RAN Controller Mobility Optimization via Individual Event Segmentation
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Solution Overview
Problem
Current mobility optimization algorithms in self-optimizing networks, such as MRO, are slow due to reliance on aggregated mobility statistics and long reporting cycles, which prevents timely adaptation to changing traffic conditions like traffic jams, leading to increased handover failures and call drops.
Innovation Solution
A radio access network controller that receives individual mobility reports from network node devices, analyzes them in real-time using machine learning models, and updates cell configurations to optimize handover settings, allowing for faster adaptation to mobility changes, such as traffic jams, by transmitting updated configuration information to network nodes via an E2 interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If centralized MRO is implemented with aggregated mobility statistics and long reporting cycles, then network stability is improved, but mobility optimization speed deteriorates
Solution Approach 1:
The patent segments the mobility optimization process into two distinct loops: a fast loop that processes individual mobility events in real-time and a slow loop that performs comprehensive optimization using aggregated statistics. This segmentation allows the system to maintain stability through the slow loop while achieving fast adaptation through the fast loop, resolving the contradiction between network stability and optimization speed.
Solution Approach 2:
The patent introduces dynamic adaptation by enabling the fast loop to continuously adjust mobility parameters based on real-time individual failure events. This dynamic mechanism allows the system to respond rapidly to changing traffic conditions while the slow loop maintains overall network stability through periodic comprehensive optimization, thus resolving the contradiction between speed and stability.
2Measurement precision
If aggregated mobility statistics are used for MRO, then measurement precision is improved, but response time deteriorates
Solution Approach 1:
The patent segments mobility reporting into individual event reporting and aggregated statistics reporting. The fast loop receives and processes individual mobility failure events immediately, enabling rapid response without waiting for aggregation cycles. The slow loop continues to use aggregated statistics for comprehensive optimization, preserving measurement precision while eliminating time loss for critical responses.
Solution Approach 2:
The patent implements preliminary action by immediately processing individual mobility failure events as they occur, before aggregation cycles complete. This allows the system to take preliminary optimization actions based on individual events, reducing response time while aggregated statistics continue to provide precise measurement data for longer-term optimization.
3Speed
If individual mobility failure events are reported in real-time, then mobility optimization speed is improved, but device complexity increases
Solution Approach 1:
The patent segments the processing architecture into a fast loop for individual event processing and a slow loop for aggregated statistics processing. This segmentation allows real-time processing of individual events to improve speed, while the separation of concerns prevents the fast loop from becoming overly complex by handling only immediate response tasks.
Solution Approach 2:
The patent introduces an intermediary fast loop that acts as a mediator between individual event reporting and the optimization process. This intermediary layer processes individual events rapidly using simplified logic, then feeds results to the comprehensive slow loop, improving speed while preventing complexity from propagating through the entire system.
4Reliability
If fast adaptation of mobility settings is implemented, then handover failure rate is reduced, but information aggregation quality deteriorates
Solution Approach 1:
The patent segments the optimization approach into a fast loop that uses individual failure events for immediate handover optimization and a slow loop that uses aggregated statistics for comprehensive parameter tuning. This segmentation enables fast adaptation to reduce handover failures while preserving aggregated statistics quality for maintaining overall network optimization.
Solution Approach 2:
The patent implements dynamic optimization where the fast loop rapidly adjusts mobility settings based on individual events to improve handover success rate, while the slow loop periodically performs comprehensive optimization using aggregated statistics. This dynamic two-loop approach ensures fast adaptation benefits are captured without degrading the quality of aggregated information for long-term optimization.
Data Source
AI summary
Radio access network controller-based mobility optimization is disclosed. Mobility reports are received at a radio access network controller from multiple network node devices, each mobility report reporting at least one individual failure event to complement one or more aggregated mobility event counters and/or one or more aggregated performance measurement reports. The mobility reports are related to client devices in one or more service areas. The radio access network controller analyzes the received mobility reports. In response to the analyzing resulting in a perceived need for an update of a cell configuration of a service area of the one or more service areas, the radio access network controller determines updated cell configuration information for the service area. The updated cell configuration information is transmitted from the radio access network controller to-wards at least one network node device in the service area.