DETAILED ACTION
This action is in response to communications filed January 15th, 2026.
Claims 1-16 are currently pending. Claims 1-2, 4-6, 8, and 14-15 are currently amended.
The present application claims priority to European Patent Application no. EP 22 152 772.8, filed on January 21st, 2022.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Claims 1-16 are rejected under 35 U.S.C. 103 as being unpatentable over Bai et al (U.S. Patent Application Publication no. 2024/0305533, hereinafter Bai in view of Tsai et al (U.S. Patent Application Publication no. 2022/0150723, herein after Tsai).
With respect to claims 1, 14, and 15, Bai discloses a method, system, and non-transitory computer-readable medium for operating a communication network (paragraph [0003]), comprising:
receiving, by a business support system of a resource reservation system (paragraph [0015], lines 1-10, mobile network operators), a reservation request (paragraph [0050], lines 13-17, reserved or allocated for users and bearer related requests), the reservation request indicates:
a Quality of Service (QoS) for an upcoming connection (paragraph [0015], lines 10-22, pre-negotiated SLAs that defines the resource constraints) to be provided at a time by the communication network for a terminal device and an application or service accessed by the terminal device via the upcoming connection and the time (paragraph [0015], lines 1-10, mobile network operators);
checking, by a bookkeeper decision engine of the resource reservation system, whether the business support system has availability for the indicated QoS at the time (paragraph [0015], lines 10-22, meet the service requirements);
in response to confirming the availability for the indicated QoS, sending, by the bookkeeper decision engine, a reservation confirmation (paragraph [0050], lines 13-17, reserved or allocated for users and bearer related requests); and
providing, by the communication network, the upcoming connection with the indicated QoS at the time (paragraph [0050], lines 13-17, reserved or allocated for users and bearer related requests).
But Bai does not disclose a Quality of Service (QoS) for an upcoming connection to be provide at a future time by the communication network.
However, discloses a Quality of Service (QoS) for an upcoming connection (paragraph [0055], lines 1-3, QoS under the corresponding application type) to be provided at a future time by the communication network for a terminal device (paragraph [0054], lines 1-10, the workload scheduling apparatus 10 receives a service request from the network service management device; paragraph [0057], the service request may further include a specific time point and length of service period) and an application or service accessed by the terminal device via the upcoming connection and the future time (paragraph [0054], lines 1-10, the service request is related to an application type of one or a plurality of terminal devices 90);
in response to confirming the availability for the indicated QoS, reserving by the bookkeeper decision engine, resources for fulfilling the reservation request at the future time (paragraph [0066], lines 1-8, arrange one or more slicing resource required by the service request according to the predicted arrangement results), and sending, by the bookkeeper decision engine, a reservation confirmation (paragraph [0065], confirm whether the service request is satisfied).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine the radio resource planning and slice aware scheduling for intelligent radio access network slicing of Bai with the resource management system and workload scheduling apparatus for network slicing of Tsai. The motivation to combine being to improve the deployment and allocation of network resource. The deployment and allocation of network resources be improved by adjusting network slices based on a prediction of requests for future network resources (abstract: Tsai).
With respect to claim 2, the combination of Bai and Tsai discloses the method according to claim 1, Bai further discloses: based on availability for a respective indicated QoS not being confirmed for a respective reservation request corresponding to a respective upcoming connection (paragraph [0013], lines 32-38, not able to meet the requirements), sending, by the business support system, a reservation offer indicating an available lower QoS for the respective upcoming connection (paragraph [0063], resource provisioning may be different for different types of slices).
With respect to claim 3, the combination of Bai and Tsai discloses the method according to claim 2, Bai further discloses wherein the reservation request, the reservation confirmation, and the reservation offer are transmitted using a dedicated protocol and/or at a specific QoS (paragraph [0050], lines 13-17, reserved or allocated for users and bearer related requests).
With respect to claim 4, the combination of Bai and Tsai discloses the method according to claim 1, Bai further discloses wherein the reservation request further indicates a location of the terminal device at the future time (paragraph [0081]), and/or a number of upcoming connections requiring the indicated QoS (paragraph [0079]).
With respect to claim 5, the combination of Bai and Tsai discloses the method according to claim 4, Bai further discloses wherein checking whether the business support system has availability for the indicated QoS at the future time comprises:
sending an availability request to the bookkeeper decision engine via a service management and orchestration engine of the resource reservation system (paragraph [0137]), the availability request comprising indications of the reservation request (paragraph [0015], lines 10-22, pre-negotiated SLAs that defines the resource constraints); and
receiving an availability confirmation from the bookkeeper decision engine via the service management and orchestration engine based on the bookkeeper decision engine finding availability for the indicated QoS (paragraph [0050], lines 13-17, reserved or allocated for users and bearer related requests).
