Dynamic SON Configuration for Mobile Base Stations
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Solution Overview
Problem
Current radio resource optimization techniques are inadequate for mobile base stations or networks with dynamic topologies, as they require fixed network topologies and lack automatic dynamic configuration mechanisms.
Innovation Solution
An automatic optimization method and system that dynamically configures Self-Optimizing Network (SON) mechanisms based on real-time network topology and traffic information, using an optimization orchestrator and self-configuration controller to adjust radio allocation profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SON mechanisms are configured with fixed network topology assumptions, then optimization performance is improved for static networks, but the system cannot adapt to mobile base stations or dynamic topologies
Solution Approach 1:
The patent implements dynamic topology detection and SON mechanism selection that adapts to changing network conditions. The system continuously monitors base station mobility and topology changes, then dynamically selects and reconfigures appropriate SON mechanisms (ABS, SFR, or coordinated beamforming) based on current network state, enabling both static and mobile network optimization.
Solution Approach 2:
The system changes operational parameters by detecting base station mobility status and topology information, then adjusting SON mechanism configuration parameters accordingly. When mobility is detected, the system transitions from static optimization parameters to dynamic parameters that account for base station movement, maintaining optimization effectiveness across different network states.
2Manufacturing precision
If manual configuration of SON mechanisms is used, then precise control over optimization parameters is achieved, but the complexity of network deployment and maintenance increases
Solution Approach 1:
The patent implements self-service through automated topology detection and SON mechanism selection. The system automatically discovers network topology, identifies base station mobility status, and selects appropriate optimization mechanisms without manual intervention. This self-configuration capability maintains precise parameter control while eliminating complex manual deployment procedures.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring network topology and base station positions, then using this information to automatically adjust SON mechanism configurations. The feedback loop enables the system to maintain optimal parameters adaptively, replacing manual configuration while preserving precision through automated decision-making based on real-time network state.
3Object-affected harmful factors
If interference management mechanisms are manually optimized, then interference reduction performance is improved, but the response time to topology changes increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring multiple SON mechanisms (ABS, SFR, coordinated beamforming) with their respective optimization strategies. When topology changes or mobility is detected, the system can immediately activate the pre-prepared appropriate mechanism, eliminating manual configuration delays and enabling rapid interference management adaptation.
Solution Approach 2:
The system dynamically switches between different interference management mechanisms based on real-time topology detection. When base station mobility or topology changes are detected, the system automatically transitions from static interference management to dynamic mechanisms that adapt to new configurations, maintaining low interference levels with fast response times.
Data Source
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AI summary
This process, which applies to first and second base stations (112, 212) associated with first and second cells (113, 213) and mobile relative to each other, consists of: when the first and second cells overlap, updating a neighborhood table of the first base station with information from the second cell; updating, by means of an analysis module (158), a radio coverage topology; determining, by means of an optimization orchestrator (152), a strategy to be implemented from the current topology, the strategy corresponding to a radio allocation profile of the first and second base stations; evaluating, by means of the analysis module, traffic on the radio coverage; and, configuring, by means of an autoconfiguration controller (156), the radio parameters of the first and second base stations according to the determined strategy, depending on the current traffic.