Variable SNR Adjustment for Faster Outer Loop Link Adaptation
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Solution Overview
Problem
Wireless packet transmission consumes significant computing resources and time, and existing approaches can be improved.
Innovation Solution
A base station adjusts the signal-to-noise ratio by a variable amount based on the number of consecutive acknowledgements received, using non-linear outer loop link adaptation to optimize modulation and coding schemes for improved wireless packet transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wireless packet transmission uses traditional signal processing approaches, then transmission can be performed, but computing resources and time consumption are significant
Solution Approach 1:
The patent changes the parameter of SNR adjustment from fixed to variable based on successful signal interpretations. By dynamically adjusting the SNR adjustment amount according to the number of successful interpretations, the system optimizes the balance between transmission reliability and computing resource consumption, improving transmission efficiency while reducing unnecessary computational overhead.
Solution Approach 2:
The patent implements a feedback mechanism where the SNR adjustment amount is determined based on the number of successful signal interpretations. This feedback loop allows the system to adaptively optimize transmission parameters based on actual channel conditions and decoding success rates, thereby improving overall transmission efficiency and reducing wasted computing resources on failed transmissions.
2Measurement precision
If SNR adjustment uses fixed amounts, then implementation is simple, but convergence speed and signal quality estimation are slower
Solution Approach 1:
The patent transitions from static fixed SNR adjustment to dynamic variable SNR adjustment. The adjustment amount varies based on the number of successful signal interpretations, allowing the system to converge faster by applying larger adjustments when appropriate and finer adjustments when needed, thereby improving both convergence speed and estimation accuracy simultaneously.
Solution Approach 2:
By changing the SNR adjustment parameter from a fixed value to a variable value dependent on successful interpretations, the system achieves faster convergence. The variable parameter allows aggressive adjustments early in the process when more iterations are available, and finer adjustments later when convergence is near, optimizing both speed and precision.
3Productivity
If variable SNR adjustment based on successful interpretations is implemented, then convergence and estimation improve, but system complexity increases
Solution Approach 1:
The system performs self-service by using its own successful interpretation count to determine the SNR adjustment amount. This self-generated feedback requires minimal external control or complex external systems, achieving improved transmission efficiency through a relatively simple internal mechanism that leverages existing decoding success information.
Data Source
AI summary
Apparatuses, systems, and techniques to adjust one or more signal-to-noise ratios. In at least one embodiment, a processor includes one or more circuits to cause one or more signal-to-noise ratios to be adjusted by a variable amount based, at least in part, on a number of indications received by the processor indicating whether a signal was interpreted successfully.