Local Breakout for PLMN Traffic in Non-Public Networks
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Solution Overview
Problem
In 5G wireless communication systems, there is a challenge in providing privacy and meeting quality of service (QoS) requirements when user equipment (UE) accesses public land mobile network (PLMN) services through a non-public network, due to potential privacy breaches, latency issues, and increased expenses associated with traffic transport.
Innovation Solution
Implementing a method for local breakout at the non-public network, which involves determining criteria for enabling local breakout, configuring the UE for local breakout, and encrypting traffic to ensure privacy, using a combination of network-based and UE-based solutions, including the use of uplink classifiers and branching points in user plane functions to steer traffic and manage quality of service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traffic is routed through PLMN when accessing non-public network, then network service availability is improved, but privacy is compromised and latency increases
Solution Approach 1:
The patent segments traffic into two categories: traffic that can be routed through PLMN and traffic that must be routed locally. The uplink classifier divides user plane traffic based on traffic flow templates, allowing sensitive traffic to be steered through local breakout while non-sensitive traffic uses PLMN routing. This segmentation resolves the contradiction by protecting privacy for specific traffic types while maintaining PLMN routing for others.
Solution Approach 2:
The patent introduces an uplink classifier as an intermediary component in the user plane function. This intermediary inspects uplink traffic, matches it against traffic flow templates, and steers traffic appropriately - either through local breakout or PLMN routing. The intermediary enables dynamic decision-making that balances privacy protection with service availability.
2Reliability
If traffic is routed through PLMN when accessing non-public network, then network service availability is improved, but latency increases
Solution Approach 1:
The patent segments traffic based on QoS requirements and latency sensitivity. Time-sensitive traffic is identified through traffic flow templates and routed through local breakout to avoid PLMN transport delays. Non-time-sensitive traffic continues to use PLMN routing. This segmentation resolves the latency issue for critical traffic while maintaining service availability through PLMN for other traffic.
Solution Approach 2:
The patent performs preliminary classification of traffic flows before routing decisions are made. Traffic flow templates are pre-configured with QoS parameters and latency requirements. The uplink classifier uses these pre-defined templates to quickly determine the appropriate routing path, enabling low-latency routing decisions without complex real-time analysis.
3Object-affected harmful factors
If local breakout is implemented at non-public network, then privacy and latency are improved, but device complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the uplink classifier automatically performs traffic classification and routing decisions based on pre-configured traffic flow templates. The system self-manages the complexity of local breakout implementation without requiring manual intervention for each traffic flow. This reduces the operational complexity burden while maintaining privacy protection capabilities.
4Object-affected harmful factors
If local breakout is implemented at non-public network, then privacy and latency are improved, but operational expenses increase
Solution Approach 1:
The patent implements partial local breakout rather than complete local breakout for all traffic. Only the portion of traffic that requires enhanced privacy or low latency is routed through local breakout, while the remainder continues to use PLMN routing. This partial action approach reduces the operational expenses associated with local breakout infrastructure while still achieving privacy protection for sensitive traffic.
Data Source
AI summary
Systems and methods are provided to control traffic accessing a public land mobile network service (PLMN) at a non-public network to perform local breakout for selected traffic.


