Adaptive Filter Gradient Sharing for Massive MIMO DPD Convergence
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Solution Overview
Problem
Massive Multiple-Input-Multiple-Output (MIMO) systems face challenges in computation load and convergence speed due to the large number of antennae, particularly in digital pre-distortion (DPD) algorithms, which struggle to efficiently track changes in power amplifier characteristics across numerous branches.
Innovation Solution
The proposed method transfers gradient-based information among all branches of the adaptive filter system, allowing uninterrupted parameter updates and improving convergence speed and tracking capability, by sharing gradient results and adjusting update rates based on branch similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of antennae is increased in massive MIMO systems, then beamforming capability is improved, but computation load and convergence speed of DPD algorithms deteriorate
Solution Approach 1:
The patent merges the parameter update processes of multiple antenna branches by transferring gradient-based information across all branches. Instead of independently updating each branch's parameters, the system combines gradient information from selected branches and uses it to update parameters across all branches simultaneously, reducing the overall computation load while maintaining beamforming capability
Solution Approach 2:
The patent creates a universal parameter update mechanism that serves all antenna branches. By computing gradient-based information for selected branches and transferring it to update parameters across all branches, the system achieves multi-functionality where a single computation process benefits the entire massive MIMO system, reducing redundant calculations
2Reliability
If the number of antennae is increased in massive MIMO systems, then beamforming capability is improved, but convergence speed of DPD algorithms deteriorates
Solution Approach 1:
The patent ensures continuous parameter updates across all branches by transferring gradient-based information. Instead of interrupting updates in non-selected branches, the system continuously updates all branches using transferred gradient information, maintaining uninterrupted convergence progress across the entire system
Solution Approach 2:
The patent implements a feedback mechanism where gradient-based information from selected branches is transferred and used to update parameters in all branches. This feedback loop allows the system to continuously refine parameters across all antenna branches, accelerating convergence while maintaining beamforming performance
3Speed
If gradient-based information is transferred among all branches, then convergence speed is improved, but communication overhead between branches increases
Solution Approach 1:
The patent applies local quality by selectively transferring gradient-based information only from and to specific branches rather than all-to-all communication. The system identifies selected branches for gradient computation and transfers information efficiently, reducing unnecessary communication overhead while maintaining convergence acceleration benefits
Data Source
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AI summary
A method in an adaptive filter system is provided. The method comprises obtaining parameters for a plurality of branches of the adaptive filter system (S310). The method further comprises computing gradient-based information for a selected one of the plurality of branches (S320). The method further comprises updating the parameters for the plurality of branches based on the gradient-based information for the selected branch (S330). An adaptive filter system is also provided.