Proactive Neighbor List Optimization for Cellular Networks
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Solution Overview
Problem
The frequent updates to a base station's neighbor list due to Automatic Neighbor Relations (ANR) processes result in increased signaling traffic and power consumption, particularly in scenarios where patterns of changes recur, such as during daily commutes, leading to inefficiencies in handover processes.
Innovation Solution
A method and system that proactively update the neighbor list based on identified patterns, allowing for anticipatory changes at specific times or when similar changes occur, reducing the need for repeated ANR processes and associated signaling traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the base station performs automatic neighbor relation (ANR) function to detect and add new neighbors to the neighbor list, then the neighbor list is updated to include current neighboring base stations, but the signaling traffic increases and causes lag in handover
Solution Approach 1:
The system performs preliminary actions by proactively updating the neighbor list before handover is actually needed. The base station predicts future neighbor relationships based on historical data and UE movement patterns, and pre-configures the neighbor list accordingly. This eliminates the need for time-consuming ANR detection and signaling during critical handover moments.
Solution Approach 2:
The neighbor list is made dynamic by continuously adapting it based on real-time UE movement patterns and historical data. Instead of static periodic updates, the system dynamically adjusts the neighbor list composition based on predicted UE trajectories and actual handover performance, optimizing the list for anticipated handover scenarios.
2Reliability
If the base station performs automatic neighbor relation (ANR) function to detect and add new neighbors to the neighbor list, then the neighbor list is updated to include current neighboring base stations, but the signaling traffic drains power from the user equipment
Solution Approach 1:
The base station performs self-service by autonomously maintaining and updating the neighbor list using its own computational resources and historical data, eliminating the need for UEs to participate in ANR signaling. The system serves itself by predicting neighbor relationships and configuring the neighbor list without requiring UE measurements or reporting, thereby conserving UE power.
Solution Approach 2:
The base station performs preliminary neighbor list updates based on historical patterns before UEs would need to detect and report new neighbors. This proactive approach prevents the need for power-consuming UE signaling activities while ensuring the neighbor list is already optimized for upcoming handover scenarios.
3Reliability
If the base station frequently updates the neighbor list based on dynamic conditions, then the neighbor list remains current with detected base stations, but the handover process becomes less efficient due to repeated signaling
Solution Approach 1:
The system performs preliminary updates to the neighbor list based on predicted handover scenarios before they occur. By analyzing historical handover data and UE movement patterns, the base station proactively configures the neighbor list with likely target base stations, eliminating the need for repeated reactive updates and signaling during actual handover events.
Solution Approach 2:
Instead of continuous or event-driven updates that trigger frequent signaling, the system implements periodic proactive updates based on identified patterns in UE behavior and network conditions. This rhythmic updating approach maintains neighbor list currency while avoiding excessive signaling overhead associated with continuous monitoring and reactive updates.
Data Source
AI summary
A method and system for proactively managing a base station neighbor list. A base station or other network node tracks changes to the base station's neighbor list and identifies a recurring pattern of changes, in correspondence with a particular time of day for instance. The base station or other node then proactively changes the base station's neighbor list in anticipation of a recurrence of the identified pattern, such as in anticipation of recurrence of the time of day for instance. Advantageously, this method can help to reduce the extent to which the base station engages in an automatic neighbor relation process, and thus reduce the extent of signaling and other issues associated with engaging in that process.