Self-Organizing Network Algorithms for Dynamic Bandwidth Optimization

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Telecommunications networks face challenges in managing fluctuating bandwidth and quality of service due to changing traffic patterns from voice to data, requiring flexible allocation of bandwidth and optimal load distribution among cells to ensure robust mobility and handovers, especially during peak traffic periods.

Innovation Solution

The implementation of self-organizing network (SON) algorithms that automate configuration, optimization, and healing of network elements, using targets and performance indicators to adjust parameters and optimize handovers and load balancing in real-time, ensuring equitable bandwidth distribution and minimizing outages.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If manual network configuration and optimization is performed, then network control and parameter setting can be done with human judgment, but operational expenses increase and response time to traffic changes slows down

Engineering Contradiction:

Improveautomation of network configuration and optimizationVSAvoidcomplexity of network management system

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The network management system enables self-service through autonomous algorithms that automatically configure, optimize, and heal network elements without human intervention. The system monitors performance indicators, compares them against targets, and autonomously adjusts parameters to maintain optimal network operation, allowing the network to serve itself.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system dynamically changes network parameters based on real-time performance monitoring. When performance indicators deviate from targets, the system automatically adjusts relevant parameters (such as handover thresholds, power levels, or resource allocation) to bring performance back within acceptable ranges, enabling adaptive optimization.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If network parameters are adjusted manually to optimize performance, then control precision can be maintained, but response time to traffic fluctuations increases and productivity decreases

Engineering Contradiction:

Improveresponse speed to traffic changesVSAvoidprecision of performance optimization

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system implements continuous feedback loops where performance indicators are constantly monitored, compared against predefined targets, and used to trigger automatic parameter adjustments. This closed-loop control ensures both rapid response to traffic changes and precise optimization by continuously refining network parameters based on actual performance measurements.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary actions by pre-configuring optimization rules and thresholds before traffic patterns change. When performance indicators approach critical levels, the system proactively adjusts parameters before significant degradation occurs, enabling preventive optimization rather than reactive correction.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If SON algorithms are deployed to automate network optimization, then operational expenses decrease and response time improves, but system complexity and difficulty of implementation increase

Engineering Contradiction:

Improvenetwork service reliabilityVSAvoidcomplexity of SON algorithm implementation

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The SON system is segmented into independent functional modules, each responsible for specific optimization tasks (handover optimization, load balancing, interference management). This modular architecture allows individual algorithms to be developed, tested, and deployed independently, reducing overall implementation complexity while maintaining high reliability through specialized functionality.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The SON platform implements universal algorithms that can optimize multiple network parameters and performance indicators across different network conditions and scenarios. A single SON system can simultaneously handle handover optimization, load balancing, and interference management, reducing the need for separate specialized systems and simplifying deployment.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentEP2638723B1Network management

Publication Date: 2020.08.26 NOKIA SOLUTIONS & NETWORKS OY

Figure 1~2
Figure 3

AI summary

A method of managing the operation of a network element in a communications system, the method comprising: receiving performance indicators by an optimising function; combining together the performance indicators to produce an achievement indicator comprising weighted components of the performance indicators; using the achievement indicator to determine an optimum setting of at least one parameter value related to operation of the network element; applying the parameter value to the network element.