Centralized Mobility Metric Estimation for 5G RAN
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Solution Overview
Problem
Current mobile and wireless telecommunication systems, particularly in 5G networks, face inefficiencies in data duplication and processor overhead due to multiple RRM/Optimization algorithms generating their own mobility metric estimates, leading to excessive data movement and processing loads.
Innovation Solution
A mobility metric estimation/prediction module is introduced, hosted on a controller platform, which receives requests from RAN optimization services, communicates with RAN nodes, and calculates mobility metrics using requested data, minimizing data duplication and processor overhead by providing a centralized estimate or prediction service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple RRM/Optimization algorithms generate their own mobility metric estimates independently, then each algorithm can obtain the mobility metrics it needs, but data duplication and processor overhead increase significantly
Solution Approach 1:
The patent merges the mobility metric estimation functionality into a single centralized module that serves multiple RRM/Optimization algorithms. Instead of each algorithm independently generating mobility metrics, they share a common estimation module that calculates metrics once and makes them available to all algorithms that need them, thereby reducing redundant processing and overhead.
Solution Approach 2:
The centralized mobility metric estimation module is designed to serve multiple different RRM/Optimization algorithms simultaneously. It provides a universal interface that can accommodate various algorithmic requirements while maintaining a single source of mobility metric calculations, making the system more versatile without proportionally increasing complexity.
2Adaptability or versatility
If multiple RRM/Optimization algorithms generate their own mobility metric estimates, then each algorithm has independent control, but data duplication increases excessively
Solution Approach 1:
The patent combines mobility metric calculations into a single centralized operation that multiple algorithms can access. The estimation module generates mobility metrics once and stores them in a shared repository, allowing multiple algorithms to retrieve the same data without regenerating it, thus eliminating data duplication while preserving algorithmic independence.
Solution Approach 2:
Instead of each algorithm generating its own copy of mobility metrics through independent calculations, the system creates a single master copy in the centralized module and allows algorithms to access copies of this data through standardized interfaces, reducing the overall quantity of duplicated data in the system.
3Productivity
If a centralized mobility metric estimation module is implemented, then data duplication and processor overhead are reduced, but the system architecture becomes more complex
Solution Approach 1:
The centralized mobility metric estimation module acts as an intermediary between the raw measurement data and the multiple RRM/Optimization algorithms. It receives data from the network, performs unified processing, and distributes results to various algorithms, simplifying the overall architecture by introducing a single mediation layer rather than multiple independent processing paths.
4Adaptability or versatility
If independent mobility metric estimation is performed by each algorithm, then customization for specific algorithm needs is possible, but network performance optimization is reduced due to excessive processing load
Solution Approach 1:
The system segments the mobility metric estimation function from the individual algorithms, placing it in a separate centralized module. This allows the estimation logic to be optimized independently for network performance while still providing customized mobility metrics to each algorithm through configured interfaces, separating the heavy processing from the algorithm-specific logic.
Data Source
AI summary
A method and apparatus for estimating and/or predicting mobility metric(s) for RAN optimization. One method includes receiving a request, from at least one RAN optimization service, to provide an estimate or prediction of a mobility metric for at least one UE or group of UEs or at least one cell. The request may include attributes describing characteristics of the mobility metric. The method may then include communicating with a RAN node to request data about the at least one UE or the group of UEs or the at least one cell associated with the request, receiving the requested data, and calculating the estimate or the prediction of the mobility metric using the requested data and based on the attributes received in the request from the at least one RAN optimization service.