Nonlinear Model Correction for Adjustable Communication Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing Volterra models are unable to accurately reflect changes in nonlinear characteristics of high-speed communication systems with adjustable parameters, requiring multiple measurements that increase temporal and spatial complexity and reduce efficiency.
Innovation Solution
An apparatus and method that determine a correction factor for nonlinear models based on input and parameter adjustments, allowing for the correction of nonlinear items and improved estimation of nonlinear characteristics under different conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the existing Volterra model is used for nonlinear estimation in systems with adjustable parameters, then the model structure is simple, but the model cannot accurately reflect changes in nonlinear characteristics when parameters change
Solution Approach 1:
The patent transforms the static Volterra model into a dynamic model by introducing a correction factor that adapts to parameter changes. The correction factor is determined based on the relationship between system parameters and nonlinear characteristics, allowing the model to dynamically adjust when parameters such as amplifier gain change, thus resolving the contradiction between model simplicity and adaptability.
Solution Approach 2:
The patent introduces a correction factor as a new parameter that captures the relationship between system parameters and nonlinear characteristics. By determining this correction factor based on parameter changes (such as amplifier gain variations), the model can accurately reflect nonlinear characteristic changes without increasing overall model complexity, thereby improving both accuracy and adaptability.
2Measurement precision
If multiple measurements are performed for different system parameters to estimate nonlinear characteristics, then the estimation accuracy for different parameters is improved, but the temporal and spatial complexity increases and efficiency decreases
Solution Approach 1:
The patent performs preliminary determination of the correction factor based on the relationship between system parameters and nonlinear characteristics. Once the correction factor is determined, it can be applied to estimate nonlinear characteristics for different parameters without requiring multiple separate measurements, thus improving efficiency while maintaining accuracy.
Solution Approach 2:
The correction factor serves as a universal element that can be applied across different system parameter conditions. By determining the correction factor once based on parameter relationships, it can be used to estimate nonlinear characteristics for various parameters (such as different amplifier gains), eliminating the need for separate measurements for each parameter and thereby improving measurement efficiency.
3Adaptability or versatility
If multiple measurements are performed for different system parameters, then the nonlinear characteristic estimation covers more parameter conditions, but the spatial complexity and resource requirements increase
Solution Approach 1:
The patent extracts the essential relationship between system parameters and nonlinear characteristics into a correction factor. This extracted correction factor captures the adaptability information needed for different parameter conditions without requiring complex measurement apparatuses for each condition, thus improving coverage while reducing spatial complexity.
Solution Approach 2:
The correction factor acts as an intermediary that bridges system parameters and nonlinear characteristics. By using this intermediary, the model can cover multiple parameter conditions without requiring separate measurement systems for each condition, thereby reducing the complexity of measurement apparatuses while maintaining broad adaptability.
Data Source
AI summary
Embodiments of the present disclosure provide a method and apparatus for determining a nonlinear characteristic and a system. The method for determining a nonlinear characteristic includes: determining a correction factor of a nonlinear item of a nonlinear model of a system to be measured according to an input and/or a parameter of the system to be measured; correcting the nonlinear item of a nonlinear model of the system to be measured by using the correction factor; and obtaining a nonlinear characteristic of the system to be measured according to the corrected nonlinear model. The nonlinear characteristic allows the input and/or the parameter of the system to be corrected to produce a corrected output. With the embodiments of the present disclosure, the nonlinear characteristic of the system to be measured under different inputs and/or parameters may be estimated, and accuracy of the estimation and applicability are improved.