Iterative Eigenvector Estimation for Beamforming Computation
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Solution Overview
Problem
Current beamforming methods in wireless communication systems face challenges in efficiently computing eigenbeams, leading to suboptimal power distribution and increased interference, particularly as higher frequencies are used.
Innovation Solution
An iterative method is introduced to compute beamforming coefficients by obtaining a channel covariance matrix, initializing and refining eigenvector estimates, and determining error vectors, which reduces computational complexity and improves convergence, allowing for accurate beamforming coefficients calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional eigenvalue decomposition is used to compute eigenbeams, then beamforming can be implemented, but computational complexity increases and convergence is slow
Solution Approach 1:
The patent segments the eigenbeam computation into two parts: using a closed-form solution for initial eigenvector estimation and an iterative refinement process for improvement. This segmentation allows the computationally intensive part to be handled by efficient closed-form methods while the iterative part focuses only on refinement, reducing overall computational complexity.
Solution Approach 2:
The patent applies preliminary action by using closed-form solutions to obtain initial eigenvector estimates before entering the iterative refinement process. This preliminary estimation provides a good starting point that accelerates convergence and reduces the number of iterations needed, thereby improving computational efficiency.
2Productivity
If higher frequencies are used in wireless communication, then bandwidth and capacity improve, but power distribution becomes suboptimal and interference increases
Solution Approach 1:
The patent implements feedback through its iterative refinement process, where each iteration uses the error between the current and previous eigenvector estimates to adjust and improve the solution. This feedback mechanism ensures optimal power distribution and minimizes interference by continuously refining the beamforming coefficients based on channel conditions.
3Measurement precision
If iterative refinement is applied to compute eigenvectors, then estimation accuracy improves, but computational time increases
Solution Approach 1:
The patent applies partial action by performing iterative refinement only to the extent necessary to achieve sufficient accuracy. The process can be stopped after a predetermined number of iterations or when convergence criteria are met, avoiding unnecessary computational overhead while maintaining adequate estimation accuracy for practical applications.
Data Source
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AI summary
This document discloses a solution for computing beamforming coefficients for a radio channel between two apparatuses. According to an aspect, a method comprises: obtaining a channel matrix representing a radio channel between an apparatus and another apparatus; obtaining an initial eigenvector estimate for an eigenvector of the channel matrix; computing an intermediate eigenvector estimate based on the channel matrix and the initial eigenvector estimate; computing an error vector representing an error between the initial eigenvector estimate and the intermediate eigenvector estimate; computing a final eigenvector estimate based on the error vector and the intermediate eigenvector estimate; and determining beamforming coefficients based on the final eigenvector estimate and communicating with said another apparatus by using the beamforming coefficients.