staging: echo: move to drivers/misc/

The code is clean, there are users of it, so it doesn't belong in
staging anymore, move it to drivers/misc/.

Cc: Steve Underwood <steveu@coppice.org>
Cc: David Rowe <david@rowetel.com>
Signed-off-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org>

1 files changed, 0 insertions, 187 deletions

diff --git a/drivers/staging/echo/echo.h b/drivers/staging/echo/echo.h
deleted file mode 100644
index 9b08c63e6369..000000000000
--- a/drivers/staging/echo/echo.h
+++ /dev/null
@@ -1,187 +0,0 @@
-/*
- * SpanDSP - a series of DSP components for telephony
- *
- * echo.c - A line echo canceller.  This code is being developed
- *          against and partially complies with G168.
- *
- * Written by Steve Underwood <steveu@coppice.org>
- *         and David Rowe <david_at_rowetel_dot_com>
- *
- * Copyright (C) 2001 Steve Underwood and 2007 David Rowe
- *
- * All rights reserved.
- *
- * This program is free software; you can redistribute it and/or modify
- * it under the terms of the GNU General Public License version 2, as
- * published by the Free Software Foundation.
- *
- * This program is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with this program; if not, write to the Free Software
- * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
- */
-
-#ifndef __ECHO_H
-#define __ECHO_H
-
-/*
-Line echo cancellation for voice
-
-What does it do?
-
-This module aims to provide G.168-2002 compliant echo cancellation, to remove
-electrical echoes (e.g. from 2-4 wire hybrids) from voice calls.
-
-How does it work?
-
-The heart of the echo cancellor is FIR filter. This is adapted to match the
-echo impulse response of the telephone line. It must be long enough to
-adequately cover the duration of that impulse response. The signal transmitted
-to the telephone line is passed through the FIR filter. Once the FIR is
-properly adapted, the resulting output is an estimate of the echo signal
-received from the line. This is subtracted from the received signal. The result
-is an estimate of the signal which originated at the far end of the line, free
-from echos of our own transmitted signal.
-
-The least mean squares (LMS) algorithm is attributed to Widrow and Hoff, and
-was introduced in 1960. It is the commonest form of filter adaption used in
-things like modem line equalisers and line echo cancellers. There it works very
-well.  However, it only works well for signals of constant amplitude. It works
-very poorly for things like speech echo cancellation, where the signal level
-varies widely.  This is quite easy to fix. If the signal level is normalised -
-similar to applying AGC - LMS can work as well for a signal of varying
-amplitude as it does for a modem signal. This normalised least mean squares
-(NLMS) algorithm is the commonest one used for speech echo cancellation. Many
-other algorithms exist - e.g. RLS (essentially the same as Kalman filtering),
-FAP, etc. Some perform significantly better than NLMS.  However, factors such
-as computational complexity and patents favour the use of NLMS.
-
-A simple refinement to NLMS can improve its performance with speech. NLMS tends
-to adapt best to the strongest parts of a signal. If the signal is white noise,
-the NLMS algorithm works very well. However, speech has more low frequency than
-high frequency content. Pre-whitening (i.e. filtering the signal to flatten its
-spectrum) the echo signal improves the adapt rate for speech, and ensures the
-final residual signal is not heavily biased towards high frequencies. A very
-low complexity filter is adequate for this, so pre-whitening adds little to the
-compute requirements of the echo canceller.
-
-An FIR filter adapted using pre-whitened NLMS performs well, provided certain
-conditions are met:
-
-    - The transmitted signal has poor self-correlation.
-    - There is no signal being generated within the environment being
-      cancelled.
-
-The difficulty is that neither of these can be guaranteed.
-
-If the adaption is performed while transmitting noise (or something fairly
-noise like, such as voice) the adaption works very well. If the adaption is
-performed while transmitting something highly correlative (typically narrow
-band energy such as signalling tones or DTMF), the adaption can go seriously
-wrong. The reason is there is only one solution for the adaption on a near
-random signal - the impulse response of the line. For a repetitive signal,
-there are any number of solutions which converge the adaption, and nothing
-guides the adaption to choose the generalised one. Allowing an untrained
-canceller to converge on this kind of narrowband energy probably a good thing,
-since at least it cancels the tones. Allowing a well converged canceller to
-continue converging on such energy is just a way to ruin its generalised
-adaption. A narrowband detector is needed, so adapation can be suspended at
-appropriate times.
-
-The adaption process is based on trying to eliminate the received signal. When
-there is any signal from within the environment being cancelled it may upset
-the adaption process. Similarly, if the signal we are transmitting is small,
-noise may dominate and disturb the adaption process. If we can ensure that the
-adaption is only performed when we are transmitting a significant signal level,
-and the environment is not, things will be OK. Clearly, it is easy to tell when
-we are sending a significant signal. Telling, if the environment is generating
-a significant signal, and doing it with sufficient speed that the adaption will
-not have diverged too much more we stop it, is a little harder.
-
-The key problem in detecting when the environment is sourcing significant
-energy is that we must do this very quickly. Given a reasonably long sample of
-the received signal, there are a number of strategies which may be used to
-assess whether that signal contains a strong far end component. However, by the
-time that assessment is complete the far end signal will have already caused
-major mis-convergence in the adaption process. An assessment algorithm is
-needed which produces a fairly accurate result from a very short burst of far
-end energy.
-
-How do I use it?
-
-The echo cancellor processes both the transmit and receive streams sample by
-sample. The processing function is not declared inline. Unfortunately,
-cancellation requires many operations per sample, so the call overhead is only
-a minor burden.
-*/
-
-#include "fir.h"
-#include "oslec.h"
-
-/*
-    G.168 echo canceller descriptor. This defines the working state for a line
-    echo canceller.
-*/
-struct oslec_state {
-	int16_t tx;
-	int16_t rx;
-	int16_t clean;
-	int16_t clean_nlp;
-
-	int nonupdate_dwell;
-	int curr_pos;
-	int taps;
-	int log2taps;
-	int adaption_mode;
-
-	int cond_met;
-	int32_t pstates;
-	int16_t adapt;
-	int32_t factor;
-	int16_t shift;
-
-	/* Average levels and averaging filter states */
-	int ltxacc;
-	int lrxacc;
-	int lcleanacc;
-	int lclean_bgacc;
-	int ltx;
-	int lrx;
-	int lclean;
-	int lclean_bg;
-	int lbgn;
-	int lbgn_acc;
-	int lbgn_upper;
-	int lbgn_upper_acc;
-
-	/* foreground and background filter states */
-	struct fir16_state_t fir_state;
-	struct fir16_state_t fir_state_bg;
-	int16_t *fir_taps16[2];
-
-	/* DC blocking filter states */
-	int tx_1;
-	int tx_2;
-	int rx_1;
-	int rx_2;
-
-	/* optional High Pass Filter states */
-	int32_t xvtx[5];
-	int32_t yvtx[5];
-	int32_t xvrx[5];
-	int32_t yvrx[5];
-
-	/* Parameters for the optional Hoth noise generator */
-	int cng_level;
-	int cng_rndnum;
-	int cng_filter;
-
-	/* snapshot sample of coeffs used for development */
-	int16_t *snapshot;
-};
-
-#endif /* __ECHO_H */