Multiple CQI Reporting Processes for URLLC
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Solution Overview
Problem
Current LTE systems' CQI reporting only corresponds to a 10% BLER target, making it unsuitable for services requiring lower block error ratios, such as ultra-reliable low-latency communication, due to UE-specific decoding performance variations and the inability to accurately convert CQI for different BLER targets.
Innovation Solution
Implementing methods for reporting multiple CQI values and a scaling factor to support various BLER targets, allowing the gNB to set appropriate modulation and coding schemes, and extending the range of supported code rates by configuring CQI processes and using scaling factors to adjust code rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single CQI reporting process with 10% BLER target is used, then the system is simple and compatible with existing LTE, but it cannot support services requiring lower BLER targets such as URLLC
Solution Approach 1:
The patent divides the CQI reporting into multiple independent CQI processes, where each process is configured with a specific BLER target (e.g., first CQI process for 10% BLER, second CQI process for 0.1% BLER). This segmentation allows the system to support different service requirements without requiring a complete redesign of the CQI reporting mechanism, thereby improving adaptability while maintaining manageable complexity through modular design.
Solution Approach 2:
The patent introduces dynamic configuration of CQI processes, where the gNB can configure and activate different CQI processes based on service requirements. The system can dynamically switch between single-process and multi-process modes, allowing flexibility in adapting to different BLER targets without permanently increasing system complexity.
2Measurement precision
If multiple CQI values are reported for different BLER targets, then accuracy for low BLER targets is improved, but the quantity of feedback information increases
Solution Approach 1:
The patent segments CQI feedback into multiple independent CQI values, each corresponding to a specific BLER target. This segmentation allows the gNB to receive precise CQI information for different service types without requiring a single bulky CQI report that would need to cover all possible scenarios, thereby improving measurement precision while managing feedback volume through targeted reporting.
Solution Approach 2:
Different CQI values are reported with different levels of detail and precision based on the specific BLER target requirements. For example, CQI processes targeting lower BLER may use more conservative reporting thresholds or different quantization levels, optimizing the quality of feedback information locally for each service type rather than applying a uniform reporting standard.
3Measurement precision
If CQI offset-based conversion is used to adapt to different BLER targets, then the system maintains simplicity, but conversion accuracy is insufficient for UE-specific decoding performance
Solution Approach 1:
Instead of using a single CQI offset for conversion, the patent segments the CQI reporting into multiple independent processes, each with its own CQI values and characteristics tailored to specific BLER targets. This eliminates the need for inaccurate offset-based conversion while maintaining manageable complexity through the modular multi-process architecture.
Solution Approach 2:
The patent changes the fundamental parameter of CQI reporting from a single value with offset-based adaptation to multiple values with distinct characteristics for different BLER targets. This parameter change enables accurate representation of UE-specific decoding performance for various service types without relying on imprecise conversion methods.
Data Source
AI summary
According to some embodiments, a method of reporting channel quality information for use in a wireless device of a wireless communication network comprises: measuring a reference signal to determine a signal to noise ratio; determining a first channel quality index (CQI) using the signal to noise ratio and a first transport block error probability (e.g., BLER); determining a second CQI using the signal to noise ratio and a second transport block error probability; and reporting the first CQI and the second CQI to a network node.