function (“SMF”) that includes the QoS expected adaptation pattern to indicate a change of the QoS profiles for the QoS flow; and sending the expected QoS adaptation pattern to a RAN node for QoS adaptation using the one or more QoS profiles of the expected QoS adaptation pattern (paragraph 0122 and Figure 4, wherein the network QoS information response is sent to the UE via the SMF, AMF and RAN).
Regarding Claim 15, the combination of Dao ‘662, Dao ‘917 and Wang further discloses the apparatus comprises an edge enabler server, wherein the mobile edge computing entity is a functionality of the edge enabler server, and wherein the expected QoS adaptation pattern is communicated to an edge enabler client executing on the UE (refer to Figure 8 and paragraphs 0056-0058 of Wang). Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to further combine Dao ‘662 / Dao ‘917 with Wang. One would have been motivated to do so in order to lower latency in 5G networks (refer to paragraph 0003 of Wang).
Regarding Claim 18, Dao ‘662 further discloses the actual or expected characteristic of the UE comprises UE perception data, the UE perception data comprising parameters indicative of sensor data as perceived by the UE along its expected route (paragraph 0162, wherein the UE provides current geographic location and expected start/end points for the travel route).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Dao ‘662 in view of Dao ‘917 and Wang, as applied to Claim 1 above, and further in view of Sharma et al (United States Pre-Grant Publication 2024/0064105), hereinafter Sharma. The combination of Dao ‘662, Dao ‘917 and Wang discloses all of the limitations of Claim 1, as described above. However, the aforementioned references do not disclose the data analytics model comprises an artificial intelligence model that is trained for expected RAN resource conditions or expected wireless backhaul resource conditions. In an analogous art, Sharma discloses this (paragraph 0145, wherein the NWDAF is implemented using AI to predict congestion periods). Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine Dao ‘662 / Dao ‘917 / Wang with Sharma. One would have been motivated to do so in order to manage network exposure function traffic congestion in 5G networks (paragraphs 0002 and 0014-0016 of Sharma).
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Dao ‘662 in view of Dao et al (United States Pre-Grant Publication 20200145876), hereinafter Dao ‘876, and Dao ‘917.
Dao ‘662 discloses a UE comprising:
at least one memory (Figure 9, 920 and paragraph 0251); and
at least one processor (Figure 9, 910 and paragraph 0251) coupled with the at least one memory (Figure 9 and paragraph 0251) and configured (to) cause the UE to:
transmit an actual or expected characteristic the UE that describes a context of the UE ((paragraphs 0141-0142 – the NWDAF receives travel route information of the UE including one or multiple ordered road segments);
receive an expected quality of service (“QoS”) adaptation pattern, the expected QoS adaptation pattern generated by a data analytics model based on actual or expected characteristic of the UE, the expected QoS adaptation pattern comprising a sequence of QoS profiles to be associated with a QoS flow for the UE over a time interval, wherein each of the QoS profile comprises a set of QoS attributes, and wherein the sequence of QoS profiles indicates a time duration or geographical area over which a corresponding set of QoS attributes is to be applied (paragraph 0141 – the NWDAF performs data analytics to provide statistic network QoS information according to the current and future geographical location; paragraphs 0142-0146 - the network may provide network QoS information for each road segment of each route, such as road segments on proposed alternative routes (see paragraphs 0143-0145), where, the network QoS information comprises QoS parameters, statistics, and critical road sub-segments where the QoS may drop below a critical threshold; the claimed alternative limitation “time duration or geographical area” is met by this disclosure).
However, Dao ‘662 does not disclose updat(ing) at least one local QoS policy at a communication part of the UE based on the expected QoS adaptation pattern; and at least one of: transmit(ting) a packet data unit (“PDU”) session modification request to a core network, the request comprising the expected QoS adaption pattern. In an analogous art, Dao ‘876 discloses this (paragraphs 0230-234 and Figure 7, where a PDU session modification is sent to the core network, thereby triggered by a RAN release, and the RAN signals information received from the SMF (e.g., QoS profiles, rules and parameters) to the UE). The Office notes that the limitation “and send(ing) the expected QoS adaptation pattern to a gNB over radio resource control (“RRC”)” is not required as the claim requires “at least one of” this step and “send(ing) a packet data unit (“PDU”) session modification request to a core network, the request comprising the expected QoS adaption pattern” mapped to Dao ‘876. Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention combine Dao ‘662 with Dao ‘876. One would be motivated to do so in order to deliver latency-sensitive packets in an environment with inconsistent network behavior (see paragraph 0006 of Dao ‘876).
