Dynamic Centralized Unit Assignment for Radio Access Network Load Balancing
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Solution Overview
Problem
Wireless networks with distributed or hierarchical infrastructure face challenges in efficiently managing traffic distribution between centralized and distributed units, leading to uneven resource utilization and potential overload during peak usage periods.
Innovation Solution
A Modeling/Orchestration System (MOS) generates and refines models to identify complementary groups of distributed units (DUs) based on usage patterns, allowing for dynamic assignment and configuration of centralized units (CUs) to balance resource load by blending DUs with diverse usage patterns, thereby optimizing traffic handling and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If centralized units are statically assigned to distributed units, then network configuration is simple, but resource utilization is uneven and overload occurs during peak usage
Solution Approach 1:
The patent implements dynamic CU-DU assignment where the orchestration system continuously monitors usage patterns and reassigns CUs to DUs based on real-time conditions. This transforms the static configuration into a dynamic system that adapts to changing traffic loads, resolving the contradiction between configuration simplicity and resource utilization efficiency.
Solution Approach 2:
The system changes the assignment parameters of CUs to DUs based on monitored usage patterns. By adjusting which CU serves which DU according to traffic conditions, the system optimizes resource utilization without requiring complex manual reconfiguration, thus resolving the contradiction between simple configuration and efficient resource use.
2Reliability
If more centralized units are deployed to handle peak traffic, then network capacity increases, but infrastructure cost and complexity increase
Solution Approach 1:
The patent makes existing CUs multi-functional by dynamically assigning them to serve different DUs based on usage patterns. A single CU can serve multiple DUs at different times, maximizing the utilization of deployed resources and eliminating the need to deploy additional CUs for peak traffic handling, thus resolving the contradiction between network capacity and infrastructure complexity.
Solution Approach 2:
The system enables self-service load balancing where the orchestration system automatically monitors usage patterns and reassigns CUs without manual intervention. This self-adjusting mechanism ensures adequate network capacity during peak traffic without requiring over-provisioning of infrastructure, resolving the contradiction between reliability and deployment complexity.
3Productivity
If centralized units are reassigned dynamically based on usage patterns, then resource utilization improves, but system complexity and control overhead increase
Solution Approach 1:
The patent implements a feedback mechanism where the orchestration system continuously monitors usage patterns of DUs and automatically adjusts CU assignments based on this feedback. This closed-loop control system optimizes resource utilization automatically without requiring complex manual control, resolving the contradiction between improved productivity and increased system control complexity.
4Reliability
If centralized units remain idle during low usage periods, then they can handle sudden traffic spikes, but overall network efficiency decreases
Solution Approach 1:
The patent dynamically assigns CUs to DUs based on real-time usage patterns, ensuring that CUs are actively utilized during low-traffic periods by serving DUs with complementary patterns. This prevents idle time while maintaining the ability to handle traffic spikes through rapid reassignment, resolving the contradiction between reliability and network efficiency.
Data Source
AI summary
A system described herein may provide a technique for the assignment of Centralized Units (“CUs”) to Distributed Units (“DUs”) in a radio access network (“RAN”) that includes a distributed or hierarchical arrangement of network infrastructure equipment. Different groups of DUs may be modeled based on usage or traffic patterns, and complementary groups of DUs may be identified based on measures of usage that may vary with time. For example, one model associated with one group of DUs may experience relatively heavy usage during morning hours and light usage during evening hours, and another model associated with a complementary group of DUs may experience relatively light usage during morning hours and heavy usage during evening hours.