5G SON Load Balancing Optimization via Distributed and Centralized Segmentation

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Solution Overview

Problem

Current self-organizing network (SON) technologies for 5G networks face challenges in efficiently managing load balancing optimization (LBO) and mobility robustness optimization (MRO) across fifth generation (5G) networks, particularly in automating traffic distribution and handover processes without manual intervention, leading to suboptimal performance and user experience.

Innovation Solution

The implementation of distributed and centralized Load Balancing Optimization (LBO) functions within the SON framework, which allows for policy management, performance measurement, and parameter adjustment to optimize traffic distribution and handover processes automatically, enabling efficient resource utilization and quality maintenance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If distributed and centralized LBO functions are implemented for automatic traffic distribution, then automation extent is improved, but device complexity increases

Engineering Contradiction:

Improveautomation of traffic distributionVSAvoidcomplexity of SON framework

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The LBO function is divided into distributed and centralized components, where distributed LBO operates at individual gNBs for local traffic distribution decisions, while centralized LBO operates at the OAM for global optimization. This segmentation allows automation of traffic distribution while distributing complexity across multiple levels rather than concentrating it at a single point.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The SON framework acts as an intermediary layer between manual network management and automatic LBO operations. It provides standardized interfaces, policies, and measurement frameworks that enable automation while abstracting the underlying complexity from network operators.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If manual intervention is reduced for network optimization, then ease of operation is improved, but measurement precision requirements increase

Engineering Contradiction:

Improveease of network managementVSAvoidprecision of performance measurement

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The system implements feedback mechanisms where performance measurements from LBO operations are collected, analyzed, and used to adjust future LBO decisions. This closed-loop feedback enables automation while maintaining measurement precision through continuous monitoring and evaluation of LBO effectiveness.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Manual network optimization operations are replaced with automated measurement and analysis systems that objectively quantify network performance. This substitution maintains measurement precision while eliminating the need for manual intervention in optimization decisions.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If load balancing optimization is automated, then productivity is improved, but loss of information about network conditions increases

Engineering Contradiction:

Improveefficiency of traffic distributionVSAvoidinformation about network load conditions

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system performs self-service by automatically collecting, analyzing, and acting on network condition information without external intervention. Distributed LBO functions at gNBs and centralized functions at OAM continuously monitor network loads and automatically adjust traffic distribution, maintaining awareness of network conditions while improving productivity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary measurements and analysis of network conditions before executing LBO actions. By proactively gathering information about network loads, handover statistics, and traffic patterns in advance, the system maintains comprehensive information awareness while automating subsequent optimization decisions.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11963041B2Load balancing optimization for 5G self-organizing networks

Publication Date: 2024.04.16 INTEL CORP

AI summary

Various embodiments generally may relate to Load Balancing Optimization (LBO) and Mobility Robustness Optimization (MRO). Some embodiments of this disclosure are directed to the following 5G SON solutions: use cases and requirements for the management of distributed LBO and centralized LBO; procedures for the management of distributed LBO and centralized LBO; and management services and information needed to support the management of distributed LBO and centralized LBO.