IP Library Granted Patent US 11,297,607
Granted Patent B2
US 11,297,607 · App. 16/700,807 · Granted Apr 5, 2022

Performance-based optimization of QoS factors

Inventors: Ting Zhang (Kirkland, WA); Sudhanshu Pandey (Bellevue, WA); Pablo Tapia (Snoqualmie, WA)
Assignee: T-Mobile USA, Inc.
H04W72/0406H04L41/082H04L41/0886H04L41/20H04L41/5009H04L41/5032H04W72/087H04W84/18H04L41/0816H04L41/16H04L41/22H04L43/087H04L43/0829H04L43/0858H04L43/0888
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 11,297,607
App. No.
16/700,807
Granted
Apr 5, 2022
Kind
B2
Abstract

Described herein are one or more self-organizing network (SON) components configured to determine QoS factors associated with QoS classes for a node of a telecommunication network based at least in part on performance metrics, network configuration, or network fault information. The one or more SON components may receive the performance metrics, network configuration, or network fault information from the node, and the performance metrics, network configuration, or network fault information may be associated with communication of traffic of the QoS classes by the node. Upon determining the QoS factors, the one or more SON components may transmit indications of the QoS factors to the node.

Claims (34)

1. A computer-implemented method, comprising:

receiving, from a node of a telecommunication network by one or more self-organizing network (SON) components of a SON device, performance metrics, network configuration, or network fault information for a plurality of quality-of-service (QoS) classes of traffic handled by the node, wherein the performance metrics, the network configuration, or the network fault information for a particular QoS class indicates a QoS that the node is providing for traffic of the particular QoS class;

determining, by the one or more SON components, updated QoS factors associated with the plurality of QoS classes for the node based at least in part on the performance metrics, the network configuration, or the network fault information, the updated QoS factors including at least maximum or minimum bit rates associated with specific ones of the plurality of QoS classes; and

transmitting, by the one or more SON components to the node, indications of the updated QoS factors,

wherein the indications of the updated QoS factors instruct the node to adjust, based on the updated QoS factors, prioritized allocation of network resources for traffic of different ones of the plurality of QoS classes.

2. The computer-implemented method of claim 1 , wherein the determining comprises determining different updated QoS factors for different times of day or different network conditions.

3. The computer-implemented method of claim 1 , wherein the plurality of QoS classes are associated with different applications, different data types, or different service categories.

4. The computer-implemented method of claim 1 , wherein the node is an access network node, a backhaul node, or a core network node.

5. The computer-implemented method of claim 1 , wherein the determining includes determining the updated QoS factors based on a type of the node.

6. The computer-implemented method of claim 5 , wherein the determining the updated QoS factors based on the type of the node comprises determining different updated QoS factors for different types of nodes.

7. The computer-implemented method of claim 1 , wherein the performance metrics, network configuration, or network fault information include at least one of throughput, delay, scheduling delay, queuing delay, jitter, packet loss, number of user, or latency.

8. The computer-implemented method of claim 1 , further comprising adjusting at least one QoS class associated with the traffic.

9. The computer-implemented method of claim 1 , further comprising repeatedly performing the receiving, the determining, and the transmitting to incrementally change how the node allocates network resources for traffic of different ones of the plurality of QoS classes based on incrementally different updated QoS factors.

10. A non-transitory computer-readable medium having a plurality of programming instructions stored thereon which, when executed by a node of a telecommunication network, cause the node to perform operations comprising:

prioritizing allocation of network resources for traffic of a plurality of quality-of-service (QoS) classes based on QoS factors associated with the plurality of QoS classes;

determining performance metrics, network configuration, or network fault information associated with transmitting or receiving traffic of the plurality of QoS classes, wherein the performance metrics, the network configuration, or the network fault information for a particular QoS class indicates a QoS that the node is providing for traffic of the particular QoS class;

reporting the performance metrics, network configuration, or network fault information to one or more self-organizing network (SON) components of the telecommunication network;

receiving, from the SON components, indications of updated QoS factors associated with the plurality of QoS classes, the updated QoS factors including at least maximum or minimum bit rates associated with specific ones of the plurality of QoS classes; and

dynamically updating the QoS factors associated with the plurality of QoS classes to match the updated QoS factors based on the indications, wherein updating the QoS factors to match the updated QoS factors adjusts prioritized allocation of network resources for traffic of different ones of the plurality of QoS classes.

