Multi-RAT Network Optimization via UE Measurement Analysis
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Solution Overview
Problem
Traditional mobile communication system radio network optimization methods, such as drive tests, are inefficient and cannot effectively address network problems due to limited sampling in time and space, and lack multipoint or regional analysis, especially in multi-RAT wireless communication networks where configuration changes in one RAT can affect other RATs.
Innovation Solution
A method for optimizing capacity and coverage in multi-RAT cellular networks by identifying worst-performing sectors, analyzing key performance indicators (KPIs), determining weak coverage symptom events, and updating configuration parameters of cells to improve signal levels, including electrical tilt adjustments and power changes for compensator, polluter, overshooter, and undershooter cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If drive tests are used for network optimization, then detailed field measurements can be obtained, but the method is inefficient and expensive with limited sampling in time and space
Solution Approach 1:
The patent creates a virtual copy of the drive test methodology by using UE measurement data that is already being collected during normal network operations. Instead of requiring physical drive tests, the system reconstructs coverage and quality maps from existing measurement reports, thereby copying the essential function of drive tests without the associated costs and limitations.
Solution Approach 2:
The network utilizes its own existing measurement collection mechanisms and UE measurement data to perform optimization analysis. The system serves its own optimization needs by processing measurement data that UEs naturally generate during normal operation, eliminating the need for external drive test resources.
2Reliability
If drive tests are used for network optimization, then coverage issues can be identified, but capital costs and lead time are significantly increased
Solution Approach 1:
The system continuously collects and processes measurement data from UEs during normal network operations. Rather than performing periodic drive tests, the optimization process runs continuously using the stream of measurement reports that UEs generate naturally, providing ongoing coverage identification without interruption to network service.
Solution Approach 2:
The system performs preliminary analysis of measurement data in near-real-time as it is collected, identifying coverage issues before they escalate into serious problems. By continuously monitoring and analyzing measurement reports, the system can detect and address coverage deficiencies proactively rather than waiting for scheduled drive tests.
3Difficulty of detecting and measuring
If optimization is based on individual RAT performance metrics, then specific RAT issues can be addressed, but indirect influences on other RATs are not considered
Solution Approach 1:
The patent implements a unified optimization framework that simultaneously handles multiple RATs (LTE, 5G, Wi-Fi) through a single system architecture. The multi-RAT coverage map and quality assessment mechanisms work across different radio access technologies, providing universal optimization capability that considers inter-RAT interactions rather than treating each RAT in isolation.
Solution Approach 2:
The system merges measurement data and optimization processes across multiple RATs into a unified framework. By combining LTE, 5G, and Wi-Fi measurement reports and analyzing them together through common algorithms, the system identifies optimization opportunities that consider the collective performance of all RATs rather than individual RAT performance alone.
Data Source
AI summary
A method for optimizing capacity and coverage in a target area of a multi-radio access technology (RAT) cellular network. In some aspects, the performance of the higher-generation RAT and that of the lower-generation RAT are each evaluated in order to optimize the capacity and coverage of the higher-generation RAT.