DSL Crosstalk Reduction via Channel Grouping and Weighting
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Solution Overview
Problem
In high-density DSL transmission systems, the computational effort for crosstalk reduction increases with the number of transmission channels, making full vectoring computationally complex and inefficient, particularly when dealing with a large number of communication lines, prompting the need for partial vectoring and selective crosstalk reduction strategies.
Innovation Solution
The solution involves grouping transmission channels into at least two groups, selecting a part of these channels for crosstalk reduction based on grouping, and using weighting factors to prioritize channels with higher crosstalk strengths and target bit rates, thereby optimizing crosstalk reduction and power control across the communication lines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full vectoring is applied to all transmission channels for crosstalk reduction, then crosstalk reduction effectiveness is improved, but computational complexity increases significantly
Solution Approach 1:
The patent divides all transmission channels into multiple groups (first group, second group, etc.) and applies crosstalk reduction only to selected groups based on their crosstalk characteristics. This segmentation allows the system to focus computational resources on channels that benefit most from vectoring, thereby reducing overall computational complexity while maintaining effective crosstalk reduction where needed.
Solution Approach 2:
The patent applies different crosstalk reduction strategies to different groups of channels based on their local characteristics. Channels in the first group (with higher crosstalk strength or target bit rate) receive full vectoring treatment, while channels in the second group may receive reduced or no crosstalk reduction. This local quality approach optimizes the balance between performance and complexity by tailoring the treatment to each channel group's specific needs.
2Productivity
If partial vectoring is used to reduce computational complexity, then computational efficiency is improved, but crosstalk reduction effectiveness deteriorates
Solution Approach 1:
The patent implements partial vectoring by selecting only certain channel groups (first group) for crosstalk reduction while excluding others (second group). This partial action approach maintains computational efficiency by avoiding full vectoring across all channels, while still achieving effective crosstalk reduction in the selected groups where it provides the most benefit based on their crosstalk strength and target bit rate characteristics.
Solution Approach 2:
The patent uses weighting factors associated with each channel group to prioritize which groups should receive crosstalk reduction. By changing the selection parameters (based on crosstalk strength, target bit rate, and weighting factors), the system dynamically determines the optimal set of channels for partial vectoring, thereby maintaining effectiveness while improving computational efficiency.
3Object-affected harmful factors
If spectrum balancing is applied to control transmission powers, then crosstalk effect reduction is improved, but system complexity increases
Solution Approach 1:
The patent combines spectrum balancing with the grouped channel structure, applying transmission power control only to channels in the first group that are selected for crosstalk reduction. This segmentation approach reduces system complexity by avoiding spectrum balancing across all channels, while still effectively reducing crosstalk effects in the prioritized channel groups.
Data Source
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AI summary
Methods and devices are disclosed involving crosstalk reduction depending on weighting factors or grouping of transmission channels. In other embodiments, other methods or devices may be used.