Antenna Array Precoding With Distortion-Reducing PA Compensation
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Solution Overview
Problem
Power amplifiers in wireless communication systems exhibit nonlinear characteristics and drift over time due to temperature changes, voltage variations, and channel changes, leading to distortion that existing technologies struggle to manage effectively.
Innovation Solution
Implement a distortion reducing matrix in the signal processing chain to minimize error signals at power amplifier outputs, combined with digital pre-distortion models to compensate for nonlinear distortions, and update the matrix coefficients based on feedback to adapt to changes in PA behavior and coupling effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If power amplifiers operate near saturation region to improve efficiency, then energy efficiency is improved, but distortion increases due to nonlinear characteristics
Solution Approach 1:
The system applies preliminary digital predistortion to the signal before it reaches the power amplifier. The predistorter pre-compensates for the nonlinear characteristics of the PA by applying an inverse distortion function, so that when the signal passes through the nonlinear PA, the overall effect is linear amplification with improved efficiency and reduced distortion
Solution Approach 2:
The system implements feedback mechanisms where the output of the power amplifier is monitored and compared with the expected output. The error signal is used to adjust the predistortion parameters in real-time, compensating for drift and changes in PA characteristics due to temperature, voltage, and aging effects
2Object-generated harmful factors
If digital predistortion models are used to compensate nonlinear distortion, then distortion is reduced, but model complexity and processing requirements increase
Solution Approach 1:
The system uses dynamic adaptation of predistortion models based on operating conditions. The complexity of the predistortion model is adjusted according to the actual distortion levels and operating point of the power amplifier, using simpler models when distortion is low and more complex models when distortion increases, optimizing the trade-off between distortion compensation and processing complexity
Solution Approach 2:
The system changes parameters of the predistortion model based on operating conditions such as temperature, voltage, and power level. By adapting model parameters rather than using fixed complex models, the system achieves effective distortion compensation while maintaining manageable model complexity and processing requirements
3Measurement precision
If PA characteristics are managed to account for drift over time, then distortion compensation accuracy is improved, but system complexity and retraining requirements increase
Solution Approach 1:
The system implements self-calibration and self-adjustment mechanisms where the predistortion parameters are automatically updated based on monitoring the actual PA output and comparing it with expected values. The system performs self-diagnosis and self-correction without requiring external intervention or complex manual recalibration procedures
Solution Approach 2:
The system maintains continuous tracking and adjustment of predistortion parameters to compensate for drift in PA characteristics. Rather than periodic retraining, the system continuously adapts the predistortion model to match current PA behavior, ensuring sustained accuracy without interrupting operation or requiring complex batch retraining procedures
Data Source
AI summary
An apparatus may be configured to receive a signal to be transmitted via an array of antennas by a zero-forcing precoder, wherein the signal is processed by the linear precoder based on one or more input power criteria for power amplifiers of the array of antennas; apply a distortion reducing matrix to the processed signal, wherein the distortion reducing matrix is trained to reduce the distortion at each output of the power amplifiers based on minimizing an error signal corresponding to a difference between measured and calculated outputs of the power amplifiers after a coupling effect between the power amplifiers based on the applied matrices; and provide an output of the distortion reducing matrix to be used in digital pre-distortion processing of an input signal for the power amplifiers.