Dynamic Network Element Targeting in SON
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Solution Overview
Problem
Self-Organizing Network (SON) technologies face suboptimal performance and configuration issues due to reliance on static definitions of network elements, which are inadequate for dynamically evolving networks with newly added cells or base stations.
Innovation Solution
Systems and methods dynamically identify newly added network elements, group them based on shared parameters, compare these groups to element inclusion policies, and update automated optimization processes to ensure targeted and efficient optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static definitions of network elements are used in SON optimization processes, then the optimization processes can be implemented with simple initial configuration, but the performance and configuration of the network becomes suboptimal when network elements are added
Solution Approach 1:
The patent implements dynamic target identification that automatically detects and adapts to newly added network elements (cells, base stations) in real-time. The system transitions from static predefined target lists to dynamic identification based on current network state, allowing optimization processes to continuously include newly added elements without manual reconfiguration.
Solution Approach 2:
The system establishes a feedback mechanism where the SON optimization process continuously monitors the network for newly added elements and automatically updates its target list. This closed-loop feedback ensures that the optimization processes always operate on current network elements, resolving the contradiction between initial simplicity and ongoing performance.
2Measurement precision
If manual updates to target network element lists are performed, then precision in targeting can be maintained, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system implements self-service automation where the SON optimization process automatically identifies newly added network elements and updates its own target lists without human intervention. The system monitors network changes, detects new elements, and autonomously incorporates them into optimization targets, eliminating manual update requirements while maintaining precise targeting.
Solution Approach 2:
The patent establishes preliminary automated monitoring mechanisms that continuously scan for newly added network elements before they need to be optimized. This preliminary detection and automatic inclusion ensures that new elements are promptly integrated into optimization processes without waiting for manual discovery or updates.
3Device complexity
If SON optimization processes run only on predefined network elements, then device complexity is reduced, but adaptability to network evolution is lost
Solution Approach 1:
The patent transforms the rigid, predefined target list into a dynamic structure that automatically adapts to network evolution. The system continuously identifies newly added elements and updates optimization targets in real-time, enabling the SON processes to adapt to network changes without increasing operational complexity for users.
Solution Approach 2:
The automated target identification system serves multiple functions: it monitors network topology changes, detects new elements, determines their eligibility for optimization, and updates target lists. This multi-functional automated system replaces multiple manual processes, maintaining simplicity while enhancing adaptability to various network evolution scenarios.
Data Source
AI summary
Systems and methods for dynamically targeting optimization of network elements in a network are described. In some embodiments, the systems and methods identify one or more network elements (e.g., cells) that are newly added to a network that is associated with currently running automated network optimization processes, optionally group the identified one or more network elements into temporary element lists that are based on shared parameters for the one or more network elements, compare the one or more network elements and/or the temporary element lists to element inclusion policies of the automated network optimization processes, and update the automated network optimization processes based on the comparison.