Distributed Unit Scaling for Seamless RU Migration in RAN
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Solution Overview
Problem
Existing communication systems lack a method for dynamically allocating server resources to distributed units (DUs) in a radio access network without disconnecting user equipment (UE) communication, leading to inefficiencies in resource usage and potential waste.
Innovation Solution
A method for scaling DUs in a cloud environment using a scaling controller to migrate services between DUs based on resource usage, allowing seamless transfer of UE communication and optimizing server resource allocation through pooling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If server resources are statically allocated to each DU, then resource allocation is simple and stable, but resource utilization efficiency deteriorates when traffic patterns vary
Solution Approach 1:
The patent implements dynamic resource allocation where the scaling controller continuously monitors resource usage metrics of DUs and automatically scales resources up or down based on actual demand. This transforms the static resource allocation into a dynamic system that adapts to varying traffic patterns, improving resource utilization efficiency while maintaining manageable complexity through automated control.
Solution Approach 2:
The scaling controller employs feedback mechanisms by monitoring resource usage metrics from DUs and using this information to make informed scaling decisions. The controller receives feedback on resource consumption patterns and adjusts resource allocation accordingly, creating a closed-loop system that optimizes resource utilization while maintaining system stability.
2Reliability
If DUs are scaled up to handle peak traffic, then service capacity is sufficient during high demand, but power consumption and resource waste increase during low demand
Solution Approach 1:
The system dynamically adjusts DU resource allocation based on real-time traffic conditions. During peak traffic periods, resources are scaled up to ensure sufficient service capacity and maintain reliability. During low demand periods, resources are scaled down to reduce power consumption and eliminate waste, while the scaling controller ensures seamless transitions that maintain service continuity.
Solution Approach 2:
The patent changes operational parameters of DUs by adjusting resource allocation levels based on monitored performance metrics. The scaling controller modifies resource parameters such as computational power and memory allocation dynamically, allowing the system to adapt between high-capacity and low-power states according to actual service demands.
3Productivity
If DUs are scaled dynamically based on resource usage, then resource efficiency is improved, but system complexity and control difficulty increase
Solution Approach 1:
The scaling controller implements self-service functionality by autonomously monitoring DU resource usage, making scaling decisions, and executing resource allocation adjustments without manual intervention. This automated self-management improves resource allocation efficiency while simplifying system operation, as the controller handles the complexity of dynamic resource management internally.
Solution Approach 2:
The system uses feedback loops where the scaling controller continuously monitors resource usage metrics from DUs and automatically adjusts resource allocation based on this feedback. This closed-loop control mechanism handles the complexity of dynamic scaling automatically, improving resource efficiency while maintaining ease of operation through automated decision-making based on monitored performance data.
4Adaptability or versatility
If resources are allocated to multiple DUs, then service coverage is expanded, but resource fragmentation and management complexity increase
Solution Approach 1:
The scaling controller serves multiple DUs simultaneously with a single unified resource pool, making the resource management system universal rather than dedicated to individual DUs. This multi-functional approach allows resources to be dynamically allocated across multiple DUs based on demand, expanding service coverage while the centralized controller manages complexity through unified resource orchestration.
Data Source
AI summary
A method of communication by a radio access network device including a distributed unit (DU) may include obtaining information about resource usage of a first DU executed through a first server by a scaling controller, selecting a second DU based on the information about the resource usage of the first DU by the scaling controller, selecting a second RU to migrate to the second DU from among at least one first remote unit (RU) processing a service of the first DU by the scaling controller, and transmitting information about the second RU to the second DU by the first DU, wherein a remaining RU except for the second RU among the at least one first RU is configured to process the service of the first DU. Other various other embodiments are possible.