Dynamic Local Cluster List for Wireless Network Optimization
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Solution Overview
Problem
Conventional methods for identifying neighboring cells in wireless networks rely on static geographic proximity and RF path loss predictions, failing to dynamically respond to changing conditions such as cell additions, seasonal changes, or actual usage patterns, leading to suboptimal interference management and network performance.
Innovation Solution
A method for establishing and maintaining a local cluster of cells relevant to a reference cell based on dynamic operating conditions, using neighbor cell lists, centroids, radio network planning data, and usage data to create a local cluster list that includes cells affecting the reference cell's maintenance or optimization operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static geographic proximity and RF path loss predictions are used to identify neighboring cells, then the neighbor cell list can be created with simple assumptions, but it fails to dynamically respond to changing network conditions such as cell additions, seasonal changes, or actual usage patterns
Solution Approach 1:
The patent transforms the static neighbor cell list into a dynamic system that automatically updates based on real-time network conditions. The system continuously monitors actual interference measurements, cell additions, removals, and usage patterns, then dynamically regenerates the neighbor cell list to reflect current network state, enabling adaptation to changing conditions without manual intervention
Solution Approach 2:
The system implements feedback loops where actual interference measurements and network performance data are continuously collected from the field, fed back to the network controller, and used to automatically update the neighbor cell list. This closed-loop feedback mechanism ensures the system responds to actual network conditions rather than relying on static predictions
2Productivity
If conservative reuse planning approaches are used to avoid excessive co-channel interference, then interference between neighboring cells is reduced, but system performance and resource utilization efficiency are limited
Solution Approach 1:
The system enables dynamic resource allocation by continuously identifying cells that are actually causing interference based on real-time measurements rather than static geographic assumptions. This allows the network to aggressively reuse frequencies in areas where interference is not problematic while providing targeted coordination only where needed, maximizing overall resource utilization
Solution Approach 2:
The system changes the operational parameters of neighbor cell lists from static geographic-based identifiers to dynamic performance-based identifiers. By continuously updating the neighbor cell list based on actual interference measurements and network conditions, the system allows flexible frequency reuse patterns that adapt to changing parameters such as traffic load, seasonal usage patterns, and network topology changes
3Reliability
If neighbor cell lists are updated periodically as new cells are established, then the list remains relatively current, but it does not account for seasonal changes in RF propagation conditions or actual cell utilization patterns
Solution Approach 1:
The system implements continuous monitoring and updating of the neighbor cell list rather than periodic updates. Real-time interference measurements and network performance data are continuously collected, and the neighbor cell list is dynamically regenerated as needed, ensuring the system always reflects current network conditions without waiting for scheduled update intervals
Solution Approach 2:
The system automatically detects and responds to changing network conditions without external intervention. The network controller autonomously monitors interference patterns, identifies when updates are needed, regenerates the neighbor cell list, and propagates updates to relevant network elements, making the entire process self-service and eliminating delays associated with manual updates
Data Source
AI summary
A networked computer system in a cellular communications network comprises a processor, a memory, and a non-transitory computer readable medium with computer executable instructions stored thereon which, when executed by the processor, cause the processor to generate a local cluster list by identifying a plurality of cells that are relevant to a maintenance or optimization operation of a reference cell using at least one neighbor cell list, a centroid of the reference cell, radio network planning data, or usage data of the reference cell, the local cluster list including local cluster information for the plurality of cells that are relevant to the maintenance or optimization operation, and store the local cluster list in the memory.