Polyphase Volterra Filter Layout for Low-Complexity Echo Cancellation
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Solution Overview
Problem
Current echo compensation methods in communications systems face challenges with high computational complexity due to the need for non-linear Volterra filters, especially when dealing with varying sampling rates, which hinders real-time echo suppression with high accuracy.
Innovation Solution
The method involves resolving Volterra filters into polyphase components, allowing these components to be interchanged with sampling rate converters, thereby reducing computational complexity by performing calculations at a lower sampling frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-linear Volterra filters are used for echo compensation, then echo suppression accuracy is improved, but computational complexity increases
Solution Approach 1:
The Volterra filter is segmented into polyphase components, dividing the filter into L parallel sub-filters that process different phases of the input signal. This segmentation allows the computational load to be distributed and enables processing at a reduced sampling rate, thereby maintaining echo suppression accuracy while reducing overall computational complexity.
Solution Approach 2:
The sampling rate parameter is changed by exploiting the polyphase structure. Instead of processing all filter operations at the original high sampling rate, the polyphase components enable processing at a reduced sampling rate of f_s/L, significantly reducing the number of computations required while preserving the filter's echo suppression performance.
2Measurement precision
If non-linear filters are used in systems with varying sampling rates, then echo path simulation accuracy is improved, but computational resources required increase
Solution Approach 1:
The filter is divided into polyphase components that can be selectively applied based on the sampling rate conditions. This segmentation allows the system to maintain high simulation accuracy when needed while reducing computational resource consumption during normal operation by processing only the necessary polyphase components at the appropriate sampling rate.
Solution Approach 2:
The filter structure is made dynamic by allowing the sampling rate to vary based on processing requirements. The polyphase components enable the system to adaptively switch between different operating modes, using the full sampling rate when high accuracy is required and reduced sampling rates when computational resources are constrained.
Data Source
AI summary
A method for creating a form of a non-linear filter suitable for reducing a computational complexity is proposed. The filter is resolved into polyphase components in such a way that the polyphase components can be interchanged with a conversion of the sampling rate of a signal to be sent to the filter or of a signal to be emitted by the filter. Corresponding filters and filter arrangements are also proposed. In this way, a computational complexity for calculating the signal to be emitted by the filter can be significantly simplified. The invention can be used in echo compensation.