Dish Wireless L.l.c.

Kazi Bashir

Siddhartha Chenumolu

Mehdi Alasti

Ashish Bansal

Ash Khamas

David Zufall

Paul-André Raymond

Rajesh Chilka

An apparatus comprises a memory and a processor communicatively coupled to one another. The memory may be configured to store one or more directories comprising access to multiple tenant profiles and one or more network access commands configured to provide access to one or more entitlements. Each tenant profile of the tenant profiles are associated with one or more services. The processor may be configured to receive a request to access at least one service. The request comprises an application function identifier (AFID) comprising a tenant ID that references a tenant profile of the tenant profiles, a department ID that references multiple entitlements associated with the tenant profile, and an API ID that references a service associated with the entitlements. Further, the processor may be configured to generate a report comprising multiple network access commands configured to enable access to the service in accordance with the entitlements.

System and method to map hierarchical multi-tenant access to services

Data center architectures for providing Network Functions (NFs) in telecommunications networks are disclosed. A 5G or 6G wireless service provider with an existing 5G or 6G core network in one or more clouds can add several NFs in another cloud to optimize certain service(s). These NFs may already exist in the core, but for different services. A 4G Long Term Evolution (LTE) customer could also incrementally migrate to a public cloud rather than migrating all NFs at once.

Multi-cloud data center architectures for providing network functions in telecommunications networks

Embodiments are directed towards systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.

User plane function (UPF) load balancing based on network data analytics to predict load of user equipment

Various arrangements are presented for managing anchor point movement on a cellular network. A user equipment (UE) can be connected with the Internet via a first anchor point (e.g., user plane function) of the cellular network. A network data analytics function (NWDAF) within a core of the cellular network can analyze one or more characteristics of the piece of UE. Based on the analysis, a second anchor point is selected and the piece of UE is connected with the selected second anchor point such that the piece of UE accesses the Internet via the second anchor point.

Intelligent anchor point movement

Embodiments are directed towards embodiments are directed toward systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.

User plane function (UPF) load balancing based on special considerations for low latency traffic

Embodiments are directed towards systems and methods for selecting, in a Fifth Generation (5G) cellular telecommunication network, a User Plane Function (UPF) of a plurality of UPFs on which to anchor a Protocol Data Unit (PDU) session of a new user equipment (UE) newly appearing on the cellular telecommunication network. The selection is based on: a location of the new UE; a plurality of current loads for each UPF of the plurality of UPFs; a predicted UE load of the new UE based on network data analytics; and predicted UPF loads of the plurality of UPFs as a function of time considering the predicted UE load based on network data analytics from the Network Data Analytics Function. In the UPF selection, the Session Management Function (SMF) gives higher priority to shorter term predicted loads than longer term predicted loads.

Predictive user plane function (UPF) load balancing based on network data analytics

Embodiments are directed towards systems and methods for hierarchical network slicing for communication services. An example method includes obtaining a set of single network slice selection assistance information (S-NSSAI); for each S-NSSAI of the set, determining a Tenant Slice-Group based, at least in part, on a slice differentiator (SD) part of the S-NSSAI; and processing the set of S-NSSAI in accordance with a hierarchy of network slicing including a plurality of Tenant Slice-Groups each including one or more network slices. The slices can inherit functionality from their respective root of a corresponding Tenant Slice-Group, geographic granularity or availability of each slice can be based on its Tenant Slice-Group, and Unified Access Control (UAC) can be implemented based, at least in part, on Tenant Slice-Group identification.

Hierarchical network slicing for communication services

Systems and methods are provided to migrate a set of network functions between control planes of a network slice A and a network slice B; and a migration management unit to manage a gradual staged transfer of a subset of the plurality of network functions originally contained in the control plane of the network slice A to the control plane of network slice B wherein the gradual transfer is a migration of the plurality of network functions in a set of multiple stages to create the subset of the plurality of network functions in the control plane of slice B, wherein each gradual staged transfer includes the migration of a reduced subset of the plurality of network functions contained in the control plane of the network slice A reconfigured to the control plane of the network slice B.

Method and system for network function migration procedures for a signaling control plane

User plane function (UPF) load balancing based on current UPF load and thresholds that depend on UPF capacity

Various arrangements for performing intelligent cellular channel management are presented herein. A physical cellular communication channel may be established between a user equipment (UE) and a cellular network for sending a short message service (SMS) message in response to a cellular service request from the UE. One or more characteristics of the UE, the SMS message, or both may be analyzed. A duration of time for which the physical cellular communication channel is to be kept active may be based on the analyzed one or more characteristics. A channel maintenance instruction may be transmitted to keep the physical cellular communication channel active based on a cellular network messaging controller determining to adjust the duration of time for which the physical cellular communication channel is kept active.

Intelligent cellular channel management

Embodiments are directed towards systems and methods for selecting, in a Fifth Generation (5G) cellular telecommunication network, a User Plane Function (UPF) of a plurality of UPFs on which to anchor a Protocol Data Unit (PDU) session of a new user equipment (UE) newly appearing on the cellular telecommunication network. The selection is based on: a location of the new UE; a plurality of current loads for each UPF of the plurality of UPFs; a predicted UE load of the new UE based on network data analytics; and predicted UPF loads of the plurality of UPFs as a function of time considering the predicted UE load based on network data analytics from the Network Data Analytics Function. In the UPF selection, the Session Management Function (SMF) gives higher priority to shorter term predicted loads than longer term predicted loads. Also, in the UPF selection, the PDU session of the UE is preferred to attach on the UPF in the current serving area in which the UE is located.

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Lewisville, TX, United States of America

Kazi Bashir