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 Amendment
The Amendment filed 02/29/2024 has been entered. Claims 3- 6, 8, 9, 11-14 have been amended. Claim 15 is canceled. Claims 16-20 have been added .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/29/2024, 05/21/2024, and 06/30/2025. The submission 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 1-2, 4-5, 9-10, 12-14, 16-18, and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Bruhn (US20240196272A1), hereinafter Bruhn.
Regarding claim 1,
Bruhn teaches a method implemented by a base station for scheduling air interface resources of a wireless communication system using one or more prediction metrics from a user equipment, UE, the method comprising (fig. 8 and [0184-0195] traffic status information obtained from the UE(s) can include .... predicted bit rate requested from a given time or within a given time window):
receiving, from the user equipment, user-equipment-prediction-metric capabilities ([0407] UE can send the network node a capability indication, which can indicate whether the UE (e.g., UE upper protocol layers) is capable of performing traffic measurements and/or prediction needed to generate certain information requested)
generating a prediction-reporting request using the user-equipment-prediction-metric capabilities ([0407] UE can send the network node a capability indication.... to generate certain information requested by the first message and included in the second message)
communicating the prediction-reporting request to the user equipment; (fig. 8) receiving, from the user equipment, one or more user-equipment-prediction-metric reports ([0153] Upon collecting predictions of the UE's data traffic requirements ... network node may use such information to optimize future network operation towards the UE, such as allocation of resources, configuration of measurements, preparation for handover, etc)
and scheduling one or more air interface resources of a wireless communication system based on the one or more user-equipment-prediction-metric reports ([0153] Upon collecting predictions of the UE's data traffic requirements ... network node may use such information to optimize future network operation towards the UE, such as allocation of resources, configuration of measurements, preparation for handover, etc).
Regarding claim 2,
Bruhn teaches the method as recited in claim 1,
Bruhn further teaches comprising: detecting, based on analyzing the user-equipment-prediction-metric capabilities, that the user equipment supports one or more of ([0407] the UE can send the network node a capability indication, which can indicate whether the UE (e.g., UE upper protocol layers) is capable of performing traffic measurements and/or prediction needed to generate certain information requested by the first message and included in the second message)
a Quality of Service, QoS, requirement prediction metric; an uplink buffer status prediction metric; an uplink or downlink data throughput prediction metric; an uplink or downlink data-transfer latency requirement prediction metric; a priority level; a packet error rate (PER);a packet delay budget (PDB); a guaranteed bit rate; a maximum data burst volume (MDBV); or an averaging window ([0294-0318]network node may request or configure the UE to provide can include any of the following: ... predicted packet error rate requested within a given time window).
Regarding claim 4,
Bruhn teaches the method as recited in claim 1,
Bruhn further teaches comprising: detecting, based on analyzing the user-equipment-prediction-metric capabilities, at least one of: a shortest time window supported by the user equipment; or a longest time window supported by the user equipment ([0294- 0318] traffic measurements and/or predictions that the first network node may request or configure the UE to provide... predicted bit rate requested within a given time window; predicted data volume requested within a given time window; predicted packet delay requested within a given time window; predicted packet delay jitter requested within a given time window).
Regarding claim 5,
Bruhn teaches the method as recited in claim 1,
Bruhn further teaches comprising: detecting, based on analyzing the user-equipment-prediction-metric capabilities, at least one of: a prediction accuracy for the one or more prediction metrics supported by the user equipment; or a confidence level for the one or more prediction metrics supported by the user equipment ([0424-0431] accuracy ... of the ... predictions; ... traffic status information includes one or more of the following traffic metrics: data volume, number of UEs, packet size, bit rate, packet delay, packet delay jitter, packet error rate, number of consecutive failed packets, inter-packet arrival time, service downtime, number of bursts in an application level message, application level message size, end-to-end latency. In some variants, each traffic metric is represented as one of the following, for each time interval).
Claim(s) [9-10 and 12-13] (method at UE), and [17-18, and 20] (apparatus at network entity) is/are rejected under the same reasoning as claim(s) [1-2, and 4-5] (method at BS), Where Bruhn Teaches both apparatus and method for BS, UE, and network entity (0576). Claim 17 differs from claim 1 only by the additional recitation of the following limitation where Bruhn further teaches “A network entity apparatus comprising: a processor; wireless communication hardware ([0576]) and computer-readable storage media storing instructions that, when executed by the processor, cause the processor and the wireless communication hardware” ([0608]).
Regarding to claim 14,
Bruhn teaches the method as recited in claim 13,
Bruhn further teaches comprising: excluding, for at least one of the one or more prediction metrics, a frequency band attribute ([0229-0234] The first network node can decide to offload ... different frequency bands ... to free up resources to accommodate the predicted incoming traffic demand and avoid predicted future excessive load and [0348-0365] first message may include one or more instructions and/or configurations of how and/or when the UE should perform measurements and/or predictions of the UE traffic state information ... filtering conditions pertaining to RRC states, RATs, slices, cells, carriers, tracking areas, PLMN, which can be used to include at least one of the above or exclude at least one of the above).
Regarding to claim 16,
Bruhn teaches the method as recited in claim 9,
Bruh further teaches wherein the one or more prediction metric reports is generated using a machine learning ([0162] algorithms that a network node could use to predict ... include traditional estimation methods (e.g., maximum like likelihood algorithms, Kalman filters, etc.) or artificial intelligence/machine learning (AI/ML)-based techniques).
