IP Library › Granted Patent US 12,542,837
Granted Patent B2
US 12,542,837 · App. 18/559,114 · Granted Feb 3, 2026

Devices and methods for requests prediction

Inventors: Dario Bega (Munich, DE); Anna Pantelidou (Massy, FR); Christiane Maria Allwang (Munich, DE)
Assignee: Nokia Technologies Oy
H04L67/62H04L41/147H04L41/16
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Quick Facts
Patent No.
US 12,542,837
App. No.
18/559,114
Granted
Feb 3, 2026
Kind
B2
Abstract

A requests prediction apparatus ( 103 ) comprising means for: —generating information related to one or more predicted data service requests on the basis of information related to one or more past data service requests; —sending information related to at least one of the predicted data service requests to a requests prediction service client ( 102 - i ).

Claims (51)

1 . A requests prediction apparatus implemented as a Network Data Analytics Function (NWDAF) in a 5G telecommunication network, the requests prediction apparatus comprising:

at least one processor; and

at least one memory storing instructions that, when executed by the at least one processor, cause the requests prediction apparatus at least to perform:

receiving, from a requests prediction service client, a request for a requests prediction service, wherein the request for comprises:

one or more probability thresholds, and

one or more future time intervals;

upon receiving the request, retrieving, from a requests storage entity implemented as an analytics data repository function, information related to one or more past data service requests comprising network data including channel state measurements, quality of service measurements, and user equipment measurements;

training an artificial intelligence or a machine learning algorithm based on the retrieved information;

generating information related to one or more predicted data service requests based on the trained artificial intelligence or machine learning algorithm, wherein the information related to one or more predicted data service requests includes a probability value for each predicted data service request of the one or more predicted data service requests, wherein the probability value represents a probability of receiving the predicted data service request at a future time interval of the one or more future time intervals, and wherein each of the one or more predicted data service requests comprises:

an indication of a requesting network function expected to send the predicted data service request, and

a type of the predicted data service request;

selecting, from the one or more predicted data service requests, at least one predicted data service request comprising: an associated probability value higher than a probability threshold of the one or more probability thresholds, and a predicted data value exceeding a data value threshold; and

sending, to the requests prediction service client, a response to the request for the requests prediction service, wherein the response comprises the at least one selected predicted data service request together with trigger information for enabling the prediction service client to perform proactive data collection or proactive training of an artificial intelligence model prior to receiving the predicted data service request.

2 . The requests prediction apparatus of claim 1 , wherein

the one or more past data service requests correspond to one or more requests received, at one or more previous time intervals, by the requests prediction service client, and

the one or more predicted data service requests correspond to one or more requests expected to be received, at the future time interval, by the requests prediction service client.

3 . The requests prediction apparatus of claim 2 , wherein the at least one memory and the instructions, when executed by the at least one processor, further cause the requests prediction apparatus at least to perform:

generating one or more predicted values based on data obtained using the one or more past data service requests;

determining whether one or more trigger criteria are met based on the one or more predicted values; and

sending, to the requests prediction service client, trigger information including information related to the data for which the one or more trigger criteria are met.

4 . The requests prediction apparatus of claim 3 , wherein the information related to the at least one predicted data service request further comprises a parameter of the at least one predicted data service request.

5 . The requests prediction apparatus according to claim 4 , wherein the information related to each of the one or more past data service requests comprises:

an indication of the requesting entity that has sent the past data service request,

an indication on a past time interval during which the past data service request was received,

an indication on the type of the past data service request, and

a parameter of the past data service request.

6 . A prediction service client apparatus implemented as a Network Function (NF) in a 5G telecommunication network, the prediction service client apparatus comprising:

at least one processor; and

at least one memory storing instructions that, when executed by the at least one processor, cause the prediction service client apparatus at least to perform:

sending, to a requests predictor implemented as a network data analytics function, a request for a requests prediction service, wherein the request comprises:

a unique identifier of the network function;

one or more probability thresholds, and

one or more future time intervals;

receiving, from the requests predictor, a response to the request for the requests prediction service, the response comprising information related to at least one predicted data service request, wherein the information related to the at least one predicted data service request comprises at least one of:

an indication of a requesting entity expected to send the predicted data service request;

a type of the predicted data service request; and

a probability value associated with the predicted data service request;

triggering, based on trigger information including the information related to the at least one predicted data service request, proactive actions comprising:

proactive data collection of telecom network data comprising channel state measurements, quality of service measurements, and user equipment measurements from one or more data sources, and

proactive training of an artificial intelligence or machine learning model using the proactively collected telecom network data, prior to receiving the predicted data service request; and

wherein the triggering information indicates that a probability value and a predicted data value exceed respective thresholds.

