IP Library Granted Patent US 12,621,671
Granted Patent B2
US 12,621,671 · App. 18/422,458 · Granted May 5, 2026

Dynamic utilization-based network slice allocation management for user equipment applications

Inventors: Sharath Somashekar (Overland Park, KS); Diego Estrella Chavez (McLean, VA); Akriti Kumar (Brambleton, VA); Rashmi Kumar (Herndon, VA)
Assignee: T-Mobile Innovations LLC
H04W16/10H04L43/0882H04W24/02
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,621,671
App. No.
18/422,458
Granted
May 5, 2026
Kind
B2
Abstract

Systems and methods for dynamic utilization-based network slice allocation management for user equipment applications are provided. In some embodiments, a slice estimation engine may be implemented to evaluate the network traffic and other application activity data associated with an application running on the UE to determine an operating mode of the application. The slice estimation engine may trigger the UE to request an adjustment to its network slice allocation configurations based on the evaluation. To determine whether or not an application should be reconfigured for a new network slice, the slice estimation engine may evaluate processes that are running on the UE. The slice estimation engine may comprise one or more slice assessment algorithms that determine which slice from a set of available network slices would optimally serve the application based on the network traffic characteristics associated with the application's current mode of operation.

Claims (43)

1 . A system for dynamic network slice allocation, the system comprising:

one or more processors; and

one or more computer-readable media storing computer-usable instructions that, when executed by the one or more processors, cause the one or more processors to:

establish at least one communication link between a telecommunications operator core network and a user equipment (UE) via a wireless base station;

evaluate one or more characteristics of application activity data associated with at least one application executed on the UE, wherein the application activity data includes at least an indication of an operating mode of the at least one application, wherein evaluation of the one or more characteristics of application activity data is performed at least in part by a slice estimation engine executed as a network function, wherein the slice estimation engine comprises one or more slice assessment algorithms that predict the operating mode of the at least one application from the application activity data;

associate the indication of the operating mode to a network slice allocation configuration; and

trigger a network slice allocation request to the telecommunications operator core network to allocate a network slice to the UE based at least on the network slice allocation configuration.

2 . The system of claim 1 , the one or more processors further to:

correlate the indication of the operating mode to a network slice allocation policy to determine the network slice allocation configuration.

3 . The system of claim 1 , the one or more processors further to:

determine the network slice for the network slice allocation request based at least on determining a set of network slices available for allocation to the UE by the telecommunications operator core network.

4 . The system of claim 1 , wherein evaluation of the one or more characteristics of application activity data is performed at least in part by the at least one application.

5 . The system of claim 1 , the one or more processors further to:

trigger a first request to the telecommunications operator core network to allocate a first network slice allocation configuration for the at least one application based at least on a first indication that the at least one application is operating in a first operating mode associated with a first characteristic of network traffic; and

trigger a second request to the telecommunications operator core network to allocate a second network slice allocation configuration for the at least one application based on a second indication that the at least one application has switched from operating in the first operating mode to operating in a second operating mode associated with a second characteristic of network traffic.

6 . The system of claim 1 , wherein evaluation of the one or more characteristics of application activity data is performed at least in part by the UE.

7 . The system of claim 1 , wherein the slice estimation engine is executed at least in part as a network function of the telecommunications operator core network.

8 . The system of claim 1 , the one or more processors further to:

evaluate the one or more characteristics of application activity data to infer the operating mode of the at least one application based on a machine learning model trained to implement a classification inference engine.

9 . The system of claim 1 , wherein the network slice allocation request comprises a Packet Data Unit (PDU) session modification request.

10 . The system of claim 1 , wherein the application activity data comprises an indication associated with the at least one application of one or more of:

a network traffic latency, a network traffic data rate, an amount of data traffic, a routing selection policy, a pattern of traffic flow, and an uplink versus downlink direction of traffic flow.

11 . The system of claim 1 , the one or more processors further to:

reconfigure a configuration of the UE based on an allocation of the network slice for the at least one application received in response to the network slice allocation request.

