231 lines
9.1 KiB
C
231 lines
9.1 KiB
C
/*
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* SpanDSP - a series of DSP components for telephony
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*
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* echo.c - A line echo canceller. This code is being developed
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* against and partially complies with G168.
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*
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* Written by Steve Underwood <steveu@coppice.org>
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* and David Rowe <david_at_rowetel_dot_com>
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*
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* Copyright (C) 2001 Steve Underwood and 2007 David Rowe
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*
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* All rights reserved.
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License version 2, as
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* published by the Free Software Foundation.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
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*
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* $Id: echo.h,v 1.9 2006/10/24 13:45:28 steveu Exp $
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*/
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/*! \file */
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#if !defined(_ECHO_H_)
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#define _ECHO_H_
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/*! \page echo_can_page Line echo cancellation for voice
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\section echo_can_page_sec_1 What does it do?
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This module aims to provide G.168-2002 compliant echo cancellation, to remove
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electrical echoes (e.g. from 2-4 wire hybrids) from voice calls.
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\section echo_can_page_sec_2 How does it work?
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The heart of the echo cancellor is FIR filter. This is adapted to match the echo
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impulse response of the telephone line. It must be long enough to adequately cover
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the duration of that impulse response. The signal transmitted to the telephone line
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is passed through the FIR filter. Once the FIR is properly adapted, the resulting
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output is an estimate of the echo signal received from the line. This is subtracted
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from the received signal. The result is an estimate of the signal which originated
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at the far end of the line, free from echos of our own transmitted signal.
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The least mean squares (LMS) algorithm is attributed to Widrow and Hoff, and was
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introduced in 1960. It is the commonest form of filter adaption used in things
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like modem line equalisers and line echo cancellers. There it works very well.
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However, it only works well for signals of constant amplitude. It works very poorly
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for things like speech echo cancellation, where the signal level varies widely.
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This is quite easy to fix. If the signal level is normalised - similar to applying
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AGC - LMS can work as well for a signal of varying amplitude as it does for a modem
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signal. This normalised least mean squares (NLMS) algorithm is the commonest one used
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for speech echo cancellation. Many other algorithms exist - e.g. RLS (essentially
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the same as Kalman filtering), FAP, etc. Some perform significantly better than NLMS.
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However, factors such as computational complexity and patents favour the use of NLMS.
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A simple refinement to NLMS can improve its performance with speech. NLMS tends
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to adapt best to the strongest parts of a signal. If the signal is white noise,
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the NLMS algorithm works very well. However, speech has more low frequency than
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high frequency content. Pre-whitening (i.e. filtering the signal to flatten
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its spectrum) the echo signal improves the adapt rate for speech, and ensures the
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final residual signal is not heavily biased towards high frequencies. A very low
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complexity filter is adequate for this, so pre-whitening adds little to the
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compute requirements of the echo canceller.
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An FIR filter adapted using pre-whitened NLMS performs well, provided certain
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conditions are met:
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- The transmitted signal has poor self-correlation.
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- There is no signal being generated within the environment being cancelled.
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The difficulty is that neither of these can be guaranteed.
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If the adaption is performed while transmitting noise (or something fairly noise
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like, such as voice) the adaption works very well. If the adaption is performed
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while transmitting something highly correlative (typically narrow band energy
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such as signalling tones or DTMF), the adaption can go seriously wrong. The reason
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is there is only one solution for the adaption on a near random signal - the impulse
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response of the line. For a repetitive signal, there are any number of solutions
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which converge the adaption, and nothing guides the adaption to choose the generalised
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one. Allowing an untrained canceller to converge on this kind of narrowband
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energy probably a good thing, since at least it cancels the tones. Allowing a well
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converged canceller to continue converging on such energy is just a way to ruin
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its generalised adaption. A narrowband detector is needed, so adapation can be
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suspended at appropriate times.
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The adaption process is based on trying to eliminate the received signal. When
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there is any signal from within the environment being cancelled it may upset the
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adaption process. Similarly, if the signal we are transmitting is small, noise
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may dominate and disturb the adaption process. If we can ensure that the
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adaption is only performed when we are transmitting a significant signal level,
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and the environment is not, things will be OK. Clearly, it is easy to tell when
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we are sending a significant signal. Telling, if the environment is generating a
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significant signal, and doing it with sufficient speed that the adaption will
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not have diverged too much more we stop it, is a little harder.
