DSL Vector Training Noise Detection for Accurate Crosstalk Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In DSL transmission systems, impulse noise can mislead error calculations during vector training, leading to suboptimal crosstalk reduction and increased bit error rates, especially when adding new communication connections to a vectored group.
Innovation Solution
An apparatus and method that differentiate between noise-induced and crosstalk error signals by evaluating noise indications, allowing for accurate adaptation of vectoring techniques, including the use of noise flags or multi-bit signals to ignore or limit error values affected by temporary noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error values are calculated based on transmitted and received signals during vector training, then crosstalk reduction can be achieved, but impulse noise causes misadaptation of vectoring leading to increased bit error rates
Solution Approach 1:
The system performs preliminary noise evaluation by comparing received synchronization symbols with expected values before using error values for vectoring adaptation. This preliminary action identifies impulse noise that would otherwise corrupt the adaptation process, allowing the system to prepare by selecting alternative error values or extending training periods.
Solution Approach 2:
Synchronization symbols serve as an intermediary element between transmitted and received signals. By evaluating these known symbols first, the system creates a reference point to detect noise before it affects the actual data transmission error calculations, thus mediating the harmful effect of impulse noise.
2Measurement precision
If vector training is performed to determine crosstalk influence when adding new communication connections, then crosstalk reduction is improved, but temporary noise leads to incorrect error values and misadaptation
Solution Approach 1:
The system performs preliminary evaluation of synchronization symbols to detect noise conditions before calculating error values for crosstalk measurement. This preliminary action ensures that only reliable error values derived from noise-free or minimally affected signals are used for vectoring adaptation.
Solution Approach 2:
The system uses feedback from synchronization symbol evaluation to adjust the vector training process. When noise is detected through synchronization symbol comparison, the system responds by selecting alternative error values or extending the training period, thereby maintaining measurement precision despite noisy conditions.
3Productivity
If error values dominated by impulse noise are used for vectoring adaptation, then adaptation speed is maintained, but bit error rates increase due to misadaptation
Solution Approach 1:
The system performs preliminary noise detection through synchronization symbol evaluation before proceeding with error value-based adaptation. This allows rapid identification of noise conditions and immediate selection of alternative adaptation strategies, maintaining overall adaptation speed while preventing misadaptation.
Solution Approach 2:
The system dynamically adjusts the vector training process based on real-time noise conditions detected during synchronization symbol evaluation. When noise is present, the system changes its behavior by selecting alternative error values or extending training, thereby adapting the adaptation process itself to maintain both speed and reliability.
Data Source
AI summary
In an embodiment, vector training signals are received. Noise affecting the training signals is evaluated, and a noise indication is thus determined.