Cognitive SON System Optimizing Antenna Signals Using Unstructured Data
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Solution Overview
Problem
Current network management technologies, particularly in wireless and mobile networks, face challenges in optimizing user experience due to limitations in capacity and coverage, which are exacerbated by the growth of IoT and cloud adoption, as they rely on static data metrics that fail to account for unstructured data influencing user experience.
Innovation Solution
The implementation of a cognitive self-organizing network (SON) system that collects and correlates unstructured data from mobile devices and social media, using predictive analytics and machine learning to generate optimizations for antennae signal adjustments, thereby improving user experience proactively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static data metrics are used for network management, then system complexity is reduced, but user experience optimization precision deteriorates
Solution Approach 1:
The patent segments network management data into structured data (traditional metrics) and unstructured data (social media, mobile device data). This segmentation allows the system to process different data types through appropriate methods, improving measurement precision without overwhelming system complexity with a single monolithic processing approach.
Solution Approach 2:
The patent introduces predictive analytics and machine learning models as intermediaries between raw unstructured data and network optimization decisions. These intermediaries process and translate unstructured data into actionable insights, enabling precise user experience optimization while maintaining manageable system complexity through modular architecture.
2Measurement precision
If unstructured data is collected and processed, then user experience optimization precision is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal data processing framework that handles both structured and unstructured data through common predictive analytics and machine learning components. This multi-functional approach improves measurement precision across different data types while reducing overall system complexity by avoiding separate processing pipelines for each data type.
Solution Approach 2:
The patent transforms unstructured data into standardized parameters and features that can be processed by machine learning models. By changing the parameter representation of unstructured data (converting social media text, device metrics into numerical features), the system achieves high optimization precision while maintaining computational efficiency and manageable complexity.
3Quantity of substance
If traditional hardware scaling is used to increase capacity and coverage, then network capacity is improved, but vendor service quality retention becomes more difficult
Solution Approach 1:
The patent implements self-organizing networks (SON) that automatically analyze unstructured data, generate predictions, and optimize network parameters without vendor intervention. This self-service capability ensures consistent service quality optimization based on real-time data, making vendor retention easier while scaling network capacity through automated intelligence rather than manual hardware management.
Solution Approach 2:
The patent establishes closed-loop feedback systems where unstructured data from mobile devices and social media continuously informs network optimization decisions. This real-time feedback mechanism ensures service quality is dynamically adjusted to match actual user experience, maintaining high reliability as network capacity scales through data-driven automated adjustments.
Data Source
AI summary
A method, computer system, and a computer program product for optimizing user experience by utilizing at least one self-organizing network (SON) is provided. The present invention may include generating one or more predictions associated with one or more optimizations for a plurality of unstructured data associated with one or more combined data sets. The present invention may then include transferring the generated one or more predictions associated with the one or more optimizations to at least one SON controller. The present invention may further include implementing the one or more optimizations to an antennae signal to determine a relationship with the implemented one or more optimizations and the plurality of unstructured data.