Network Slice Selection Using UE Location and History
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Solution Overview
Problem
Current 5G telecommunications systems face challenges in optimizing network resources for user equipment (UE) based on location and application activity, leading to suboptimal quality of service, latency, and bandwidth utilization.
Innovation Solution
A server in the 5G system determines and proactively provides network slices to user equipment based on location and historical application activity, optimizing bandwidth, security, and latency requirements, even before a specific application is requested, using components like the Access and Mobility Management Function (AMF) and Home Subscriber Server (HSS) to classify and manage network slices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network slices are allocated dynamically based on real-time requests, then network resource utilization is improved, but quality of service and latency are worsened due to lack of pre-optimization
Solution Approach 1:
The system performs preliminary actions by determining and providing network slices to UE based on historical application activity and location data before actual application requests are made. The AMF proactively establishes optimal network slice configurations in advance, so when applications are requested, the network is already optimized for those services, reducing latency and improving QoS while maintaining efficient resource utilization.
2Reliability
If network slices are pre-allocated for all possible applications, then quality of service is improved, but network capacity and resource efficiency are worsened
Solution Approach 1:
The system applies local quality by determining network slices based on specific UE characteristics including location and historical application activity patterns. Instead of uniform pre-allocation for all UE, the AMF customizes network slice configurations locally for each UE based on their specific needs and behavior patterns, optimizing QoS where needed while avoiding unnecessary resource allocation elsewhere.
Solution Approach 2:
The system changes parameters dynamically by adjusting network slice allocations based on UE location and application activity patterns. The AMF modifies network slice parameters proactively based on observed usage patterns, transitioning from static pre-allocation to dynamic parameter adjustment that optimizes both QoS and network capacity utilization.
3Device complexity
If network slice determination is performed reactively after application requests, then device complexity is reduced, but latency and response time are worsened
Solution Approach 1:
The AMF performs preliminary determination of network slices by analyzing UE location and historical application activity data before applications are actually requested. This proactive approach establishes optimal network slice configurations in advance, eliminating the time delay that would occur with reactive determination while maintaining manageable system complexity through automated analysis of historical patterns.
Data Source
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AI summary
Techniques for determining a network slice for a communication session associated with user equipment (UE) are described herein. A fifth generation telecommunications network can implement a server to determine one or more network slices that enable the UE to receive a variety of services and/or applications as part of the communication session. The server can determine a location of the UE and application activity by the UE over a previous time period. The server can generate a set of network slices for the UE based on the location of the UE and the previous application activity. The server can transmit the set of network slices to the UE to cause the UE to access a network slice of the set of network slices during the communication session.