FreeCalypso > hg > gsm-codec-lib
view libtwamr/r_fft.c @ 434:ba5031723ab6
implement amrefr-tseq-enc test program
author | Mychaela Falconia <falcon@freecalypso.org> |
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date | Wed, 08 May 2024 02:17:08 +0000 |
parents | 810ac4b99025 |
children |
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/* ***************************************************************************** * * GSM AMR-NB speech codec R98 Version 7.6.0 December 12, 2001 * R99 Version 3.3.0 * REL-4 Version 4.1.0 * ***************************************************************************** * * File : r_fft.c * Purpose : Fast Fourier Transform (FFT) algorithm * ***************************************************************************** */ /***************************************************************** * * This is an implementation of decimation-in-time FFT algorithm for * real sequences. The techniques used here can be found in several * books, e.g., i) Proakis and Manolakis, "Digital Signal Processing", * 2nd Edition, Chapter 9, and ii) W.H. Press et. al., "Numerical * Recipes in C", 2nd Ediiton, Chapter 12. * * Input - There is one input to this function: * * 1) An integer pointer to the input data array * * Output - There is no return value. * The input data are replaced with transformed data. If the * input is a real time domain sequence, it is replaced with * the complex FFT for positive frequencies. The FFT value * for DC and the foldover frequency are combined to form the * first complex number in the array. The remaining complex * numbers correspond to increasing frequencies. If the input * is a complex frequency domain sequence arranged as above, * it is replaced with the corresponding time domain sequence. * * Notes: * * 1) This function is designed to be a part of a VAD * algorithm that requires 128-point FFT of real * sequences. This is achieved here through a 64-point * complex FFT. Consequently, the FFT size information is * not transmitted explicitly. However, some flexibility * is provided in the function to change the size of the * FFT by specifying the size information through "define" * statements. * * 2) The values of the complex sinusoids used in the FFT * algorithm are stored in a ROM table. * * 3) In the c_fft function, the FFT values are divided by * 2 after each stage of computation thus dividing the * final FFT values by 64. This is somewhat different * from the usual definition of FFT where the factor 1/N, * i.e., 1/64, used for the IFFT and not the FFT. No factor * is used in the r_fft function. * *****************************************************************/ #include "tw_amr.h" #include "namespace.h" #include "typedef.h" #include "cnst.h" #include "basic_op.h" #include "oper_32b.h" #include "no_count.h" #include "vad2.h" #define SIZE 128 #define SIZE_BY_TWO 64 #define NUM_STAGE 6 #define TRUE 1 #define FALSE 0 static const Word16 phs_tbl[] = { 32767, 0, 32729, -1608, 32610, -3212, 32413, -4808, 32138, -6393, 31786, -7962, 31357, -9512, 30853, -11039, 30274, -12540, 29622, -14010, 28899, -15447, 28106, -16846, 27246, -18205, 26320, -19520, 25330, -20788, 24279, -22006, 23170, -23170, 22006, -24279, 20788, -25330, 19520, -26320, 18205, -27246, 16846, -28106, 15447, -28899, 14010, -29622, 12540, -30274, 11039, -30853, 9512, -31357, 7962, -31786, 6393, -32138, 4808, -32413, 3212, -32610, 1608, -32729, 0, -32768, -1608, -32729, -3212, -32610, -4808, -32413, -6393, -32138, -7962, -31786, -9512, -31357, -11039, -30853, -12540, -30274, -14010, -29622, -15447, -28899, -16846, -28106, -18205, -27246, -19520, -26320, -20788, -25330, -22006, -24279, -23170, -23170, -24279, -22006, -25330, -20788, -26320, -19520, -27246, -18205, -28106, -16846, -28899, -15447, -29622, -14010, -30274, -12540, -30853, -11039, -31357, -9512, -31786, -7962, -32138, -6393, -32413, -4808, -32610, -3212, -32729, -1608 }; static const Word16 ii_table[] = {SIZE / 2, SIZE / 4, SIZE / 8, SIZE / 16, SIZE / 32, SIZE / 64}; /* FFT function for complex sequences */ /* * The decimation-in-time complex FFT is implemented below. * The input complex numbers are presented as real part followed by * imaginary part for each sample. The counters are therefore * incremented by two to access the complex valued samples. */ static void c_fft(Word16 * farray_ptr) { Word16 i, j, k, ii, jj, kk, ji, kj, ii2; Word32 ftmp, ftmp_real, ftmp_imag; Word16 tmp, tmp1, tmp2; /* Rearrange the input array in bit reversed order */ for (i = 0, j = 0; i < SIZE - 2; i = i + 2) { test(); if (sub(j, i) > 0) { ftmp = *(farray_ptr + i); move16(); *(farray_ptr + i) = *(farray_ptr + j); move16(); *(farray_ptr + j) = ftmp; move16(); ftmp = *(farray_ptr + i + 1); move16(); *(farray_ptr + i + 1) = *(farray_ptr + j + 1); move16(); *(farray_ptr + j + 1) = ftmp; move16(); } k = SIZE_BY_TWO; move16(); test(); while (sub(j, k) >= 0) { j = sub(j, k); k = shr(k, 1); } j = add(j, k); } /* The FFT part */ for (i = 0; i < NUM_STAGE; i++) { /* i is stage counter */ jj = shl(2, i); /* FFT size */ kk = shl(jj, 1); /* 2 * FFT size */ ii = ii_table[i]; /* 2 * number of FFT's */ move16(); ii2 = shl(ii, 1); ji = 0; /* ji is phase table index */ move16(); for (j = 0; j < jj; j = j + 2) { /* j is sample counter */ for (k = j; k < SIZE; k = k + kk) { /* k is butterfly top */ kj = add(k, jj); /* kj is butterfly bottom */ /* Butterfly computations */ ftmp_real = L_mult(*(farray_ptr + kj), phs_tbl[ji]); ftmp_real = L_msu(ftmp_real, *(farray_ptr + kj + 1), phs_tbl[ji + 1]); ftmp_imag = L_mult(*(farray_ptr + kj + 1), phs_tbl[ji]); ftmp_imag = L_mac(ftmp_imag, *(farray_ptr + kj), phs_tbl[ji + 1]); tmp1 = round(ftmp_real); tmp2 = round(ftmp_imag); tmp = sub(*(farray_ptr + k), tmp1); *(farray_ptr + kj) = shr(tmp, 1); move16(); tmp = sub(*(farray_ptr + k + 1), tmp2); *(farray_ptr + kj + 1) = shr(tmp, 1); move16(); tmp = add(*(farray_ptr + k), tmp1); *(farray_ptr + k) = shr(tmp, 1); move16(); tmp = add(*(farray_ptr + k + 1), tmp2); *(farray_ptr + k + 1) = shr(tmp, 1); move16(); } ji = add(ji, ii2); } } } /* end of c_fft () */ void r_fft(Word16 * farray_ptr) { Word16 ftmp1_real, ftmp1_imag, ftmp2_real, ftmp2_imag; Word32 Lftmp1_real, Lftmp1_imag; Word16 i, j; Word32 Ltmp1; /* Perform the complex FFT */ c_fft(farray_ptr); /* First, handle the DC and foldover frequencies */ ftmp1_real = *farray_ptr; move16(); ftmp2_real = *(farray_ptr + 1); move16(); *farray_ptr = add(ftmp1_real, ftmp2_real); move16(); *(farray_ptr + 1) = sub(ftmp1_real, ftmp2_real); move16(); /* Now, handle the remaining positive frequencies */ for (i = 2, j = SIZE - i; i <= SIZE_BY_TWO; i = i + 2, j = SIZE - i) { ftmp1_real = add(*(farray_ptr + i), *(farray_ptr + j)); ftmp1_imag = sub(*(farray_ptr + i + 1), *(farray_ptr + j + 1)); ftmp2_real = add(*(farray_ptr + i + 1), *(farray_ptr + j + 1)); ftmp2_imag = sub(*(farray_ptr + j), *(farray_ptr + i)); Lftmp1_real = L_deposit_h(ftmp1_real); Lftmp1_imag = L_deposit_h(ftmp1_imag); Ltmp1 = L_mac(Lftmp1_real, ftmp2_real, phs_tbl[i]); Ltmp1 = L_msu(Ltmp1, ftmp2_imag, phs_tbl[i + 1]); *(farray_ptr + i) = round(L_shr(Ltmp1, 1)); move16(); Ltmp1 = L_mac(Lftmp1_imag, ftmp2_imag, phs_tbl[i]); Ltmp1 = L_mac(Ltmp1, ftmp2_real, phs_tbl[i + 1]); *(farray_ptr + i + 1) = round(L_shr(Ltmp1, 1)); move16(); Ltmp1 = L_mac(Lftmp1_real, ftmp2_real, phs_tbl[j]); Ltmp1 = L_mac(Ltmp1, ftmp2_imag, phs_tbl[j + 1]); *(farray_ptr + j) = round(L_shr(Ltmp1, 1)); move16(); Ltmp1 = L_negate(Lftmp1_imag); Ltmp1 = L_msu(Ltmp1, ftmp2_imag, phs_tbl[j]); Ltmp1 = L_mac(Ltmp1, ftmp2_real, phs_tbl[j + 1]); *(farray_ptr + j + 1) = round(L_shr(Ltmp1, 1)); move16(); } } /* end r_fft () */