RF Pre-Distorter Using Lookup-Table Nonlinear Gain Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital compensation methods for non-linear circuits, such as radio transmitter chains, face challenges in accurately linearizing the system while minimizing computational and storage requirements, and are not robust to variations in parameters and circuit characteristics.
Innovation Solution
A pre-distorter that uses diverse real-valued signals derived from the input, subjected to configurable non-linear transformations, with outputs serving as gain terms for complex signals, which are summed to compute the pre-distorted signal. This approach includes phase-invariant derived signals and time-varying gain components, efficiently implemented using lookup tables, and adapts to sensed output variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional digital pre-distortion methods are used to linearize non-linear circuits, then compensation accuracy is improved, but computational requirements and storage requirements increase significantly
Solution Approach 1:
The patent segments the pre-distortion function into multiple components: a non-linear magnitude function G(|u|) and a phase function H(∠u), each handled separately. This segmentation allows independent optimization of each function's complexity, reducing overall computational burden while maintaining compensation accuracy through specialized processing paths for magnitude and phase corrections.
Solution Approach 2:
The patent extracts the magnitude and phase components of the complex pre-distortion function into separate processing branches. By taking out the magnitude correction (through G function) and phase correction (through H function) as independent operations, the system avoids computing the full complex function directly, thereby reducing computational complexity while preserving the essential linearization functionality.
2Measurement precision
If complex pre-distortion functions with many parameters are used, then compensation accuracy is improved, but storage requirements increase
Solution Approach 1:
The patent segments the parameter set into magnitude-related parameters for function G and phase-related parameters for function H. This segmentation allows the system to store parameters separately in optimized data structures, reducing total storage requirements by eliminating redundant complex number representations and allowing independent optimization of each parameter set's storage efficiency.
Solution Approach 2:
The patent extracts real and imaginary components of the pre-distortion parameters into separate real-valued parameter sets for the magnitude function G and phase function H. By taking out the real and imaginary parts as independent parameter groups, the system reduces storage requirements by storing only necessary real values rather than full complex parameter structures.
3Reliability
If the pre-distorter is made robust to parameter variations, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic adaptation mechanisms that allow the pre-distorter to adjust its parameters in real-time based on sensed output variations. The system dynamically updates the magnitude function G and phase function H parameters to track changes in the power amplifier's characteristics, ensuring continued linearization performance despite parameter drift or environmental variations.
Solution Approach 2:
The patent incorporates feedback loops that sense the actual output of the power amplifier and use this information to adjust the pre-distortion parameters. By feeding back the sensed output and comparing it with the desired output, the system automatically compensates for parameter variations and maintains robust linearization performance without requiring complex manual recalibration.
Data Source
AI summary
A pre-distorter that both accurately compensates for the non-linearities of a radio frequency transmit chain, and that imposes as few computation requirements in terms of arithmetic operations, uses a diverse set of real-valued signals that are derived from the input signal. The derived real signals are passed through configurable non-linear transformations, which may be adapted during operation, and which may be efficiently, implemented using lookup tables. The outputs of the non-linear transformations serve as gain terms for a set of complex signals, which are functions of the input, and which are summed to compute the pre-distorted signal. A small set of the complex signals and derived real signals may be selected for a particular system to match the classes of non-linearities exhibited by the system, thereby providing further computational savings, and reducing complexity of adapting the pre-distortion through adapting of the non-linear transformations.