12 . A telecommunications network, the network comprising:

at least one wireless base station coupled to an operator core network, wherein the at least one wireless base station establishes one or more communication links between the operator core network and a user equipment (UE);

one or more processors to perform one or more operations to:

evaluate application activity data associated with at least one application executed on the UE, wherein the application activity data includes at least an indication of an operating mode of the at least one application, wherein evaluation of the one or more characteristics of application activity data is performed at least in part by a slice estimation engine executed as a network function, wherein the slice estimation engine comprises one or more slice assessment algorithms that predict the operating mode of the at least one application from the application activity data;

associate the indication of the operating mode to a network slice allocation configuration; and

trigger the UE to transmit a network slice allocation request to the operator core network to allocate a network slice to the UE for the at least one application, based at least on the network slice allocation configuration.

13 . The network of claim 12 , the one or more processors further to:

determine the network slice for the network slice allocation request based at least on determining a set of network slices available for allocation to the UE by the operator core network.

14 . The network of claim 12 , wherein the one or more processors performing the one or more operations are comprised at least in part in an edge server of a core network edge of the operator core network.

15 . The network of claim 12 , wherein the one or more operations are executed by an edge server as a network function of the operator core network.

16 . The network of claim 12 , wherein the application activity data comprises an indication associated with the at least one application of one or more of:

a network traffic latency, a network traffic data rate, an amount of data traffic, a routing selection policy, a pattern of traffic flow, and an uplink versus downlink direction of traffic flow.

17 . A method for dynamic network slice allocation, the method comprising:

evaluating one or more characteristics of application activity data associated with at least one application executed on a user equipment (UE), wherein the application activity data includes at least an indication of an operating mode of the at least one application, wherein the UE is coupled to an operator core network of a telecommunications network via a wireless base station, wherein evaluation of the one or more characteristics of application activity data is performed at least in part by a slice estimation engine executed as a network function, wherein the slice estimation engine comprises one or more slice assessment algorithms that predict the operating mode of the at least one application from the application activity data;

associating the indication of the operating mode to a network slice allocation configuration; and

triggering the UE to send a network slice allocation request to the operator core network to allocate a network slice to the UE based at least on the network slice allocation configuration.

18 . The method of claim 17 , the method further comprising:

triggering a first request to the operator core network to allocate a first network slice allocation configuration for the at least one application based at least on a first indication that the at least one application is operating in a first operating mode associated with a first characteristic of network traffic; and

triggering a second request to the operator core network to allocate a second network slice allocation configuration for the at least one application based on a second indication that the at least one application has switched from operating in the first operating mode to operating in a second operating mode associated with a second characteristic of network traffic.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 1, 2024
From: SOMASHEKAR, SHARATH; CHAVEZ, DIEGO ESTRELLA; KUMAR, AKRITI; KUMAR, RASHMI
To: T-MOBILE INNOVATIONS LLC
Reel/Frame 068151/0071 →
Continuity (1)
Related Publication 20250247710A1 · Jul 31, 2025
References Cited (11)
US 11432159B2 · Buyukdura · 2022 [cited by applicant]
US 20180359337A1 · Kodaypak · 2018 [cited by examiner]
US 20200389828A1 · Venkataraman · 2020 [cited by examiner]
US 20230111373A1 · Chandran · 2023 [cited by applicant]
US 20230224787A1 · Vrzic · 2023 [cited by applicant]
US 20230283529A1 · Zhang · 2023 [cited by examiner]
International Search Report and Written Opinion in PCT/US2025/012710 dated Mar. 31, 2025, 8 pages. [cited by applicant]
Abbas, K., et al., “Network Slice Lifecycle Management for 5G Mobile Networks: An Intent-Based Networking Approach”, IEEE Access, vol. 9, Jun. 8, 2021, pp. 80128-80146. [cited by applicant]
Ericsson, “Ericsson enables multiple tailored slices for smartphones with Dynamic Network Slice Selection launch”, Dynamic Network Slice Selection, Jan. 27, 2022. pp. 1-6. [cited by applicant]
Ericsson, “FarEasTone and Ericsson mark a breakthrough in 5G network slicing”, Nov. 1, 2021. pp. 1-5. [cited by applicant]
Nhu, C., et al., “Dynamic Network Slice Scaling Assisted by Attention-Based Prediction in 5G Core Network”, Research Article, vol. 10, Jul. 18, 2022. pp. 72955-72972. [cited by applicant]