Digital Post-Distortion Slicing for PA Nonlinearity Drift
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless communication systems face challenges in accurately decoding signals due to non-linearities introduced by power amplifiers in base stations, leading to residual distortions that reduce the effectiveness of digital post-distortion techniques.
Innovation Solution
User equipment (UE) receives an indication of changes in the non-linearity model of the power amplifier from the base station, updates its model, and uses multiple coefficients for slicing operations to estimate and correct distortions, thereby improving the accuracy of digital post-distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital post-distortion techniques are used to correct power amplifier non-linearities, then signal decoding accuracy is improved, but residual distortions reduce the effectiveness of the correction
Solution Approach 1:
The base station performs preliminary actions by determining changes in its power amplifier's non-linearity model and proactively notifying the UE of these changes. This allows the UE to update its distortion model before receiving signals, ensuring the correction algorithm remains synchronized with the actual PA characteristics and maintains effectiveness despite drift over time.
Solution Approach 2:
The system implements feedback by having the base station monitor its own PA non-linearity model changes and communicate these changes to the UE. This closed-loop approach ensures the UE's correction model remains accurate by continuously adapting to PA drift, thereby maintaining signal decoding accuracy and post-distortion effectiveness.
2Measurement precision
If complex models and multiple coefficients are used for slicing operations, then digital post-distortion accuracy is improved, but power and processing resources are consumed
Solution Approach 1:
The base station performs preliminary analysis of its PA non-linearity characteristics and determines the essential model changes before notifying the UE. This allows the UE to update only the necessary portions of its distortion model rather than recomputing entire complex models, reducing processing overhead while maintaining correction accuracy.
Solution Approach 2:
The system changes parameters by having the base station identify and communicate specific non-linearity model changes rather than transmitting complete model datasets. The UE then updates its slicing coefficients and distortion model parameters selectively based on these change notifications, achieving accurate post-distortion with reduced computational burden and power consumption.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, an indication of a change in a non-linearity model associated with a power amplifier of the base station. The UE may update a model associated with the power amplifier based at least in part on the indication. The UE may further update at least one parameter associated with slicing received signals based at least in part on the indication. In some aspects, the UE may use at least two coefficients when slicing. Numerous other aspects are described.