Self-Organized Network Policy for Terminal-Based Measurement Reporting
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Solution Overview
Problem
Conventional network optimization techniques, such as manual drive testing, are costly and time-consuming, making it difficult to implement effective network management in rapidly changing wireless communication systems.
Innovation Solution
Implementing a Self-Organized Network (SON) policy that standardizes and automates the collection and reporting of network measurements by user equipment (UEs), allowing for autonomous network management and optimization without the need for manual testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual drive testing is used to obtain measurements from devices and locations in the network, then measurement precision is improved, but operational expense and time consumption increase significantly
Solution Approach 1:
The system enables user equipment (UE) to autonomously perform measurements and report them to the network without requiring manual drive testing. The UE automatically collects measurement data, determines when reporting is needed based on network conditions, and transmits reports to network entities, thereby eliminating the need for manual testing while maintaining measurement accuracy.
Solution Approach 2:
The network provides UEs with measurement configurations and criteria in advance, including event-triggered reporting conditions and periodic reporting schedules. This preliminary setup enables UEs to automatically perform measurements and reports without manual intervention, reducing time consumption while maintaining measurement precision through predefined accuracy standards.
2Reliability
If manual drive testing is used to optimize network operations, then network optimization effectiveness is improved, but operational expense increases significantly
Solution Approach 1:
The system transfers network optimization responsibilities to user equipment, which autonomously performs measurements and generates optimization recommendations. Network entities receive these reports and execute optimizations without requiring expensive manual drive testing operations, thereby maintaining optimization effectiveness while significantly reducing operational expenses.
Solution Approach 2:
The system establishes a feedback loop where UEs continuously monitor network conditions, generate measurement reports based on predefined criteria, and transmit this information to network entities. Network entities use this feedback to dynamically adjust network parameters and configurations, ensuring effective optimization without the need for costly manual testing.
3Reliability
If conventional network management techniques are used, then network optimization capability is maintained, but adaptability to rapidly changing network environments deteriorates
Solution Approach 1:
The system implements dynamic measurement and reporting mechanisms that adapt to changing network conditions. Network entities can modify measurement configurations, reporting criteria, and optimization strategies in real-time based on current network state, enabling the system to maintain optimization capability while adapting to rapidly changing network environments.
Solution Approach 2:
The network pre-configures UEs with measurement criteria and reporting conditions that can be dynamically adjusted. This preliminary setup, combined with real-time configuration updates, enables the system to maintain optimization capabilities while adapting to changing network environments without requiring manual reconfiguration of measurement parameters.
4Loss of energy
If automated measurement collection is implemented, then operational expense is reduced, but measurement precision may deteriorate
Solution Approach 1:
The system dynamically adjusts measurement parameters and reporting criteria based on network conditions and optimization needs. Network entities can modify measurement configurations to ensure adequate precision for specific optimization tasks while maintaining automated collection, thereby reducing operational expenses without compromising measurement accuracy through intelligent parameter management.
Data Source
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AI summary
Systems and methodologies are described that facilitate network management and optimization. As described herein, a network and a device communicating with the network can exchange network management information, thereby supporting a Self Organized Network (SON) architecture for proved network management and optimization performance. A Non-Access Stratum (NAS) layer protocol and/or an Internet Protocol (IP) application, in combination with a set of associated network management messages, can be utilized to exchange network management information between a device and a network. As further described herein, various procedures can be utilized to install a SON policy to a device in order to define device behavior for operations such as collecting and reporting information related to network management. Additionally, a set of standardized events can be defined, based on which a device can detect the occurrence of an event and report the occurrence to an associated network.