Adaptive Power Amplifier Predistortion via Remote DPD Updates
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Solution Overview
Problem
Existing power amplifier (PA) distortion estimation methods are computationally intensive and costly, especially for small base stations, due to the need for constant feedback loops and complex signal processing, which becomes even more challenging in 6G networks with increased base station density and complex operating conditions.
Innovation Solution
A method and system for adaptively updating digital predistortion (DPD) models by offloading the analysis from individual base stations to a remote computing device or cloud service, using a training device to determine updated DPD parameters based on input and output signals from the base stations, and transmitting these updates efficiently to reduce hardware and computational burdens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If constant feedback loops and complex signal processing are used for PA distortion estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts the computationally intensive distortion estimation and DPD parameter update functions from the base station hardware and relocates them to a remote training device. This removes the complex feedback loops and signal processing requirements from the base station, reducing device complexity while maintaining measurement precision through cloud-based processing.
Solution Approach 2:
The patent introduces a remote training device as an intermediary between the base station and the DPD model. This intermediary handles the complex computations and feedback processing, allowing the base station to maintain simple hardware while achieving accurate distortion estimation through the mediating cloud-based system.
2Measurement precision
If computationally intensive distortion estimation methods are used, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent extracts the energy-intensive computational tasks from the base station and relocates them to a remote training device with dedicated processing resources. This separation allows the base station to consume minimal energy for basic signal transmission while the cloud-based system handles the computationally demanding distortion estimation and DPD parameter updates.
3Adaptability or versatility
If DPD model updates are performed frequently to account for changing operating conditions, then adaptability is improved, but productivity decreases
Solution Approach 1:
The patent implements dynamic DPD model updates triggered by changes in operating conditions such as temperature, load, or frequency. The system continuously monitors these conditions and automatically initiates model updates only when necessary, balancing adaptability to changing conditions with efficient resource utilization and maintained productivity.
Solution Approach 2:
The patent establishes a feedback mechanism where the base station transmits PA input and output signals to the remote training device, which processes the data and returns updated DPD parameters. This feedback loop enables the system to adapt to changing operating conditions while maintaining productivity through automated, on-demand updates rather than continuous processing.
Data Source
AI summary
Methods and systems and devices for adaptively updating digital predistortion parameters for a power amplifier distortion model in a wireless communications network base station. The updated parameters are determined by a computing device separate from the base station. The base station monitors one or more operating conditions. When an operating condition differs from a stored operating condition by more than a threshold amount, the base station requests a parameter update from the computing device and receives a scheduled time to submit signals. Power amplifier input and output signals are provided to the computing device at the schedule time and the computing device determines the updated power amplifier distortion model and, consequently, the updated predistortion parameters, which it provides to the base station.