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      1 /* K=9 r=1/3 Viterbi decoder for PowerPC G4/G5 Altivec vector instructions
      2  * 8-bit offset-binary soft decision samples
      3  * Copyright Aug 2006, Phil Karn, KA9Q
      4  * May be used under the terms of the GNU Lesser General Public License (LGPL)
      5  */
      6 #include <stdio.h>
      7 #include <stdlib.h>
      8 #include <memory.h>
      9 #include <limits.h>
     10 #include "fec.h"
     11 
     12 typedef union { unsigned char c[2][16]; vector unsigned char v[2]; } decision_t;
     13 typedef union { unsigned short s[256]; vector unsigned short v[32]; } metric_t;
     14 
     15 static union branchtab39 { unsigned short s[128]; vector unsigned short v[16];} Branchtab39[3];
     16 static int Init = 0;
     17 
     18 /* State info for instance of Viterbi decoder */
     19 struct v39 {
     20   metric_t metrics1; /* path metric buffer 1 */
     21   metric_t metrics2; /* path metric buffer 2 */
     22   void *dp;          /* Pointer to current decision */
     23   metric_t *old_metrics,*new_metrics; /* Pointers to path metrics, swapped on every bit */
     24   void *decisions;   /* Beginning of decisions for block */
     25 };
     26 
     27 /* Initialize Viterbi decoder for start of new frame */
     28 int init_viterbi39_av(void *p,int starting_state){
     29   struct v39 *vp = p;
     30   int i;
     31 
     32   for(i=0;i<32;i++)
     33     vp->metrics1.v[i] = (vector unsigned short)(1000);
     34 
     35   vp->old_metrics = &vp->metrics1;
     36   vp->new_metrics = &vp->metrics2;
     37   vp->dp = vp->decisions;
     38   vp->old_metrics->s[starting_state & 255] = 0; /* Bias known start state */
     39   return 0;
     40 }
     41 
     42 void set_viterbi39_polynomial_av(int polys[3]){
     43   int state;
     44 
     45   for(state=0;state < 128;state++){
     46     Branchtab39[0].s[state] = (polys[0] < 0) ^ parity((2*state) & abs(polys[0])) ? 255 : 0;
     47     Branchtab39[1].s[state] = (polys[1] < 0) ^ parity((2*state) & abs(polys[1])) ? 255 : 0;
     48     Branchtab39[2].s[state] = (polys[2] < 0) ^ parity((2*state) & abs(polys[2])) ? 255 : 0;
     49   }
     50   Init++;
     51 }
     52 
     53 /* Create a new instance of a Viterbi decoder */
     54 void *create_viterbi39_av(int len){
     55   struct v39 *vp;
     56 
     57   if(!Init){
     58     int polys[3] = { V39POLYA, V39POLYB, V39POLYC };
     59 
     60     set_viterbi39_polynomial_av(polys);
     61   }
     62   vp = (struct v39 *)malloc(sizeof(struct v39));
     63   vp->decisions = malloc(sizeof(decision_t)*(len+8));
     64   init_viterbi39_av(vp,0);
     65   return vp;
     66 }
     67 
     68 /* Viterbi chainback */
     69 int chainback_viterbi39_av(
     70       void *p,
     71       unsigned char *data, /* Decoded output data */
     72       unsigned int nbits, /* Number of data bits */
     73       unsigned int endstate){ /* Terminal encoder state */
     74   struct v39 *vp = p;
     75   decision_t *d = (decision_t *)vp->decisions;
     76   int path_metric;
     77 
     78   /* Make room beyond the end of the encoder register so we can
     79    * accumulate a full byte of decoded data
     80    */
     81   endstate %= 256;
     82 
     83   path_metric = vp->old_metrics->s[endstate];
     84 
     85   /* The store into data[] only needs to be done every 8 bits.
     86    * But this avoids a conditional branch, and the writes will
     87    * combine in the cache anyway
     88    */
     89   d += 8; /* Look past tail */
     90   while(nbits-- != 0){
     91     int k;
     92 
     93     k = (d[nbits].c[endstate >> 7][endstate & 15] & (0x80 >> ((endstate>>4)&7)) ) ? 1 : 0;
     94     endstate = (k << 7) | (endstate >> 1);
     95     data[nbits>>3] = endstate;
     96   }
     97   return path_metric;
     98 }
     99 
    100 /* Delete instance of a Viterbi decoder */
    101 void delete_viterbi39_av(void *p){
    102   struct v39 *vp = p;
    103 
    104   if(vp != NULL){
    105     free(vp->decisions);
    106     free(vp);
    107   }
    108 }
    109 
    110 int update_viterbi39_blk_av(void *p,unsigned char *syms,int nbits){
    111   struct v39 *vp = p;
    112   decision_t *d = (decision_t *)vp->dp;
    113   int path_metric = 0;
    114   vector unsigned char decisions = (vector unsigned char)(0);
    115 
    116   while(nbits--){
    117     vector unsigned short symv,sym0v,sym1v,sym2v;
    118     vector unsigned char s;
    119     void *tmp;
    120     int i;
    121 
    122     /* Splat the 0th symbol across sym0v, the 1st symbol across sym1v, etc */
    123     s = (vector unsigned char)vec_perm(vec_ld(0,syms),vec_ld(5,syms),vec_lvsl(0,syms));
    124 
    125     symv = (vector unsigned short)vec_mergeh((vector unsigned char)(0),s);    /* Unsigned byte->word unpack */
    126     sym0v = vec_splat(symv,0);
    127     sym1v = vec_splat(symv,1);
    128     sym2v = vec_splat(symv,2);
    129     syms += 3;
    130 
    131     for(i=0;i<16;i++){
    132       vector bool short decision0,decision1;
    133       vector unsigned short metric,m_metric,m0,m1,m2,m3,survivor0,survivor1;
    134 
    135       /* Form branch metrics
    136        * Because Branchtab takes on values 0 and 255, and the values of sym?v are offset binary in the range 0-255,
    137        * the XOR operations constitute conditional negation.