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 3, 11 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bruhn in view of Dao (US20170317894A1), hereinafter Dao .
Regarding to claim 3,
Bruhn teaches the method as recited in claim 1,
Bruhn does not explicitly teach detecting, based on analyzing the user-equipment-prediction-metric capabilities, that the user equipment supports one or more of: per-application prediction metrics; or aggregated protocol data unit, PDU, session level prediction metrics
Dao teaches detecting, based on analyzing the user-equipment-prediction-metric capabilities, that the user equipment supports one or more of: per-application prediction metrics; or aggregated protocol data unit, PDU, session level prediction metrics ([0154-0160] following parameters are used for the QoS framework definition ... Maximum Flow Bitrate: UL and DL bitrate value applicable for ... aggregation of PDU sessions for a given UE. ... It indicates maximum bitrate authorized for the data session).
It would have been obvious to one having ordinary skill in the art before the effective filing date to add the teaching of Dao to the teaching of Bruhn. The motivation for such an addition would be to improve the operation of the network ([0207] Dao).
Claims [11] (method at UE), and [19] (apparatus at network entity) are rejected under the same reasoning as claim [3] (method at BS), where Bruhn teaches both apparatus and method for BS, UE, and network entity (0576).
Claim(s) 6-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bruhn in view of Rydén (US 20230388817 A1), hereinafter Rydén.
Regarding claim 6,
Bruhn teaches the method as recited in claim 1,
Bruhn further teaches specifying, for each of the selected one or more prediction metrics, a respective prediction- reporting configuration ([0516-0521] first message can also include indications of ... one or more reporting formats for the requested traffic measurements and/or predictions; ...)
Bruhn does not explicitly teach wherein generating the prediction-reporting request further comprises: selecting the one or more prediction metrics indicated by the user equipment through the received user-equipment-prediction-metric capabilities; including the selected one or more prediction metrics in the prediction-reporting request; ... determining a time window based, at least in part, on a scheduling latency at the base station; and specifying, in the respective prediction-reporting configuration, the time window.
Rydén teaches wherein generating the prediction-reporting request further comprises: selecting the one or more prediction metrics indicated by the user equipment through the received user-equipment-prediction-metric capabilities (fig. 6 and [0020] sending, to a network node, information that indicates ... capabilities of the wireless communication device for reporting of predicted values that are predicted by the wireless communication device ... request includes (a) a request to start reporting predicted values ... performing one or more actions in response to receiving the request ... [0021] performing the one or more actions includes generating one or more reports comprising one or more predicted values) including the selected one or more prediction metrics in the prediction-reporting request (fig. 6 and [0020] sending, to a network node, information that indicates ... capabilities of the wireless communication device for reporting of predicted values that are predicted by the wireless communication device ... request includes (a) a request to start reporting predicted values ... performing one or more actions in response to receiving the request ... [0021] performing the one or more actions includes generating one or more reports comprising one or more predicted values) ... determining a time window based, at least in part, on a scheduling latency at the base station; and ([0267] QoS Prediction ... [0268]] Quality of service (QoS) describes the overall performance of a service, for example the latency, ... [0269] predict whether ... the target QoS requirements will be fulfilled or not. Such prediction can be relative to a specific time window into the future...[0273] slice configuration, for example allocate more resources if SLA is predicted to not be fulfilled in a future time window.) specifying, in the respective prediction-reporting configuration, the time window. ([0023]a request to start reporting predicted values ... during a particular time window(s))
It would have been obvious to one having ordinary skill in the art before the effective filing date to add the teaching of Rydén to the teaching of Bruhn. The motivation for such an addition would be to improve network operation ([0020] Rydén).
Regarding claim 7,
Bruhn and Rydén teach the method as recited in claim 6,
Bruhn further teaches wherein generating the prediction-reporting request further comprises: excluding, for at least one of the selected one or more prediction metrics, a radio frequency, RF, characteristic ([0229-0234] The first network node can decide to offload ... different frequency bands ... to free up resources to accommodate the predicted incoming traffic demand and avoid predicted future excessive load and [0348-0365] first message may include one or more instructions and/or configurations of how and/or when the UE should perform measurements and/or predictions of the UE traffic state information ... filtering conditions pertaining to RRC states, RATs, slices, cells, carriers, tracking areas, PLMN, which can be used to include at least one of the above or exclude at least one of the above).
Regarding claim 8,
Bruhn and Rydén teach the method as recited in claim 6,
Bruhn further teaches wherein generating the prediction-reporting request further comprises: specifying, for a first prediction metric of the selected one or more prediction metrics, a first prediction-reporting configuration; and specifying, for a second prediction metric of the one or more prediction metrics, a second prediction-reporting configuration that is different from the first prediction-reporting configuration. ([0516-0521] first message can also include indications of ... one or more reporting formats for the requested traffic measurements and/or predictions; ...)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure US 20220377751 A1, and US 20190274064 A1 .
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VAN T NGUYEN whose telephone number is (571)272-6178. The examiner can normally be reached 8:00 AM - 5:00 PM (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ayman A Abaza can be reached at (571) 270-0422. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/VAN TA NGUYEN/Examiner, Art Unit 2465 /AYMAN A ABAZA/Primary Examiner, Art Unit 2465