7 . The prediction service client apparatus of claim 6 , wherein the at least one memory and the instructions, when executed by the at least one processor, further cause the prediction service client apparatus at least to perform:

receiving, from the requests predictor, the trigger information indicating that one or more trigger criteria based on predicted values are met, wherein the predicted values are generated based on values of data obtained using the one or more past data service requests.

8 . The prediction service client apparatus of claim 7 , wherein the information related to the at least one predicted data service request further comprises:

a probability value associated with the at least one predicted data service request, and

a parameter of the at least one predicted data service request.

9 . The prediction service client apparatus of claim 6 , wherein information related to each of the past data service requests comprises:

an indication of the requesting entity that has sent the past data service request,

an indication on a past time interval during which the past data service request was received,

an indication on the type of the past data service request, and

a parameter of the past data service request.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 29, 2024
From: PANTELIDOU, ANNA
To: NOKIA BELL LABS FRANCE
Reel/Frame 066273/0043 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 29, 2024
From: BEGA, DARIO; ALLWANG, CHRISTIANE MARIA
To: NOKIA SOLUTIONS AND NETWORKS GMBH & CO. KG
Reel/Frame 066273/0407 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 29, 2024
From: NOKIA BELL LABS FRANCE
To: NOKIA TECHNOLOGIES OY
Reel/Frame 066273/0558 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 29, 2024
From: NOKIA SOLUTIONS AND NETWORKS GMBH & CO. KG
To: NOKIA TECHNOLOGIES OY
Reel/Frame 066273/0591 →
Continuity (1)
Related Publication 20240236208A1 · Jul 11, 2024
References Cited (29)
US 10970629B1 · Dirac · 2021 [cited by examiner]
US 11258847B1 · Rhodes · 2022 [cited by examiner]
US 11388244B1 · Ni · 2022 [cited by examiner]
US 20100229174A1 · Mukherjee · 2010 [cited by examiner]
US 20150172134A1 · Yanacek · 2015 [cited by examiner]
US 20170316334A1 · Srivastava · 2017 [cited by examiner]
US 20190129599A1 · Manthina · 2019 [cited by examiner]
US 20200219070A1 · Rosenzweig · 2020 [cited by examiner]
US 20200358689A1 · Lee · 2020 [cited by examiner]
US 20210136178A1 · Casey · 2021 [cited by examiner]
US 20210241177A1 · Wang · 2021 [cited by examiner]
US 20210335135A1 · Lauer · 2021 [cited by examiner]
US 20210397392A1 · Adachi · 2021 [cited by examiner]
US 20220253690A1 · Sinha · 2022 [cited by examiner]
US 20220382857A1 · Liu · 2022 [cited by examiner]
US 20230007092A1 · Singh · 2023 [cited by examiner]
US 20230217304A1 · Singh · 2023 [cited by examiner]
US 20240073709A1 · Karampatsis · 2024 [cited by examiner]
EP 3836037A1 · 2021 [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Universal Terrestrial Radio Access (UTRA), Evolved Universal Terrestrial Radio Access (E-UTRA) and Next Generation Radio Access; R… [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Telecommunication management; Subscriber and equipment trace; Trace control and configuration management (Release 17)”, 3GP… [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Architecture enhancements for 5G System (5GS) to support network data analytics services (Release 17)”, 3GPP TS 23.288, V17… [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Telecommunication management; Generic Network Resource Model (NRM Integration Reference Point (IRP); Information Service (I… [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Management and orchestration; Performance assurance (Release 16)”, 3GPP TS 28.550, V16.7.0, Dec. 2020, pp. 1-85. [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Management and orchestration; Generic management services; (Release 16)”, 3GPP TS 28.532, V16.7.1, Apr. 2021, 222 pages. [cited by applicant]
“IEEE 802.16”, Wikipedia, Retrieved on Oct. 10, 2023, Webpage available at : https://en.wikipedia.org/wiki/IEEE_802.16. [cited by applicant]
International Search Report and Written Opinion received for corresponding Patent Cooperation Treaty Application No. PCT/EP2021/073965, dated May 6, 2022, 13 pages. [cited by applicant]
Golshani et al., “Proactive auto-scaling for cloud environments using temporal convolutional neural networks”, Journal of Parallel and Distributed Computing, vol. 154, Aug. 2021, pp. 119-141. [cited by applicant]
“3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Study of Enablers for Network Automation for the 5G System (5GS); Phase 3 (Release 18)”, 3GPP TR 23.700-81, V18.0.0, Dec. 2… [cited by applicant]