MDA-Assisted SON Coordination for 5G Energy Optimization
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Solution Overview
Problem
Current wireless communication systems face challenges in effectively managing self-organizing network (SON) conflicts and energy saving in 5G networks, as existing solutions lack comprehensive analytics and coordinated decision-making mechanisms for optimizing network performance and energy efficiency.
Innovation Solution
The implementation of Management Data Analytics (MDA) services that utilize machine learning (ML) techniques to analyze data from various network sources, identify SON conflicts, and provide analytics reports for conflict resolution and energy-saving recommendations, ensuring coordinated energy management across network components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If MDA services utilize machine learning techniques to analyze data from various network sources, then network intelligence and automation are enhanced, but device complexity and computational requirements increase
Solution Approach 1:
The patent introduces a management data analytics service as an intermediary layer between network data sources and SON functions. This service collects, processes, and analyzes data from multiple network sources using machine learning techniques, then provides processed analytics reports to SON functions. This intermediary approach enhances automation while managing complexity by centralizing the analytical processing in a dedicated service rather than distributing it across all network elements.
2Reliability
If comprehensive analytics are implemented for SON conflict identification, then conflict resolution effectiveness improves, but processing time and computational resources increase
Solution Approach 1:
The management data analytics service performs preliminary analysis of network data continuously, maintaining ready-to-use analytics reports that identify potential SON conflicts before they manifest as actual network issues. By proactively analyzing data and preparing conflict identification results in advance, the system improves conflict resolution effectiveness while reducing the time needed when actual conflicts occur, as the analytical framework is already established and can quickly retrieve or update relevant information.
3Use of energy by moving object
If coordinated energy management across network components is implemented, then energy efficiency improves, but system complexity and coordination overhead increase
Solution Approach 1:
The management data analytics service performs multiple functions including SON conflict analysis, energy efficiency optimization, and network performance monitoring through a single unified platform. By consolidating these diverse functions into one multi-functional service, the system achieves coordinated energy management across network components while avoiding the complexity that would arise from implementing separate specialized systems for each function. The service uses common data collection and processing mechanisms serving multiple purposes.
Data Source
AI summary
Various embodiments generally may relate to the field of wireless communications. For example, some embodiments may relate to solutions for MDA (Management Data Analytics)-assisted self-organizing network (SON) coordination, MDA-assisted energy saving, and machine learning (ML) model training for MDA. Other embodiments may be disclosed and/or claimed.