Adaptive Echo Cancellation via Dynamic Step-Size Control
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Solution Overview
Problem
Communication devices face challenges in reducing echo signals in hands-free mode, as the local microphone picks up both user responses and audio from the loudspeaker, leading to echo contamination in the signal sent to the distant location, which affects audio clarity.
Innovation Solution
An audio processing device implements echo reduction by controlling a step-size parameter based on the cross-correlation of the local-microphone signal with a previous iteration's resultant signal, performing this calculation in the frequency domain to create a convergence value, allowing for larger step-sizes during initial convergence and smaller step-sizes as echo reduction progresses to avoid overshoot and oscillation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If echo cancellation is implemented using a fixed step-size parameter, then the echo reduction process is simple to implement, but the convergence speed is slow and the echo cancellation accuracy is limited
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed step-size parameter to a time-varying step-size parameter that adapts during the echo cancellation process. The step-size parameter changes over time to be larger during initial convergence for faster adaptation and smaller during steady-state for higher precision, resolving the contradiction between convergence speed and cancellation accuracy.
Solution Approach 2:
The patent implements parameter changes by modifying the step-size parameter based on the convergence state of the echo cancellation algorithm. By monitoring convergence metrics and adjusting the step-size parameter accordingly, the system achieves both fast initial convergence and high steady-state accuracy without requiring complex additional hardware.
2Speed
If a large step-size parameter is used for fast convergence, then the initial convergence speed is improved, but the system overshoots and oscillates during echo reduction
Solution Approach 1:
The patent applies periodic action by implementing a two-phase echo cancellation process: an initial phase with larger step-size for fast convergence and a steady-state phase with smaller step-size for stability. This periodic switching between different step-size regimes allows the system to achieve both fast convergence and stable echo reduction without overshoot or oscillation.
Solution Approach 2:
The patent uses dynamics to make the step-size parameter adaptive rather than fixed. By dynamically adjusting the step-size based on the convergence state (using metrics like cross-correlation between reference and error signals), the system automatically transitions from aggressive initial convergence to gentle steady-state refinement, eliminating oscillations while maintaining fast overall convergence.
3Stability of the object's composition
If a small step-size parameter is used to avoid overshoot, then the echo reduction stability is improved, but the convergence speed becomes slow
Solution Approach 1:
The patent resolves this contradiction by making the step-size parameter dynamic and time-dependent. During the initial convergence phase, a larger step-size is used to achieve fast convergence while the system is far from the optimal solution. As convergence progresses and the system approaches the optimal solution, the step-size is reduced to ensure stability and prevent overshoot, thus achieving both fast initial convergence and stable final convergence.
Solution Approach 2:
The patent applies preliminary action by using a larger step-size parameter during the initial phase of echo cancellation when the adaptive filter coefficients are far from their optimal values. This preliminary aggressive adjustment accelerates convergence toward the solution, after which the step-size is reduced for fine-tuning, thereby achieving fast overall convergence without sacrificing final stability.
4Measurement precision
If the step-size parameter is dynamically adjusted based on cross-correlation, then the echo cancellation accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent implements parameter changes by adjusting the step-size parameter based on cross-correlation calculations between the reference signal and the error signal. This adaptive parameter adjustment improves echo cancellation accuracy by optimizing the convergence behavior, while the use of efficient cross-correlation algorithms minimizes the additional computational burden.
Solution Approach 2:
The patent replaces complex mechanical or hardware-based echo cancellation mechanisms with signal processing algorithms that use cross-correlation to adaptively control the step-size parameter. This substitution achieves high echo cancellation accuracy through software-based adaptive filtering, reducing the need for complex hardware while maintaining or improving performance.
Data Source
AI summary
Echo reduction. At least one example embodiment is a method including producing, by a loudspeaker, acoustic waves based on a far-microphone signal; receiving, at a local microphone, an echo based on the acoustic waves, and receiving acoustic waves generated locally, the receiving creates a local-microphone signal; producing an estimated-echo signal based on the far-microphone signal and a current step-size parameter; summing the local-microphone signal and the estimated echo signal to produce a resultant signal having reduced echo in relation to the local-microphone signal; and controlling the current step-size parameter. The controlling current step size may include: calculating a convergence value based on a cross-correlation of the local-microphone signal and the resultant signal; and updating the current step-size parameter based on the convergence value.