osd-contiki/core/lib/ifft.c

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/*
* Copyright (c) 2008, Swedish Institute of Computer Science
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* 3. Neither the name of the Institute nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE INSTITUTE AND CONTRIBUTORS ``AS IS'' AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE INSTITUTE OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
* OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
* OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
* SUCH DAMAGE.
*
* -----------------------------------------------------------------
* ifft - Integer FFT (fast fourier transform) library
*
*
* Author : Joakim Eriksson
* Created : 2008-03-27
* Updated : $Date: 2008/07/03 23:40:12 $
* $Revision: 1.3 $
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*/
#include "lib/ifft.h"
/*---------------------------------------------------------------------------*/
/* constant table of sin values in 8/7 bits resolution */
/* NOTE: symmetry can be used to reduce this to 1/2 or 1/4 the size */
#define SIN_TAB_LEN 120
#define RESOLUTION 7
#define ABS(x) (x < 0 ? -x : x)
static const int8_t SIN_TAB[] = {
0,6,13,20,26,33,39,45,52,58,63,69,75,80,
85,90,95,99,103,107,110,114,116,119,121,
123,125,126,127,127,127,127,127,126,125,
123,121,119,116,114,110,107,103,99,95,90,
85,80,75,69,63,58,52,45,39,33,26,20,13,6,
0,-6,-13,-20,-26,-33,-39,-45,-52,-58,-63,
-69,-75,-80,-85,-90,-95,-99,-103,-107,-110,
-114,-116,-119,-121,-123,-125,-126,-127,-127,
-127,-127,-127,-126,-125,-123,-121,-119,-116,
-114,-110,-107,-103,-99,-95,-90,-85,-80,-75,
-69,-63,-58,-52,-45,-39,-33,-26,-20,-13,-6
};
static uint16_t bitrev(uint16_t j, uint16_t nu)
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{
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uint16_t k;
k = 0;
for (; nu > 0; nu--) {
k = (k << 1) + (j & 1);
j = j >> 1;
}
return k;
}
/* Non interpolating sine... which takes an angle of 0 - 999 */
static int16_t sinI(uint16_t angleMilli)
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{
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uint16_t pos;
pos = (uint16_t) ((SIN_TAB_LEN * (uint32_t) angleMilli) / 1000);
return SIN_TAB[pos % SIN_TAB_LEN];
}
static int16_t cosI(uint16_t angleMilli)
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{
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return sinI(angleMilli + 250);
}
static uint16_t ilog2(uint16_t val)
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{
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uint16_t log;
log = 0;
val = val >> 1; /* The 20 = 1 => log = 0 => val = 0 */
while (val > 0) {
val = val >> 1;
log++;
}
return log;
}
/* ifft(xre[], n) - integer (fixpoint) version of Fast Fourier Transform
An integer version of FFT that takes in-samples in an int16_t array
and does an fft on n samples in the array.
The result of the FFT is stored in the same array as the samples
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was stored. Them imaginary part of the result is stored in xim which
needs to be of the same size as xre (e.g. n ints).
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Note: This fft is designed to be used with 8 bit values (e.g. not
16 bit values). The reason for the int16_t array is for keeping some
'room' for the calculations. It is also designed for doing fairly small
FFT:s since to large sample arrays might cause it to overflow during
calculations.
*/
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void
ifft(int16_t xre[], int16_t xim[], uint16_t n)
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{
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uint16_t nu;
uint16_t n2;
uint16_t nu1;
int p, k, l, i;
int32_t c, s, tr, ti;
nu = ilog2(n);
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nu1 = nu - 1;
n2 = n / 2;
for (i = 0; i < n; i++)
xim[i] = 0;
for (l = 1; l <= nu; l++) {
for (k = 0; k < n; k += n2) {
for (i = 1; i <= n2; i++) {
p = bitrev(k >> nu1, nu);
c = cosI((1000 * p) / n);
s = sinI((1000 * p) / n);
tr = ((xre[k + n2] * c + xim[k + n2] * s) >> RESOLUTION);
ti = ((xim[k + n2] * c - xre[k + n2] * s) >> RESOLUTION);
xre[k + n2] = xre[k] - tr;
xim[k + n2] = xim[k] - ti;
xre[k] += tr;
xim[k] += ti;
k++;
}
}
nu1--;
n2 = n2 / 2;
}
for (k = 0; k < n; k++) {
p = bitrev(k, nu);
if (p > k) {
n2 = xre[k];
xre[k] = xre[p];
xre[p] = n2;
n2 = xim[k];
xim[k] = xim[p];
xim[p] = n2;
}
}
/* This is a fast but not 100% correct magnitude calculation */
/* Should be sqrt(xre[i]^2 + xim[i]^2) and normalized with div. by n */
for (i = 0, n2 = n / 2; i < n2; i++) {
xre[i] = (ABS(xre[i]) + ABS(xim[i]));
}
}