Repeating Scheduling Pattern Generation for Mobile Communication Testers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The complexity of modern mobile communication standards, such as 5G, 4G, and 3G, leads to a combinatorial explosion of network configurations, making it difficult and costly to manually define suitable repeating scheduling patterns for testing, as existing methods rely on semi-static configurations rather than dynamic channel state information.
Innovation Solution
A method that casts the definition of repeating scheduling patterns as a constrained optimization problem, using a processing circuit to maximize scheduled grants and consider network configuration constraints, such as 3GPP specifications, to automatically generate optimized patterns for different configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manually defining repeating scheduling patterns is used, then test reproducibility is ensured, but development effort and cost increase significantly
Solution Approach 1:
The system enables self-service by allowing the mobile communication tester to automatically generate its own repeating scheduling patterns based on network configuration parameters, without requiring manual definition by developers. The tester processes configuration parameters and autonomously creates the scheduling patterns, eliminating the need for manual intervention in pattern definition.
Solution Approach 2:
The invention changes the approach from manual pattern definition to automated parameter-driven generation. The system takes network configuration parameters (such as TDD patterns, carrier aggregation settings) as input and automatically transforms them into repeating scheduling patterns, using parameter changes to drive the generation process rather than relying on fixed manual definitions.
2Reliability
If semi-static configuration parameters are used for scheduling, then test reproducibility is achieved, but adaptability to dynamic channel conditions is reduced
Solution Approach 1:
The system introduces dynamics by enabling the repeating scheduling pattern to be automatically adapted based on network configuration parameters. While the pattern itself is periodic and reproducible, the system dynamically generates the pattern according to current network conditions (TDD patterns, carrier aggregation, numerology), allowing the same tester to adapt to different channel conditions while maintaining test reproducibility through automated parameter processing.
3Adaptability or versatility
If repeating scheduling patterns are defined for all possible configurations, then test coverage is improved, but device complexity increases
Solution Approach 1:
The system achieves universality by creating a single automated generation mechanism that handles multiple configuration types. Instead of maintaining separate manual definitions for different configurations (FDD, TDD, carrier aggregation scenarios), the system uses one universal parameter processing approach that automatically generates appropriate scheduling patterns for any network configuration, reducing complexity while improving coverage.
Solution Approach 2:
The invention uses copying by automatically generating scheduling patterns that replicate the structure and characteristics of standard reference patterns. The system copies the essential features of known repeating patterns and adapts them according to the input configuration parameters, creating valid scheduling patterns without requiring manual re-creation for each configuration type.
Data Source
AI summary
The present disclosure provides a method of obtaining a repeating scheduling pattern for testing a device under test by a mobile communication tester. A network configuration for performing a wireless communication test on the device under test is inputted. At least one key performance indicator is provided. The network configuration and the at least one key performance indicator are processed by a processing circuit. The processing circuit obtains a repeating scheduling pattern based on the network configuration and the at least one key performance indicator.