RU-DU Call Flow Remapping for Dynamic Network Load Balancing
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Solution Overview
Problem
Existing wireless communication networks face inefficient network resource utilization due to the lack of mechanisms for load balancing by disassociating heavily loaded Radio Units (RUs) from Distributed Units (DUs) and associating them with less loaded DUs.
Innovation Solution
A method and system that utilize call flow traffic data, historical data, and prediction models to determine optimal configurations for remapping RUs between DUs, enabling efficient load balancing by re-linking RUs to balance network load effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a different RU accepts connection requests from new UEs when the original RU is heavily loaded, then new UE connections are maintained, but network resource utilization becomes inefficient
Solution Approach 1:
The patent implements dynamic load balancing by continuously monitoring traffic data from multiple DUs and using a prediction model to determine optimal RU-DU mappings. The system dynamically remaps RUs between DUs based on predicted traffic patterns, transforming the static RU-DU association into a dynamic, adaptive configuration that optimizes both connection acceptance and resource utilization.
Solution Approach 2:
The system employs feedback mechanisms by collecting call flow traffic data from DUs, analyzing current load conditions, and using prediction models to make informed remapping decisions. The feedback loop continuously monitors network state and adjusts RU-DU assignments to maintain optimal performance, resolving the contradiction between connection acceptance and resource efficiency.
2Device complexity
If RU is statically associated with a DU, then configuration simplicity is maintained, but load balancing capability is lost
Solution Approach 1:
The patent transforms the static RU-DU configuration into a dynamic system where RUs can be remapped between different DUs based on traffic conditions. The prediction model and automated remapping mechanism enable flexible, adaptive configuration that maintains simplicity in operation while providing sophisticated load balancing capabilities.
Solution Approach 2:
The system introduces an intermediary layer (the load balancing mechanism with prediction model) between the RU and DU that manages the associations dynamically. This intermediary handles the complexity of load balancing and remapping decisions, keeping the overall system configuration simple while enabling advanced load balancing functionality.
Data Source
AI summary
The present disclosure describes a method, and a system to identify call flows in Radio Unit (RU) or Centralized Unit (CU) and Distributed Units (DU) for cell-to-pod remapping. The method comprising receiving call flow traffic data of a plurality of DUs from an associated CU. Subsequently, the method comprises determining a first DU and a second DU among the plurality of DUs based on the call flow traffic data. Thereafter, the method comprises determining a new configuration for each of the first DU and the second DU based on at least one of the call flow traffic data, historical data, and pre-determined rules using a prediction model. Lastly, the method comprises transmitting the new configuration for each of the first DU and the second DU to the associated CU for remapping of a RU.