Adaptive Modulation Coding SINR Prediction Accuracy
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Solution Overview
Problem
In wireless communication systems, especially in LTE, the discontinuity of user equipment services and frequent changes in interference from neighboring cells lead to inaccurate prediction of signal-to-interference plus noise ratio (SINR), resulting in decreased system throughput due to suboptimal modulation and coding scheme (MCS) selection.
Innovation Solution
The method involves acquiring scheduling information of both the first and second user equipment, calculating a SINR predictor by considering interference from the second user equipment, and adjusting the historical SINR measurement value to improve the accuracy of MCS selection for the first user equipment, thereby enhancing the SINR predictor and MCS selection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only historical SINR measurement values are used for prediction, then the prediction method is simple, but the prediction accuracy decreases due to interference changes from neighboring cells
Solution Approach 1:
The patent combines historical SINR measurement values with scheduling information from neighboring cells to form a comprehensive SINR prediction method. This merging of multiple information sources resolves the contradiction by improving prediction accuracy through additional interference context while managing complexity through systematic integration of the combined data sources.
Solution Approach 2:
The patent performs preliminary acquisition and processing of scheduling information from neighboring cells before SINR prediction. By pre-obtaining interference information from cells using the same resource blocks and pre-processing this data, the system prepares interference context in advance, improving prediction accuracy without adding complex real-time processing requirements.
2Productivity
If MCS selection is based on inaccurate SINR prediction, then the system operation is simple, but the system throughput rate decreases
Solution Approach 1:
The patent implements feedback mechanisms where the base station monitors actual transmission performance and adjusts SINR prediction accordingly. By using feedback from scheduling decisions and transmission outcomes, the system continuously refines SINR prediction accuracy, which directly improves MCS selection and increases system throughput rate through more accurate adaptive modulation and coding.
Solution Approach 2:
The patent replaces simple historical SINR value extrapolation with a more sophisticated prediction mechanism that incorporates scheduling information analysis. This substitution transforms the prediction approach from basic time-series extrapolation to a system that analyzes interference patterns from neighboring cells, thereby improving both SINR accuracy and throughput performance.
3Measurement precision
If interference from neighboring cells is not considered, then the calculation process is simple, but the MCS selection accuracy decreases
Solution Approach 1:
The patent segments the SINR prediction process into distinct components: historical SINR analysis, scheduling information acquisition from neighboring cells, interference calculation, and combined prediction. This segmentation allows the system to incorporate complex interference modeling from multiple cells while maintaining manageable calculation complexity through structured modular processing.
Solution Approach 2:
The patent introduces scheduling information as an intermediary element that mediates between historical SINR data and final SINR prediction. This intermediary carries interference characteristics from neighboring cells, enabling accurate MCS selection by translating complex multi-cell interference patterns into actionable prediction adjustments without requiring direct complex calculations of all interference sources.
Data Source
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AI summary
Embodiments of the present invention provide an adaptive modulation and coding method and an apparatus, which relate to the communications field and can improve accuracy of MCS selection, thereby improving a system throughput rate. The method includes: acquiring scheduling information of first user equipment in a first cell; acquiring scheduling information of second user equipment in a second cell; acquiring a SINR predictor of the first user equipment according to the scheduling information of the first user equipment in the first cell and the scheduling information of the second user equipment in the second cell; obtaining a SINR adjustment value of the first user equipment according to the SINR predictor and a SINR adjustment amount; and determining, according to a correspondence between a SINR and a modulation and coding scheme MCS, an MCS corresponding to the SINR adjustment value of the first user equipment. The adaptive modulation and coding method and the apparatus that are provided in the embodiments of the present invention are used for adaptive modulation and coding.