Dynamic Digital Predistortion for PA Memory Effects and CPL
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current digital pre-distortion techniques for high power amplifiers in radio transmitters are inefficient, especially for high efficiency PAs like Doherty PAs, as they fail to maintain good Channel Power Leakage (CPL) and Spectral Emission Mask requirements, especially during rapid power transitions, and are not optimized for highly non-linear PAs or single-chip implementation.
Innovation Solution
A dynamic digital pre-distortion engine that uses a composite of linear filters and high-order term filters with programmable coefficients to predistort the input signal, dynamically correcting PA non-linearity and memory effects, implemented using embedded hardware to handle rapid signal changes and fit within a single chip.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional digital pre-distortion techniques are used for high efficiency PAs like Doherty PAs, then PA efficiency can be improved, but Channel Power Leakage (CPL) performance deteriorates and spectral emission mask requirements are not met
Solution Approach 1:
The pre-distortion function is segmented into multiple independent lookup tables, each optimized for specific operating conditions (power levels, temperature ranges, modulation types). This allows selective application of appropriate pre-distortion characteristics without compromising overall performance across all conditions.
Solution Approach 2:
The system dynamically selects and switches between different pre-distortion lookup tables based on real-time operating conditions such as instantaneous power level, temperature, and signal characteristics. This dynamic adaptation ensures optimal CPL performance and spectral compliance while maintaining high PA efficiency across varying operational states.
2Stability of the object's composition
If digital pre-distortion is implemented to correct PA non-linearity, then linearity improves, but device complexity increases
Solution Approach 1:
Instead of implementing complex real-time computational pre-distortion algorithms, the system uses pre-computed lookup tables that store optimal pre-distortion characteristics. These tables are copied into the transmitter memory and applied through simple table lookup and interpolation operations, dramatically reducing computational complexity while maintaining linearity correction effectiveness.
Solution Approach 2:
The system changes the operational parameters of the pre-distortion function by storing multiple lookup tables with different characteristics optimized for various operating conditions. By selecting and switching between these parameter sets based on current operating state, the system achieves adaptive linearity correction without requiring complex real-time computation.
3Adaptability or versatility
If pre-distortion coefficients are updated dynamically to handle rapid power transitions, then adaptability improves, but processing speed requirements increase
Solution Approach 1:
Optimal pre-distortion lookup tables for various operating conditions are pre-computed and stored in memory before operation. When rapid power transitions occur, the system simply switches between pre-prepared tables rather than computing new coefficients in real-time, achieving fast adaptability without demanding high processing speeds.
Solution Approach 2:
The system replaces complex real-time computational mechanics with a memory-based lookup approach. Instead of mechanically computing pre-distortion coefficients during operation, the system uses electrical memory storage and retrieval, which is significantly faster and more suitable for handling rapid power transitions in modern transmitters.
Data Source
AI summary
A Dynamic Digital Pre-Distortion (DDPD) system is disclosed to rapidly correct power amplifier (PA) non-lincaiity and memory effects. To perform pre-distortion, a DDPD engine predistorts an input signal in order to cancel PA nonlinearities as the signal is amplified by the PA. The DDPD engine is implemented as a composite of one linear filter and N-1 high order term linear filters. The bank of linear filters have programmable complex coefficients. To compute the coefficients, samples from the transmit path and a feedback path are captured, and covariance matrices A and B are computed using optimized hardware. After the covariance matrices are computed, Gaussian elimination processing may be employed to compute the coefficients. Mathematical and hardware optimizations may be employed to simplify and reduce the number of multiplication operands and other operations, which can enable the DDPD system to fit within a single chip.