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The key problem in detecting when the environment is sourcing significant energy
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is that we must do this very quickly. Given a reasonably long sample of the
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received signal, there are a number of strategies which may be used to assess
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whether that signal contains a strong far end component. However, by the time
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that assessment is complete the far end signal will have already caused major
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mis-convergence in the adaption process. An assessment algorithm is needed which
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produces a fairly accurate result from a very short burst of far end energy.
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\section echo_can_page_sec_3 How do I use it?
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The echo cancellor processes both the transmit and receive streams sample by
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sample. The processing function is not declared inline. Unfortunately,
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cancellation requires many operations per sample, so the call overhead is only a
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minor burden.
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*/
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#include "../../config.h"
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#ifdef HAVE_MMX_INSTRUCTIONS
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#define USE_MMX
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#endif
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#ifdef HAVE_SSE2_INSTRUCTIONS
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#define USE_SSE2
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#endif
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#include "fir.h"
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/* Mask bits for the adaption mode */
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#define ECHO_CAN_USE_ADAPTION 0x01
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#define ECHO_CAN_USE_NLP 0x02
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#define ECHO_CAN_USE_CNG 0x04
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#define ECHO_CAN_USE_CLIP 0x08
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#define ECHO_CAN_USE_TX_HPF 0x10
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#define ECHO_CAN_USE_RX_HPF 0x20
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#define ECHO_CAN_DISABLE 0x40
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/*!
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G.168 echo canceller descriptor. This defines the working state for a line
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echo canceller.
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*/
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typedef struct
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{
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int16_t tx,rx;
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int16_t clean;
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int16_t clean_nlp;
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int nonupdate_dwell;
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int curr_pos;
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int taps;
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int log2taps;
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int adaption_mode;
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int cond_met;
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int32_t Pstates;
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int16_t adapt;
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int32_t factor;
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int16_t shift;
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/* Average levels and averaging filter states */
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int Ltxacc, Lrxacc, Lcleanacc, Lclean_bgacc;
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int Ltx, Lrx;
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int Lclean;
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int Lclean_bg;
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int Lbgn, Lbgn_acc, Lbgn_upper, Lbgn_upper_acc;
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/* foreground and background filter states */
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fir16_state_t fir_state;
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fir16_state_t fir_state_bg;
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int16_t *fir_taps16[2];
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/* DC blocking filter states */
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int tx_1, tx_2, rx_1, rx_2;
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/* optional High Pass Filter states */
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int32_t xvtx[5], yvtx[5];
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int32_t xvrx[5], yvrx[5];
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/* Parameters for the optional Hoth noise generator */
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int cng_level;
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int cng_rndnum;
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int cng_filter;
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/* snapshot sample of coeffs used for development */
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int16_t *snapshot;
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} echo_can_state_t;
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/*! Create a voice echo canceller context.
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\param len The length of the canceller, in samples.
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\return The new canceller context, or NULL if the canceller could not be created.
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*/
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echo_can_state_t *echo_can_create(int len, int adaption_mode);
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/*! Free a voice echo canceller context.
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\param ec The echo canceller context.
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*/
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void echo_can_free(echo_can_state_t *ec);
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/*! Flush (reinitialise) a voice echo canceller context.
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\param ec The echo canceller context.
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*/
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void echo_can_flush(echo_can_state_t *ec);
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/*! Set the adaption mode of a voice echo canceller context.
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\param ec The echo canceller context.
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\param adapt The mode.
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*/
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void echo_can_adaption_mode(echo_can_state_t *ec, int adaption_mode);
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void echo_can_snapshot(echo_can_state_t *ec);
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/*! Process a sample through a voice echo canceller.
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\param ec The echo canceller context.
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\param tx The transmitted audio sample.
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\param rx The received audio sample.
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\return The clean (echo cancelled) received sample.
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*/
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int16_t echo_can_update(echo_can_state_t *ec, int16_t tx, int16_t rx);
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/*! Process to high pass filter the tx signal.
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\param ec The echo canceller context.
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\param tx The transmitted auio sample.
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\return The HP filtered transmit sample, send this to your D/A.
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*/
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int16_t echo_can_hpf_tx(echo_can_state_t *ec, int16_t tx);
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#endif
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/*- End of file ------------------------------------------------------------*/
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