Wireless Transmitter Calibration Using Neural Predistortion Feedback
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Solution Overview
Problem
Existing methods for correcting the nonlinearity of power amplifiers in wireless communication devices are inefficient due to the use of heuristic approaches, leading to performance degradation in transmission signals.
Innovation Solution
A wireless communication device that uses a neural network-based linearity calibration model to generate a calibration signal, which is then amplified to correct the nonlinearity of the power amplifier, thereby improving transmission performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If heuristic methods are used to select pre-distortion coefficients, then the transmitter nonlinearity can be corrected, but the performance degradation occurs due to difficulty in selecting appropriate coefficients
Solution Approach 1:
The system performs self-calibration by automatically selecting pre-distortion coefficients through iterative testing and evaluation without requiring manual intervention. The transmitter measures its own output signal quality and adjusts coefficients autonomously to optimize performance.
Solution Approach 2:
The system implements a feedback mechanism where the output signal from the power amplifier is measured and fed back to the pre-distortion coefficient selector. This feedback loop enables automatic adjustment of coefficients based on actual transmission performance, resolving the difficulty of manual coefficient selection.
2Power
If power amplifier amplification is increased to enhance signal strength, then transmission power is improved, but nonlinearity increases causing performance degradation
Solution Approach 1:
The system applies pre-distortion to the input signal before it enters the power amplifier. This preliminary anti-action counteracts the expected nonlinearity of the amplifier, allowing high power amplification while maintaining signal linearity through predictive compensation.
Solution Approach 2:
The system dynamically changes the pre-distortion coefficients based on the operating conditions and power level of the amplifier. By adjusting these parameters, the system maintains optimal linearity across different power levels, enabling high transmission power without sacrificing signal quality.
Data Source
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AI summary
An operating method of a wireless communication device, the method including generating an IQ compensation value by performing IQ mismatch compensation on a first input signal using a linearity calibration model, the linearity calibration model being based on a neural network, generating a pre-distortion value by performing pre-distortion on the first input signal using the linearity calibration model, generating a first calibration signal based on the IQ compensation value and the pre-distortion value, generating a calibrated first output signal by amplifying the first calibration signal based on an amplification coefficient, and training the linearity calibration model based on the first input signal and the calibrated first output signal.