Centralized RAN Load Analysis for Neighbor Relations
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Solution Overview
Problem
Current radio area network (RAN) technologies face challenges in optimizing coverage area and handover performance due to decentralized control processes, leading to localized load analysis that is not effective for wider network corrections, and identification conflicts caused by shared PCI usage among base stations.
Innovation Solution
A centralized real-time load analysis system that determines neighbor relations between base stations based on current performance metrics, employing key performance indicators (KPIs) and weighting to prioritize and adjust base station selections, thereby reducing PCI conflicts and improving network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If decentralized control processes are used for RAN coverage optimization, then ease of operation is improved, but network-wide coordination effectiveness deteriorates
Solution Approach 1:
A centralized server acts as an intermediary between base stations and the core network. The server collects load information from multiple base stations, performs centralized analysis, and returns optimized neighbor relation recommendations. This mediator enables network-wide coordination while keeping base station operations simple and autonomous.
Solution Approach 2:
The system segments the RAN optimization function into separate components: base stations perform local measurements and report to the centralized server, which then generates optimized neighbor relations. This segmentation allows decentralized operation at the base station level while achieving centralized network-wide optimization.
2Device complexity
If localized load analysis is performed at each base station, then device complexity is reduced, but network coverage optimization effectiveness deteriorates
Solution Approach 1:
The system merges the load analysis functionality from multiple individual base stations into a single centralized server. The server aggregates load information from all base stations and performs comprehensive analysis to generate optimized neighbor relations, achieving network-wide optimization that no single base station could accomplish alone.
3Device complexity
If PCI sharing is allowed among base stations, then device complexity is reduced, but identification conflicts increase
Solution Approach 1:
The centralized server receives load information and neighbor relation data from base stations, analyzes potential PCI conflicts, and returns optimized neighbor relation recommendations. This feedback mechanism enables the system to detect and resolve identification conflicts while maintaining the simplicity of PCI sharing.
Data Source
AI summary
Adjusting RAN performance by adapting cell coverage area can help optimize a wireless communications network. RAN topology can be adapted based on analysis of real-time load conditions of RAN base stations. Analysis of the load conditions of RAN base stations can be performed in a core-network of a wireless carrier rather than distributing the analysis to RAN-side elements. Analysis can be based on receiving real-time load information relating to key performance indicators such as X2 load, S1 load, instant outbound handover count, instant inbound handover count, etc. Further, analysis can include the application of predetermined rules relating to preferential performance of the base stations. This can facilitate ranking neighboring base stations, adding new base stations, deleting base stations, black/white listing base stations, etc., in neighbor relations data structures, such as automatic neighbor relations structures for self-organizing networks, e.g., eNodeBs in LTE networks.