However, the aforementioned references do not disclose transmit QoS configuration parameters comprising a QoS flow identity (“ID”), a list of QoS profiles, and priorities of QoS profiles or determining the QoS adaptation pattern on the QoS configuration parameters. In an analogous art, Dao ‘917 discloses this. Specifically, Dao ‘917 discloses an SMF providing one or more QoS profiles to a RAN node, where the profiles include parameters such as a QoS Identifier and an Allocation and Retention Priority (paragraph 0101). Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine Dao ‘662 and Dao ‘917. One would have been motivated to do so in order to improve reporting of events in which QoS parameters of delay critical GBR QoS flows are violated (refer to paragraph 0005 of Dao ‘917).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Dao ‘662 in view of Dao ‘917.
Regarding Claim 20, Dao ‘662 discloses an apparatus comprising:
At least one memory (Figure 9, 920 and paragraph 0251); and
At least on(e) processor (Figure 9, 910 and paragraph 0251) coupled to the memory (Figure 9 and paragraph 0251) and configured to cause the apparatus to:
transmit a subscription request to be notified of an expected quality of service (“QoS”) adaptation pattern (paragraphs 0047-0049, wherein the SMF may request or subscribe for statistical QoS values based on values previously provided to the NWDAF);
transmit an actual or expected characteristics of a user equipment (“UE”) that describes a context of the UE (paragraphs 0141-0142 – the NWDAF receives travel route information of the UE including one or multiple ordered road segments);
receive the expected QoS adaptation pattern, which is generated using a data analytics model based on the actual or expected characteristic of the UE, the expected QoS adaptation pattern comprising a sequence of QoS profiles to be associated with a QoS flow for the UE over a time interval, wherein each of the QoS profile comprises a set of QoS attributes, and wherein the sequence of QoS profiles indicates a time duration or geographical area over which a corresponding set of QoS attributes is to be applied (paragraph 0141 – the NWDAF performs data analytics to provide statistic network QoS information according to the current and future geographical location; paragraphs 0142-0146 - the network may provide network QoS information for each road segment of each route, such as road segments on proposed alternative routes (see paragraphs 0143-0145), where, the network QoS information comprises QoS parameters, statistics, and critical road sub-segments where the QoS may drop below a critical threshold; the claimed alternative limitation “time duration or geographical area” is met by this disclosure); and
transmit an indication of the QoS adaptation pattern to a Session Management Function (“SMF”), the indication comprising a QoS profile from the QoS adaptation pattern for changing the QoS flow for the UE (paragraph 0168 and Figure 6, wherein the network QoS information response is sent to the UE via the SMF, AMF and RAN).
However, Dao ‘662 does not disclose the QoS configuration parameters comprise a QoS flow identity ("ID"), a list of QoS profiles, and priorities of QoS profiles or determining the QoS adaptation pattern on the QoS configuration parameters. In an analogous art, Dao ‘917 discloses this. Specifically, Dao ‘917 discloses an SMF providing one or more QoS profiles to a RAN node, where the profiles include parameters such as a QoS Identifier and an Allocation and Retention Priority (paragraph 0101). Thus, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine Dao ‘662 and Dao ‘917. One would have been motivated to do so in order to improve reporting of events in which QoS parameters of delay critical GBR QoS flows are violated (refer to paragraph 0005 of Dao ‘917).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
NWDAF: Automating the 5G network with machine learning and data analytics is directed to predictive QoS in V2X deployments.
SG Automotive Association; Working Group System Architecture and Solution Development; SGS Enhancements for Providing Predictive QoS in C-V2X discloses making UE-based QoS Predictions (section 5.1.4).
3GPP TS 23.288 V16.4.0 (3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Architecture enhancements for 5G System (5GS) to support network data analytics services (Release 16)) discloses NWDAF-assisted UE behavioral analytics (clause 6.7.4.4.1) and QoS sustainability analysis (clause 6.9).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW W. CHRISS whose telephone number is (571)272-1774. The examiner can normally be reached Monday-Friday, 8am-4pm ET.
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/ANDREW W CHRISS/Primary Examiner, Art Unit 2472