11. The non-transitory computer-readable medium of claim 10 , wherein the operations further comprise repeatedly performing the prioritizing, the determining, the reporting, the receiving, and the dynamically updating to incrementally change how the node allocates the network resources for traffic of different ones of the plurality of QoS classes based on incrementally different updated QoS factors.

12. The non-transitory computer-readable medium of claim 10 , wherein the plurality of QoS classes are associated with different applications, different data types, or different service categories.

13. The non-transitory computer-readable medium of claim 10 , wherein the node is an access network node, a backhaul node, or a core network node.

14. The non-transitory computer-readable medium of claim 10 , wherein the performance metrics, network configuration, or network fault information include at least one of throughput, delay, scheduling delay, queuing delay, jitter, packet loss, number of user, or latency.

15. The non-transitory computer-readable medium of claim 10 , wherein the operations further comprise adjusting at least one QoS class associated with the traffic.

16. A system comprising:

one or more processors;

a consolidation engine configured to be operated by the one or more processors to receive performance metrics, network configuration, or network fault information associated with transmission of traffic of individual ones of a plurality of quality-of-service (QoS) classes by a node of a telecommunication network, wherein the performance metrics, the network configuration, or the network fault information for a particular QoS class indicates a QoS that the node is providing for traffic of the particular QoS class;

a self-organizing network (SON) tool configured to be operated by the one or more processors to determine updated QoS factors associated with the plurality of QoS classes based at least in part on the performance metrics, network configuration, or network fault information, the updated QoS factors including at least maximum or minimum bit rates associated with specific ones of the plurality of QoS classes; and

a parameter configurator configured to be operated by the one or more processors to transmit indications of the updated QoS factors to the nodes of the telecommunication network,

wherein the indications of the updated QoS factors instruct the node to adjust, based on the updated QoS factors, prioritized allocations of network resources for traffic of different ones of the plurality of QoS classes.

17. The system of claim 16 , further comprising a SON portal to enable configuration of the SON tool.

18. The system of claim 16 , wherein the SON tool is configured to determine different updated QoS factors for different times of day or different network conditions.

19. The system of claim 16 , wherein the plurality of QoS classes are associated with different applications, different data types, or different service categories.

20. The system of claim 16 , wherein the node of the telecommunication network is an access network node, a backhaul node, or a core network node.

Assignments (3)
RELEASE OF SECURITY INTEREST Recorded Aug 23, 2022
From: DEUTSCHE BANK TRUST COMPANY AMERICAS
To: IBSV LLC; LAYER3 TV, LLC; PUSHSPRING, LLC; T-MOBILE CENTRAL LLC; T-MOBILE USA, INC.; ASSURANCE WIRELESS USA, L.P.; BOOST WORLDWIDE, LLC; CLEARWIRE COMMUNICATIONS LLC; CLEARWIRE IP HOLDINGS LLC; SPRINTCOM LLC; SPRINT COMMUNICATIONS COMPANY L.P.; SPRINT INTERNATIONAL INCORPORATED; SPRINT SPECTRUM LLC
Reel/Frame 062595/0001 →
SECURITY AGREEMENT Recorded Apr 2, 2020
From: T-MOBILE USA, INC.; ISBV LLC; T-MOBILE CENTRAL LLC; LAYER3 TV, INC.; PUSHSPRING, INC.; BOOST WORLDWIDE, LLC; CLEARWIRE COMMUNICATIONS LLC; CLEARWIRE IP HOLDINGS LLC; CLEARWIRE LEGACY LLC; SPRINT COMMUNICATIONS COMPANY L.P.; SPRINT INTERNATIONAL INCORPORATED; SPRINT SPECTRUM L.P.; ASSURANCE WIRELESS USA, L.P.
To: DEUTSCHE BANK TRUST COMPANY AMERICAS
Reel/Frame 053182/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 2, 2019
From: ZHANG, TING; PANDEY, SUDHANSHU; TAPIA, PABLO
To: T-MOBILE USA, INC.
Reel/Frame 051159/0542 →
Continuity (4)
Continuation 14612962 · Feb 3, 2015
Continuation In Part 13831082 · Mar 14, 2013
Provisional Application 61695212 · Aug 30, 2012
Related Publication 20200107313A1 · Apr 2, 2020