Systems and methods for application-aware dynamic slicing in radio access network (RAN)

Patent metadata

Field	Value
Publication number	US-12101637-B2
Application number	US-202217672991-A
Country	US
Kind code	B2
Filing date	Feb 16, 2022
Priority date	Jul 13, 2021
Publication date	Sep 24, 2024
Grant date	Sep 24, 2024

Abstract

Fifth generation and beyond (5G+) systems are expected to adopt new network architectures, services, and deployment schemes for compatibility with the latest technologies and end user's needs. With increase in user equipment (UE), also come variety of advanced applications and use-cases, wherein each application type has its own KPI requirements. Existing resource allocation schemes in cellular networks are not able to handle such dynamic requirements due to which network slice can lead to unwanted mismanagement of resources. Present application provides systems and methods for application-aware dynamic slicing in radio access network (RAN), wherein RAN slicing is proactively managed by learning historical slice demands and consumptions. Once slices are created, the system allocates resources to user equipment by following optimal inter-slice and intra-slice mechanisms based on application type(s), traffic demand(s) and wireless characteristics of UE. Upon resource allocation the UE are further monitored to avoid resource misutilization and resource wastage.

First claim

What is claimed is:

1. A processor-implemented method, comprising:
periodically obtaining, by a network slicing, control, and management system (NSCMS), (i) one or more uplink data requests associated with one or more user equipment, the one or more user equipment is connected to an enhanced node, and (ii) a list of available radio access network (RAN) resources;
identifying, by the NSCMS, the one or more uplink data requests, the one or more uplink data requests comprising one of a first demands request, and a second demand request, wherein the first demand request comprises a predictive demand request, wherein the second demand request comprises a real-time demand request, and wherein requirement of the real-time demand request depends on instantaneous or immediate future of traffic demands, and in the predictive demand request, predictive slicing for user demands is forecasted; and
iteratively performing:
dynamically slicing, by the NSCMS, one or more available RAN resources into a plurality of sliced RAN resources based on the one or more identified requests;
allocating, by the NSCMS, the one or more user equipment on a corresponding sliced RAN resource from the plurality of sliced RAN resources based on an inter slice allocation and an intra slice allocation, wherein the inter slice allocation selects a specific application that needs to be scheduled based on one or more key performance indicators, KPIs, and to schedule a sliced RAN resource for the specific application, wherein the intra slice allocation schedules the one or more user equipment attempting for the sliced RAN resource after the sliced RAN resource for the specific application is scheduled, wherein the specific application correspond to at least one of an enhanced mobile broadband, eMBB, application type, an ultra-reliable low latency, URLLC, application type, and a massive machine type communication, mMTC, application type, and wherein the steps of dynamic slicing and allocation is performed till all of the one or more user equipment from all application types are allocated; and
monitoring, by the NSCMS, the plurality of sliced RAN resources to obtain information specific to performance degradation based on at least one of (i) allocation of the one or more available RAN resources, (ii) change in traffic pattern, and (iii) wireless characteristics, until one or more parameters associated with the plurality of sliced RAN resources reach a pre-defined threshold.

2. The processor implemented method of claim 1 , wherein when the one or more identified requests are of the first demand request, the dynamic step of slicing, of the one or more available RAN resources into the plurality of sliced RAN resources is based on a historical sliced based dataset.

3. The processor implemented method of claim 1 , wherein the plurality of sliced RAN resources is one of an enhanced mobile broadband (eMBB) sliced resource, an ultra-reliable low latency (URLLC) sliced resource, or a massive machine type communication (mMTC) sliced resource.

4. The processor implemented method of claim 1 , wherein the step of allocating using the inter slice allocation, by the NSCMS, the one or more user equipment on a corresponding sliced RAN resource from the plurality of sliced RAN resources is based on the one or more KPIs key performance indicators associated with an uplink data request of the one or more user equipment.

5. The processor implemented method of claim 4 , wherein the one or more user equipment are allocated on a corresponding sliced RAN resource from the plurality of sliced RAN resources based on an average KPI demand associated with a corresponding application type.

6. The processor implemented method of claim 1 , wherein the step of allocating using the intra slice allocation, by the NSCMS, the one or more user equipment on a corresponding sliced RAN resource from the plurality of sliced RAN resources comprises:
prioritizing at least a subset of user equipment corresponding to a specific application from the one or more user equipment having the one or more applications for allocation on the corresponding sliced RAN resource from the plurality of sliced RAN resources based on a KPI demand of the specific application corresponding to a user equipment.

7. The processor implemented method of claim 1 , wherein the one or more parameters associated with the plurality of sliced RAN resources comprise at least one of resource utilization, and resource wastage.

8. A network slicing, control, and management system (NSCMS), comprising:
a memory storing instructions;
one or more communication interfaces; and
one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to:
periodically obtain (i) one or more uplink data requests associated with one or more user equipment, the one or more user equipment is connected to an enhanced node, and (ii) a list of available radio access network (RAN) resources;
identify the one or more uplink data requests, the one or more uplink data requests comprising one of a first demand request, and a second demand request, wherein the first demand request comprises a predictive demand request, wherein the second demand request comprises a real-time demand request, and wherein requirement of the real-time demand request depends on instantaneous or immediate future of traffic demands, and in the predictive demand request, predictive slicing for user demands is forecasted; and iteratively perform:
dynamically slice of one or more available RAN resources into a plurality of sliced RAN resources based on the one or more identified requests;
allocate the one or more user equipment on a corresponding sliced RAN resource from the plurality of sliced RAN resources, based on an inter slice allocation and an intra slice allocation, wherein the inter slice allocation selects a specific application that needs to be scheduled based on one or more key performance indicators, KPIs, and to schedule a sliced RAN resource for the specific application, wherein the intra slice allocation schedules the one or more user equipment attempting for the sliced RAN resource after the sliced RAN resource for the specific application is scheduled, wherein the specific application correspond to at least one of an enhanced mobile broadband, eMBB, application type, an ultra-reliable low latency, URLLC, application type, and a massive machine type communication, mMTC, application type, and wherein the steps of dynamic slicing and allocation is performed till all of the one or more user equipment from all application types are allocated; and
monitor the plurality of sliced RAN resources to obtain information specific to performance degradation based on at least one of (i) allocation of the one or more available RAN resources, (ii) change in traffic pattern associated thereof, and (iii) wireless characteristics associated thereof,
until one or more parameters associated with the plurality of sliced RAN resources reach a pre-defined threshold.

9. The system as claimed in claim 8 , wherein when the one or more identified requests are of the first demand request, the dynamic slicing, of the one or more available RAN resources into the plurality of sliced RAN resources is based on a historical sliced based dataset.

10. The system as claimed in claim 8 , wherein the plurality of sliced RAN resources is one of an enhanced mobile broadband (eMBB) sliced resource, an ultra-reliable low latency (URLLC) sliced resource, or a massive machine type communication (mMTC) sliced resource.

11. The system as claimed in claim 8 , wherein the step of allocating,

Assignees

• Tata Consultancy Services Ltd

Inventors

• Panigrahi Bighnaraj
• Patro Sumanta
• Rath Hemant Kumar
• Nadaf Shameemraj
• Mishra Garima

Classifications

• H04W24/08

  Testing, {supervising or monitoring} using real traffic · CPC title

• H04W16/04

  Traffic adaptive resource partitioning · CPC title

• H04W24/02

  Arrangements for optimising operational condition · CPC title

• H04W16/02

  Resource partitioning among network components, e.g. reuse partitioning · CPC title

• H04W72/04

  Wireless resource allocation · CPC title