With respect to claim 6, the combination of Bai and Tsai discloses the method according to claim 5, Bai further discloses wherein finding availability for the indicated QoS comprises at the future time:
sending a QoS prediction request to a QoS prediction service of the resource reservation system (paragraph [0081]); and
receiving a QoS prediction report from the QoS prediction service, the QoS prediction request comprising indications of the availability request and the QoS prediction report indicating a highest available QoS (paragraph [0154], machine learning (ML) workflows including model training), a determined number of resource blocks required for the indicated QoS, a number of available resource blocks, and a number of free resource blocks at the location of the terminal device (paragraph [0064], average rate per resource block).
With respect to claim 7, the combination of Bai and Tsai discloses the method according to claim 6, Bai further discloses wherein the bookkeeper decision engine or the QoS prediction service determines the number of resource blocks required for the indicated QoS based on the location of the terminal device and a device capability of the terminal device via an estimation or a calculation (paragraph [0062], based on the QoS/SLA requirements).
With respect to claim 8, the combination of Bai and Tsai discloses the method according to claim 6, Bai further discloses wherein a capacity usage policy manager of the resource reservation system provides the bookkeeper decision engine with a capacity usage policy and the bookkeeper decision engine finds availability for the indicated QoS by applying the provided capacity usage policy to the QoS prediction report (paragraph [0031], traffic usage reporting).
With respect to claim 9, the combination of Bai and Tsai discloses the method according to claim 8, Bai further discloses wherein the capacity usage policy manager selects the capacity usage policy based on an indicated application or service and provides the selected capacity usage policy (paragraph [0018], application and/or service requirements).
With respect to claim 10, the combination of Bai and Tsai discloses the method according to claim 8, Bai further discloses wherein the bookkeeper decision engine finds availability for the indicated QoS based on the calculated number of the resource blocks required for the indicated QoS being lower than a predetermined first percentage of free resource blocks (paragraph [0064], average rate per resource block) and a number of reserved resource blocks being lower than a predetermined second percentage of available resource blocks, the first percentage and the second percentage being defined by availability rules of the capacity usage policy (paragraph [0074]).
With respect to claims 11 and 16, the combination of Bai and Tsai discloses the method according to claims 8 and 15, Bai further discloses:
implementing a QoS reservation application programming interface (API) for the service management and orchestration engine, a capacity usage policy API for the capacity usage policy manager, or a QoS prediction API for the QoS prediction service (paragraph [0017]);
wherein the implemented API is supported by the bookkeeper decision engine (paragraph [0017]).
With respect to claim 12, the combination of Bai and Tsai discloses the method according to claim 5, Bai further discloses wherein the bookkeeper decision engine stores reservation data corresponding to the indications of the availability request in a reservation database of the resource reservation system first as temporary and second, upon a reservation confirmation received from the business support system, as final (paragraph [0050], lines 13-17, reserved or allocated for users and bearer related requests).
With respect to claim 13, the combination of Bai and Tsai discloses the method according to claim 1, Bai further discloses: assigning the indicated QoS, wherein assigning the indicated QoS comprises authorizing the terminal device via a subscriber identity module of the terminal device (paragraph [0064], UE subscription data).
Response to Arguments
Applicant's arguments filed January 15th, 2026 have been fully considered but they are not persuasive.
With respect to applicant’s argument that the cited portions of Bai, specifically paragraph [0050], does not have support in their provisional application (no. 63/219,631) filed on July 8th, 2021, and thus should not receive the benefit of the priority date to be applied as prior art.
The examiner respectfully disagrees. Paragraphs [0040]-[0042] of the Bai’s provisional application provide support for all of the teachings of paragraph [0050] of the Patent Application Publication cited above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chandramouli Pat. Pub. 2024/0057139
Ickin Pat. Pub. 2023/0370341
Parekh Pat. Pub. 2021/0235277
Lunardi Pat. Pub. 2025/0039714
Xu Pat. Pub. 2024/0397480
Bai Pat. Pub. 2024/0305533
Pateromichelakis Pat. Pub. 2024/0095100
Gholmieh Pat. Pub. 2024/0098627
Kodaypak Pat. Pub. 2024/0049046
Manolakos Pat. Pub. 2024/0031978
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 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BLAKE J RUBIN whose telephone number is (571)270-3802. The examiner can normally be reached on Monday - Friday, 9am - 5pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ario Etienne can be reached on 571-272-4001. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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3/20/26
/BLAKE J RUBIN/Primary Examiner, Art Unit 2457