Adaptive Echo Cancellation Using Foreground and Background Filters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing telecommunication systems face challenges in effectively canceling hybrid and acoustic echoes, which degrade voice quality and lead to intrusive echoes due to poor echo suppression and digital processing delays, especially in mixed technology networks.
Innovation Solution
An adaptive echo canceller system comprising a foreground filter and a background filter that work together to identify and cancel echo-induced peaks in a sparse impulse response, with the background filter performing a normalized least-mean square update and decimating data to enhance echo return loss, allowing for adaptive updates of finite impulse response filter coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional echo suppressors are used to block echo signals, then echo reduction is achieved, but voice quality deteriorates due to choppy syllables and artificial volume adjustment
Solution Approach 1:
The patent replaces traditional mechanical echo suppressors with adaptive digital signal processing techniques. Specifically, it uses adaptive filters (such as NLMS and RLS algorithms) that dynamically adjust filter coefficients to model and subtract echo paths, replacing the mechanical switching approach with computational methods that preserve voice quality while eliminating echo.
Solution Approach 2:
The patent employs adaptive filters that continuously change their parameters (filter coefficients) based on incoming signal characteristics. The filter adapts to varying echo paths by updating coefficients in real-time, allowing effective echo cancellation across different acoustic environments while maintaining natural voice transmission without the artifacts of traditional suppressors.
2Object-affected harmful factors
If adaptive filters continuously update coefficients to track echo paths, then echo cancellation performance improves, but computational complexity and processing delays increase
Solution Approach 1:
The patent implements dynamic adaptive filtering where filter coefficients are continuously updated to track time-varying echo paths. The system adapts its behavior based on signal conditions, adjusting the degree of adaptation to balance between tracking performance and processing speed, thereby reducing unnecessary computational delays while maintaining effective echo cancellation.
Solution Approach 2:
The patent applies adaptation only when necessary - specifically, it monitors signal conditions and activates full adaptive coefficient updates only when echo paths change significantly. During stable conditions, the system reduces adaptation activity, thereby decreasing computational load and processing delays while maintaining adequate echo cancellation performance.
3Object-affected harmful factors
If multiple adaptive algorithms are used to handle different echo scenarios, then echo suppression effectiveness improves, but system complexity increases
Solution Approach 1:
The patent segments the echo cancellation problem into distinct operational scenarios and applies different adaptive algorithms appropriate for each scenario. For example, it separates near-end speech detection from far-end echo cancellation, and applies specialized algorithms for each function, making the overall complex system manageable through functional segmentation.
Solution Approach 2:
The patent introduces intermediate processing stages and control mechanisms that coordinate multiple adaptive algorithms. These intermediaries manage the interaction between different algorithms, selecting and switching between them based on current signal conditions, thereby reducing the apparent complexity while maintaining comprehensive echo suppression effectiveness.
Data Source
AI summary
An echo canceller comprises foreground and background filters. The background filter locates and confirms peaks, defines active regions centered about the confirmed peaks and updates coefficients of the foreground filter when the background filter is more effective than the foreground filter. A method for improved adaptive echo cancellation comprises configuring a foreground filter, calculating an echo-return loss responsive to the foreground filter, identifying the location of one or more peaks repetitively in a block of data in a background filter, confirming one or more identified peaks over a defined number of blocks before defining an active region equally about the identified peaks in the background filter, filtering the sparse impulse response responsive to the active regions, calculating an echo-return loss responsive to the background filter, and updating the foreground filter when the background filter includes a more effective set of filter coefficients.