Wideband RF Transmitter Predistortion for Nonlinearity and Memory Effects
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Solution Overview
Problem
Existing models for dynamic nonlinear radio frequency transmitters face challenges in accurately identifying parameters, are complex, and fail to account for memory effects, making them unsuitable for broadband adaptive communications.
Innovation Solution
A behavioral model comprising a dynamic weak nonlinear (DWNL) module and a static strong nonlinear (SSNL) module, implemented as FIR-based filters and AM/AM, AM/PM lookup tables, respectively, to account for nonlinearity and memory effects in wideband RF transmitters, with augmented Wiener and Hammerstein predistorters for compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior art models are used for dynamic nonlinear systems, then model implementation is possible, but parameter identification is inaccurate and model accuracy is low
Solution Approach 1:
The behavioral model is segmented into multiple functional modules: a memoryless nonlinear module for static nonlinearities, a dynamic module for memory effects, and an identification module. This segmentation allows each module to be optimized independently, improving overall model accuracy while maintaining reliable parameter identification through specialized identification algorithms for each module.
2Measurement precision
If complex models are used to account for memory effects, then modeling accuracy improves, but device complexity increases
Solution Approach 1:
The model segments memory effects into manageable dynamic modules with specific functional responsibilities, allowing accurate representation of complex behaviors while maintaining modular structure that reduces overall system complexity and facilitates implementation.
Solution Approach 2:
The model uses parameter transformations and normalized representations to describe memory effects, allowing accurate modeling of dynamic behaviors through parameter adjustments rather than complex structural changes, thereby reducing model complexity while maintaining accuracy.
3Device complexity
If simple models are used, then device complexity is reduced, but memory effects are not accounted for and accuracy decreases
Solution Approach 1:
The dynamic module acts as an intermediary component that specifically handles memory effects between the input signal and the memoryless nonlinear module. This intermediary structure allows the model to account for memory effects without requiring complete model restructuring, maintaining relative simplicity while improving accuracy.
4Object-affected harmful factors
If accurate modeling of RF transmitters is implemented, then signal quality and interference are reduced, but system complexity increases
Solution Approach 1:
The transmitter modeling system is segmented into distinct functional modules that can be independently implemented and optimized. This allows accurate modeling of nonlinearities and memory effects to reduce interference while maintaining manageable system complexity through modular architecture.
Data Source
AI summary
Disclosed is a behavioral model for wide-band radio frequency transmitters. Also disclosed are various implementation of the behavioral model for purpose of baseband predistortion of dynamic nonlinear systems, such as wideband wireless transmitters and power amplifiers. In one example embodiment, a LBG behavioral model comprises two non-linear cascading modules: a dynamic weak nonlinear (DWNL) module, which models dynamic week nonlinearities of the system, and a static strong nonlinear (SSNL) module, which models static strong nonlinearities of the system. In one example embodiment, a forward LBG model includes DWNL module followed by the SSNL module. In another example embodiment, a reverse LBG model includes SSNL module followed by DWNL module.