Power Amplifier Predistortion With Iterative Convergence Estimation
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Solution Overview
Problem
Current methods for computing complex division in RF power amplifiers require resource-intensive data conversion and division operations, which are inefficient and consume significant resources.
Innovation Solution
An iterative computation method that selects a complex factor for each computation interval, estimates the solution value, and calculates cumulative error independently, terminating when a convergence criterion is met, thereby avoiding preliminary data conversion and division operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional complex division techniques (coordinate rotation or complex conjugate multiplication) are used, then complex gain calculation is achieved, but resource-intensive data conversion and division operations are required
Solution Approach 1:
The patent extracts and eliminates the complex division operation from the calculation process. Instead of performing full complex division to compute complex gain, the system uses an iterative approach that only requires complex multiplication and error computation, removing the resource-intensive division step while maintaining calculation accuracy through convergence-based refinement.
Solution Approach 2:
The patent implements a dynamic iterative computation process where the complex gain estimate is continuously refined over multiple computation intervals. The system adapts the number of iterations based on convergence criteria, allowing the calculation to proceed with minimal resources when sufficient accuracy is achieved, rather than requiring fixed resource allocation for complete division operations.
2Productivity
If iterative computation with convergence criteria is used, then resource consumption is reduced, but computation time may extend beyond single computation interval
Solution Approach 1:
The patent implements feedback through convergence criteria that monitor the cumulative error in each iteration. The computation automatically terminates when the error falls below a threshold, providing a dynamic stopping condition that balances resource efficiency with computational completeness. This feedback mechanism prevents unnecessary iterations while ensuring sufficient accuracy is achieved.
Solution Approach 2:
The iterative computation maintains continuous refinement of the complex gain estimate across computation intervals, rather than performing discrete complete divisions. The useful action of error reduction continues incrementally, allowing the system to achieve sufficient accuracy progressively rather than requiring complete computation in each interval, thus reducing overall resource consumption.
Data Source
AI summary
To estimate complex factors for use in predistortion of a power amplifier, a complex factor is selected a set of complex factors a computation interval. A solution value is estimated for the selected complex factor during the computation interval by an iterative computation that constrains the estimated solution value towards a final solution value over an arbitrary number of iterations that is not bounded by the duration of the computation interval. A cumulative error in the estimated solution value is computed at each iteration over consecutive computation intervals. From the cumulative error, it is determined whether a convergence criterion is met and, if so, the estimating is terminated. The termination occurs independently of the solution value estimated for any one of the complex factors in the set.