Multi-Band Digital Predistortion With Lookup-Table Nonlinearity Compensation
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Solution Overview
Problem
Existing methods for linearizing non-linear power amplifiers and radio transmitter chains with multi-band inputs face challenges in accurately compensating for non-linearities while minimizing computational and storage requirements, and are often inefficient in handling variations in parameter values and system characteristics.
Innovation Solution
A pre-distorter system that uses diverse real-valued signals derived from input signals and their combinations, subjected to configurable non-linear transformations, with gain-adjusted complex signals summed to compute the pre-distorted signal, which is efficiently implemented using lookup tables and adapted based on sensed output to maintain robustness and reduce complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional pre-distortion methods are used to linearize non-linear power amplifiers, then compensation for non-linearities is achieved, but computational requirements and storage requirements increase significantly
Solution Approach 1:
The patent segments the multi-band input signal into multiple separate frequency bands, processes each band independently through dedicated pre-distortion functions, and then combines the processed bands. This segmentation allows the system to handle non-linearities in each band separately, reducing the overall computational complexity compared to processing the entire multi-band signal as a single complex entity.
Solution Approach 2:
The patent employs parameterized pre-distortion functions with configurable parameters that can be adapted to match the specific characteristics of the power amplifier. By using parameterized models rather than fixed complex transformations, the system achieves accurate non-linearity compensation while maintaining lower computational requirements through efficient parameter management and lookup tables.
2Reliability
If pre-distortion parameters are made robust to variation in system characteristics, then performance degradation is reduced, but the complexity of parameter adaptation increases
Solution Approach 1:
The patent uses parameterized pre-distortion functions where the parameters can be adapted to match variations in power amplifier characteristics. The parameterized model allows for systematic adjustment of pre-distortion behavior to compensate for different operating conditions and amplifier variations, achieving robustness through controlled parameter changes rather than complex adaptive algorithms.
Solution Approach 2:
The patent incorporates feedback mechanisms where the output of the power amplifier is measured and used to adjust the pre-distortion parameters. This feedback loop enables the system to adapt to variations in system characteristics automatically, maintaining performance robustness while keeping the adaptation process manageable through iterative parameter refinement rather than complex real-time optimization.
3Object-generated harmful factors
If separate processing of multiple frequency bands is implemented, then unwanted emissions between bands are reduced, but the device complexity increases
Solution Approach 1:
The patent divides the multi-band input signal into separate frequency bands, applies independent pre-distortion processing to each band, and then combines the processed bands. This segmentation approach prevents intermodulation distortion and unwanted emissions between bands by handling each band separately, while the modular structure of the processing functions keeps the implementation complexity manageable.
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 separate band signals that make up 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.