What Is Echo Cancellation?

An echo is the reflected copy of an original sound that arrives at the listener with a delay. In voice communications, echo occurs due to impedance mismatch and is annoying to the users.

Echo cancellers are digital signal processing systems that adaptively estimate and cancel out the echo signal from the received signal.

They are essential components in modern telecommunication networks and audio conferencing systems to provide good voice quality.

Echo cancellers use advanced algorithms to model the echo path and subtract the estimated echo from the received signal.

Adaptive filtering tracks changes in the echo path characteristics. Additional processing like residual echo suppression, and doubletalk detection enhances the cancellation performance.

Digital echo cancellation is often implemented on DSP processors or FPGAs.

Causes of Echo in Telephone Networks

In telephone networks, echo occurs mainly due to impedance mismatches in the 2-wire to 4-wire conversion points along the signal path:

At the hybrid transformer between the local 2-wire loop and 4-wire long-distance network
At the customer premise equipment like speakerphones, PBXs, etc.

The mismatch causes the talker’s voice from the far end to reflect, arriving as an echo at the near-end talker. This is called electrical echo.

Acoustical echo happens when sound from loudspeakers reflects into the microphone in a hands-free speakerphone.

Hybrid echo is a combination of electrical and acoustical echoes.

Echo Canceller Operation

The key idea in echo cancellation is to adaptively model the echo path impulse response using a digital filter called the echo canceller filter.

This filter estimates the echo signal, which is then subtracted from the received signal containing both talker speech and echo.

The echo canceller filter coefficients are updated continuously using an adaptive algorithm to account for changes in the echo path over time.

Additional processing suppresses the residual echo left after cancellation by attenuating signals during single talk. Doubletalk detection pauses filter adaptation during near-end speech to prevent divergence.

Echo Path Modelling

The echo path impulse response depends on the network topology, routing, type of equipment producing the echo, etc.

Mathematical modeling helps estimate the echo characteristics for developing canceller algorithms.

Some common echo path models are:

1. Finite Impulse Response (FIR) Model

The echo path is modeled as an FIR filter represented by a tap delay line. LMS or RLS algorithms adapt tap weights to match the impulse response.

Simpler but often effective for electrical echoes.

2. Infinite Impulse Response (IIR) Model

Echo path modeled by an IIR filter capable of representing long impulse responses concisely. filtered-X LMS methods used for adaptation.

Complexity is higher than the FIR model.

3. Neural Network Model

Neural networks can model nonlinear echo paths. Used mainly for acoustic echoes. Echo canceller converges faster than conventional methods.

Accurate modeling is key for echo cancellation performance in real-world conditions. Model structure impacts the speed of adaptation, computational complexity, and storage requirements.

Adaptive Filter Algorithms

Adaptive filters dynamically adjust their coefficients to minimize the error between the actual echo signal and the estimated echo generated by the canceller filter.

Two commonly used algorithms are:

1. Least Mean Squares (LMS)

A stochastic gradient descent method that updates filter taps to converge on the minimum mean square error. Simple, efficient, and robust but slow convergence.

2. Recursive Least Squares (RLS)

Updates filter coefficients based on least squares regression for faster convergence than LMS. However, complexity increases due to matrix inversions.

3. Variants like Normalized LMS (NLMS)

Improve convergence speed while keeping complexity low. Other algorithms include affine projection, frequency-domain block LMS, etc.

The algorithm is chosen based on the speed of adaptation, computational power, and storage constraints.

Additional Echo Canceller Features

Along with adaptive filtering, certain enhancements in echo canceller improve performance:

Double Talk Detector – Freezes filter adaptation when the near-end user is talking to prevent canceller divergence. Detects double talk based on signal levels and cross-correlation.
Nonlinear Processor – Suppresses residual echo left after cancellation using center clipping, noise injection, etc. Effective for echoes with nonlinear components.
Comfort Noise Generator – Adds background comfort noise when suppressing residual echo to mask unnatural silence in speech.
Voice Activity Detector – Reduces computational complexity by adapting filters only during active echo periods.

Echo Cancellation in VoIP Networks

Packet voice networks like VoIP and video conferencing also use echo cancellers, implemented in IP phones or media gateways.

Additional challenges compared to PSTN networks:

Variable echo paths due to dynamic call routing
Delay fluctuations cause misalignment between echo and cancellation signal
Loss of tail end of echo due to packet loss
Low bitrate voice coding artifacts

Adaptive jitter buffers, reserved bandwidth, and special VAD techniques are used to improve cancellation.

Overall higher canceller complexity is required compared to traditional circuits.

Applications of Echo Cancellation

Key applications and use cases for echo cancellation include:

PSTN networks – Cancellers at 2W to 4W hybrid junctions, trunk exchanges, and national tandem exchanges.
Voice over IP – Implemented at end devices or media gateways in VoIP and video conferencing.
Audio conferences – Used in multi-point bridging units to suppress echoes between participants.
Automotive hands-free kits – Cancels in-car echoes for clearer hands-free voice calls.
Professional audio systems – Add echo cancellation for PA systems, and smart conference rooms.
Hearing aids – Miniature echo cancellers improve hearing aid performance.
Remote education – Cancels unwanted echoes in video lecture streaming applications.

Frequently Asked Questions (FAQ)

Ques 1. What causes echo in telephone networks?

Ans. Echo is mainly caused by impedance mismatch at 2-wire to 4-wire junctions and hybrids resulting in electrical echo.

Acoustic echo happens due to loudspeaker-microphone coupling.

Ques 2. How does an echo canceller work?

Ans. Echo cancellers adaptively model the echo path using a digital filter to generate an echo estimate, which is subtracted from the received signal to cancel out the actual echo.

Ques 3. What are the main components of an echo canceller?

Ans. Key components are an adaptive filter, double-talk detector, residual echo suppressor, voice activity detector, and comfort noise generator.

Ques 4. What adaptive algorithms are used in echo cancellers?

Ans. Common adaptive algorithms used are LMS, NLMS, RLS, and their variants. Complexity vs convergence speed trade-off is considered for algorithm selection.