1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
|
/* File: Somap.c
Description: Soft demapper (M-ary to binary LLR conversion)
The calling syntax is:
[output] = Somap( input, [demod_type], [extrinsic_info] )
Where:
output = Length N*log2(M) stream of LLR values
input = M by N matrix of symbol likelihoods
demod_type = The type of max_star algorithm that is used
= 0 For linear approximation to log-MAP (DEFAULT)
= 1 For max-log-MAP algorithm (i.e. max*(x,y) = max(x,y) )
= 2 For Constant-log-MAP algorithm
= 3 For log-MAP, correction factor from small nonuniform table and interpolation
= 4 For log-MAP, correction factor uses C function calls
extrinsic_info = 1 by N*log2(M) vector of extrinsic info (defaults to all-zero)
Copyright (C) 2005-2006, Matthew C. Valenti
Last updated on Jan. 11, 2006
Function Somap is part of the Iterative Solutions
Coded Modulation Library. The Iterative Solutions Coded Modulation
Library is free software; you can redistribute it and/or modify it
under the terms of the GNU Lesser General Public License as published
by the Free Software Foundation; either version 2.1 of the License,
or (at your option) any later version.
This library 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
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
*/
#include <math.h>
#include <mex.h>
#include <Matrix.h>
#include <stdlib.h>
#include "./include/maxstar.h"
/* Input Arguments
prhs[0] is input
prhs[1] is demod_type
prhs[2] is ex_info */
/* Output Arguments
plhs[0] is output */
/* main function that interfaces with MATLAB */
void mexFunction(
int nlhs,
mxArray *plhs[],
int nrhs,
const mxArray *prhs[] )
{
double *input;
double *llr_in;
double *output_p;
int demod_type = 0;
int M, m, DataLength;
int i, j, k, n, mask;
int NumberSymbols;
float metric;
float *den, *num;
int temp_int;
float *llr;
int Number_LLR_bits;
/* put the different max_star functions into array so easy to call */
float (*max_star[])(float, float) =
{
max_star0, max_star1, max_star2, max_star3, max_star4
};
/* Check for proper number of arguments */
if (nrhs == 0) {
mexErrMsgTxt("Usage: [output] = Somap( input, [demod_type], [extrinsic_info] )");
}
if (nrhs > 0 ) {
/* first (and only required) input is M-ary symbols for conversion */
input = mxGetPr(prhs[0]);
}
if (nrhs > 1) {
/* second (optional) input is the demodulator type */
demod_type = (int) *mxGetPr(prhs[1]);
if ( (demod_type < 0)||(demod_type > 4) )
mexErrMsgTxt("demod_type must be be 0 through 4");
}
/* initialize the input data */
NumberSymbols = mxGetN(prhs[0]);
M = mxGetM(prhs[0]);
/* determine number of bits per symbol */
m = 0;
temp_int = M;
while (temp_int>1) {
temp_int = temp_int/2;
m++;
}
/* printf( "%d bits per symbol\n", m ); */
if (temp_int < 1)
mexErrMsgTxt("Number of symbols M must be a power of 2");
DataLength = m*NumberSymbols; /* total number of bits */
/* allocate memory */
den = (float*)calloc( m, sizeof(float) );
num = (float*)calloc( m, sizeof(float) );
llr = (float*)calloc( DataLength, sizeof(float) ); /* llr input defaults to all-zeros */
if (nrhs > 2) {
/* third (optional) input is the llr
if not long enough, assume that end is all-zeros */
Number_LLR_bits = mxGetN(prhs[2]);
if ( Number_LLR_bits > DataLength )
mexErrMsgTxt("Too many a prior LLR inputs");
llr_in = mxGetPr(prhs[2]);
for (k=0;k<Number_LLR_bits;k++) {
llr[k] = (float) llr_in[k];
}
}
/* the bit-wise LLRs */
plhs[0] = mxCreateDoubleMatrix(1, DataLength, mxREAL );
output_p = mxGetPr(plhs[0]);
for (n=0;n<NumberSymbols;n++) { /* loop over symbols */
for (k=0;k<m;k++) {
/* initialize */
num[k] = -1000000;
den[k] = -1000000;
}
for (i=0;i<M;i++) {
metric = input[n*M+i]; /* channel metric for this symbol */
mask = 1 << (m - 1);
for (j=0;j<m;j++) { /* incorporate extrinsic info */
if (mask&i) {
metric += llr[n*m+j];
}
mask = mask >> 1;
}
mask = 1 << (m - 1);
for (k=0;k<m;k++) { /* loop over bits */
if (mask&i) {
/* this bit is a one */
num[k] = ( *max_star[demod_type] )( num[k], metric - llr[n*m+k] );
} else {
/* this bit is a zero */
den[k] = ( *max_star[demod_type] )( den[k], metric );
}
mask = mask >> 1;
}
}
for (k=0;k<m;k++) {
output_p[m*n+k] = num[k] - den[k];
}
}
/* free memory */
free( den );
free( num );
free( llr );
return;
}
|
