LTE PDCCH Quality Prediction via SINR and RPPDCCH Analysis
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Solution Overview
Problem
Current methods lack an accurate and efficient control channel quality prediction for the physical downlink control channel in LTE systems, which hinders rapid and precise resource and power allocation in Evolved Node B (eNodeB) operations.
Innovation Solution
A quality prediction method and device that determine the signal-to-interference-plus-noise ratio (SINR) or equivalent reception level (RPPDCCH) of the physical downlink control channel by analyzing reference signal received power (RSRP) from multiple cells, including serving and co-channel interference cells, to accurately assess channel quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional PDCCH quality prediction methods are used, then the system can operate with existing protocols, but accurate and efficient control channel quality prediction is not achieved, hindering rapid and precise resource and power allocation
Solution Approach 1:
The patent performs preliminary channel quality prediction for PDCCH by calculating SINR and RPPDCCH values before resource and power allocation decisions are made. This advance prediction enables the eNodeB to quickly determine appropriate CCE resources and power levels without waiting for actual channel measurements during allocation, thereby improving both prediction accuracy and allocation efficiency
Solution Approach 2:
The patent introduces SINR (signal-to-interference-plus-noise ratio) and RPPDCCH (reference signal received power for PDCCH) as intermediary parameters to bridge the gap between channel conditions and resource allocation decisions. These intermediary metrics translate physical channel characteristics into actionable prediction values that directly guide CCE selection and power allocation, resolving the contradiction between accurate prediction and efficient allocation
2Adaptability or versatility
If PDCCH operates with variable load capacity and power allocation, then adaptability to changing conditions is improved, but interference fluctuation in adjacent cell control channel regions becomes severe
Solution Approach 1:
The patent implements feedback mechanisms where the eNodeB uses predicted SINR and RPPDCCH values to adjust PDCCH power allocation and CCE resource assignment in real-time. This feedback loop allows the system to adapt to changing interference conditions and load requirements while maintaining stable interference levels in adjacent cells through continuous monitoring and adjustment based on prediction results
Solution Approach 2:
The patent dynamically changes PDCCH transmission parameters including power level and CCE resource allocation based on predicted channel conditions. By adjusting these parameters according to the calculated SINR and RPPDCCH values, the system achieves adaptability to varying load conditions while controlling interference fluctuations through parameter optimization rather than fixed allocation
3Measurement precision
If accurate PDCCH quality prediction is implemented using SINR and RPPDCCH calculations, then rapid and accurate positioning basis is provided for resource allocation, but additional calculation complexity is introduced
Solution Approach 1:
The patent replaces complex actual channel measurements and physical layer analysis with mathematical models that calculate SINR and RPPDCCH based on reported RSRP values and predefined parameters. This substitution of direct physical measurement with computational modeling achieves accurate prediction while reducing the complexity of implementation, as the calculations can be performed using standard base station processing capabilities without requiring complex measurement systems
Data Source
AI summary
Provided are a quality prediction method and device for a physical downlink control channel of a long term evolution system. In the method, a target user equipment (UE) requiring physical downlink control channel (PDCCH) quality prediction is determined, and information reported by the target UE is received. According to the reported information, a prediction index of the target UE is determined, wherein the prediction index is a signal to interference plus noise ratio (SINR) of the control channel or an equivalent reception level (RPPDCCH) of the control channel. According to the SINR or the RPPDCCH, the PDCCH quality of the target UE is determined. The present document can be applied to provide more accurate and highly efficient control channel quality prediction for LTE users without adding measurement and signalling, thereby achieving the purpose of providing a quick and precise positioning basis for a control channel element (CCE) resource and power allocation algorithm of an Evolved Node B (eNodeB).