AMF Node Selection for 5G Registration and Handover Latency
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Solution Overview
Problem
Current wireless communication systems face challenges in effectively measuring and optimizing performance metrics for user equipment (UE) registration and handover processes in Next Generation Radio Access Networks (NG-RAN), particularly in 5G networks, leading to potential service disruptions and latency issues.
Innovation Solution
A method and apparatus for monitoring and analyzing registration and mobility measurements, such as registration requests, successful registrations, PDU sessions, and quality of service (QoS) flows, to select optimal nodes for UE connections and handovers, using access and mobility management functions (AMFs) and radio front-end circuitry to improve connection retention and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If performance measurements are monitored for registration and handover processes, then network service reliability is improved, but system complexity increases
Solution Approach 1:
The system automatically monitors performance measurements, selects optimal nodes, and performs handovers without human intervention. The AMF autonomously processes registration requests, evaluates performance metrics, and makes decisions about node selection and handover execution, allowing the system to serve itself in managing network reliability.
Solution Approach 2:
The system continuously monitors performance measurements including registration success rates, handover completion rates, and latency metrics. This feedback loop enables the system to evaluate network conditions, identify performance degradation, and trigger appropriate actions such as node selection or handover to maintain service reliability.
2Reliability
If optimal nodes are selected based on performance measurements, then connection retention is improved, but measurement and analysis complexity increases
Solution Approach 1:
The system extracts and monitors specific key performance indicators such as registration success rates, handover completion rates, and latency measurements from the complex network operations. By focusing on these critical measurements rather than all possible parameters, the system can make informed node selection decisions without being overwhelmed by excessive data complexity.
Solution Approach 2:
The system dynamically evaluates performance parameters and uses them to select optimal nodes for UE connections. By changing and adapting the selection criteria based on real-time performance measurements, the system improves connection retention while managing analysis complexity through focused parameter evaluation.
3Loss of time
If handover processes are optimized using performance measurements, then latency is reduced, but process complexity increases
Solution Approach 1:
The system performs preliminary monitoring and evaluation of performance measurements before handover is needed. By continuously gathering data on node performance, the system prepares advance knowledge about optimal target nodes, enabling faster handover execution when required and reducing overall latency despite the added monitoring processes.
Data Source
AI summary
Some embodiments of this disclosure include apparatuses and methods for identifying performance measurements for registration and handovers for user equipment (UE) and wireless network nodes. A service producer system may register a first wireless communication connection with a first UE using one or more access and mobility management functions (AMFs). The service producer system may monitor registration measurements corresponding to this registration, perform a handover for the first UE using the one or more AMFs, and monitor mobility measurements corresponding to the handover. The service producer system may select a node for a second wireless communication connection corresponding to a second UE based on the registration measurements and mobility measurements and transmit an indication of the selected node to the second UE. The measurements may include a number of requests, successful requests, measurements related protocol data unit (PDU) sessions, and measurements related to Quality of Service (QoS) flows.