Automated Neighbor Relation Data for LTE Handover Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional Automated Neighbor Relation (ANR) systems in LTE networks do not adequately consider a user equipment's (UE) overall requirements or network traffic conditions when selecting the best neighboring cell for handover, leading to suboptimal handover decisions.
Innovation Solution
A centralized system that dynamically generates and updates ANR data for each Radio Base Station (RBS) based on end-to-end traffic sessions, including service characteristics like signal quality and Quality of Service (QoS), and lifetime indicators, allowing UEs to intelligently select the best RBS for handover, while also considering global end-to-end capacity optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ANR systems select neighboring cells based solely on SINR, then handover decisions are simple and fast, but handover optimality deteriorates because UE overall requirements and network traffic conditions are not considered
Solution Approach 1:
The system pre-calculates and stores ANR data including service characteristics and lifetime indicators for multiple neighboring cells before handover is needed. This preliminary preparation allows the UE to make optimal handover decisions based on current traffic conditions and service requirements without complex real-time calculations, resolving the contradiction between handover optimality and decision complexity
Solution Approach 2:
The patent introduces an intermediary ANR data structure that mediates between the simple SINR measurement and the complex handover decision. This intermediary contains pre-processed information about service characteristics and lifetime indicators, allowing the UE to make informed decisions without directly handling all the complexity of network traffic conditions and service requirements
2Reliability
If ANR data is updated frequently to reflect current traffic conditions, then handover decisions become more accurate, but signaling overhead and system complexity increase
Solution Approach 1:
The ANR data structure includes a dynamic lifetime indicator that automatically expires after a certain period. This dynamic mechanism ensures that ANR data reflects current traffic conditions without requiring continuous updates, as outdated data naturally becomes invalid. This resolves the contradiction by maintaining handover accuracy through periodic updates while avoiding excessive signaling overhead from continuous updates
Solution Approach 2:
Instead of continuous updates, the system uses periodic updates with time-bound ANR data. The lifetime indicator creates a natural update cycle where ANR data is valid only for a specified duration, prompting refreshes only when necessary. This periodic approach maintains handover accuracy while minimizing signaling overhead by avoiding unnecessary frequent updates
3Productivity
If the system considers global end-to-end capacity optimization, then network capacity utilization improves, but the complexity of ANR data generation and management increases
Solution Approach 1:
The UE autonomously uses the provided ANR data to make handover decisions that optimize network capacity utilization. The centralized system only needs to generate and provide the ANR data with service characteristics, while the UE independently applies this information to select the most appropriate target cell based on current network conditions. This self-service approach improves network capacity utilization without requiring the centralized system to manage complex real-time handover decisions
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
A network node in a communication network provides Automated Neighboring Relation (ANR) data to User Equipments (UEs). The network node collects information of ongoing end- to-end traffic sessions from other network nodes in the communication network, and determines service characteristics of Radio Base Stations (RBSs) based on the collected information. For each RBS, the network node creates an ANR record indicating the determined service characteristics of neighboring RBSs. The network node then transmits the ANR record to each RBS to cause the RBS to propagate the ANR record to attached UEs.