    138        * the metrics are in the range 0-765
    139        */
    140       m0 = vec_add(vec_xor(Branchtab39[0].v[i],sym0v),vec_xor(Branchtab39[1].v[i],sym1v));
    141       m1 = vec_xor(Branchtab39[2].v[i],sym2v);
    142       metric = vec_add(m0,m1);
    143       m_metric = vec_sub((vector unsigned short)(765),metric);
    144 
    145       /* Add branch metrics to path metrics */
    146       m0 = vec_adds(vp->old_metrics->v[i],metric);
    147       m3 = vec_adds(vp->old_metrics->v[16+i],metric);
    148       m1 = vec_adds(vp->old_metrics->v[16+i],m_metric);
    149       m2 = vec_adds(vp->old_metrics->v[i],m_metric);
    150 
    151       /* Compare and select */
    152       decision0 = vec_cmpgt(m0,m1);
    153       decision1 = vec_cmpgt(m2,m3);
    154       survivor0 = vec_min(m0,m1);
    155       survivor1 = vec_min(m2,m3);
    156 
    157       /* Store decisions and survivors.
    158        * To save space without SSE2's handy PMOVMSKB instruction, we pack and store them in
    159        * a funny interleaved fashion that we undo in the chainback function.
    160        */
    161       decisions = vec_add(decisions,decisions); /* Shift each byte 1 bit to the left */
    162 
    163       /* Booleans are either 0xff or 0x00. Subtracting 0x00 leaves the lsb zero; subtracting
    164        * 0xff is equivalent to adding 1, which sets the lsb.
    165        */
    166       decisions = vec_sub(decisions,(vector unsigned char)vec_pack(vec_mergeh(decision0,decision1),vec_mergel(decision0,decision1)));
    167 
    168       vp->new_metrics->v[2*i] = vec_mergeh(survivor0,survivor1);
    169       vp->new_metrics->v[2*i+1] = vec_mergel(survivor0,survivor1);
    170 
    171       if((i % 8) == 7){
    172 	/* We've accumulated a total of 128 decisions, stash and start again */
    173 	d->v[i>>3] = decisions; /* No need to clear, the new bits will replace the old */
    174       }
    175     }
    176 #if 0
    177     /* Experimentally determine metric spread
    178      * The results are fixed for a given code and input symbol size
    179      */
    180     {
    181       int i;
    182       vector unsigned short min_metric;
    183       vector unsigned short max_metric;
    184       union { vector unsigned short v; unsigned short s[8];} t;
    185       int minimum,maximum;
    186       static int max_spread = 0;
    187 
    188       min_metric = max_metric = vp->new_metrics->v[0];
    189       for(i=1;i<32;i++){
    190 	min_metric = vec_min(min_metric,vp->new_metrics->v[i]);
    191 	max_metric = vec_max(max_metric,vp->new_metrics->v[i]);
    192       }
    193       min_metric = vec_min(min_metric,vec_sld(min_metric,min_metric,8));
    194       max_metric = vec_max(max_metric,vec_sld(max_metric,max_metric,8));
    195       min_metric = vec_min(min_metric,vec_sld(min_metric,min_metric,4));
    196       max_metric = vec_max(max_metric,vec_sld(max_metric,max_metric,4));
    197       min_metric = vec_min(min_metric,vec_sld(min_metric,min_metric,2));
    198       max_metric = vec_max(max_metric,vec_sld(max_metric,max_metric,2));
    199 
    200       t.v = min_metric;
    201       minimum = t.s[0];
    202       t.v = max_metric;
    203       maximum = t.s[0];
    204       if(maximum-minimum > max_spread){
    205 	max_spread = maximum-minimum;
    206 	printf("metric spread = %d\n",max_spread);
    207       }
    208     }
    209 #endif
    210 
    211     /* Renormalize if necessary. This deserves some explanation.
    212      * The maximum possible spread, found by experiment, for 8 bit symbols is about 3825
    213      * So by looking at one arbitrary metric we can tell if any of them have possibly saturated.
    214      * However, this is very conservative. Large spreads occur only at very high Eb/No, where
    215      * saturating a bad path metric doesn't do much to increase its chances of being erroneously chosen as a survivor.
    216 
    217      * At more interesting (low) Eb/No ratios, the spreads are much smaller so our chances of saturating a metric
    218      * by not not normalizing when we should are extremely low. So either way, the risk to performance is small.
    219 
    220      * All this is borne out by experiment.
    221      */
    222     if(vp->new_metrics->s[0] >= USHRT_MAX-5000){
    223       vector unsigned short scale;
    224       union { vector unsigned short v; unsigned short s[8];} t;
    225 
    226       /* Find smallest metric and splat */
    227       scale = vp->new_metrics->v[0];
    228       for(i=1;i<32;i++)
    229 	scale = vec_min(scale,vp->new_metrics->v[i]);
    230 
    231       scale = vec_min(scale,vec_sld(scale,scale,8));
    232       scale = vec_min(scale,vec_sld(scale,scale,4));
    233       scale = vec_min(scale,vec_sld(scale,scale,2));
    234 
    235       /* Subtract it from all metrics
    236        * Work backwards to try to improve the cache hit ratio, assuming LRU
    237        */
    238       for(i=31;i>=0;i--)
    239 	vp->new_metrics->v[i] = vec_subs(vp->new_metrics->v[i],scale);
    240       t.v = scale;
    241       path_metric += t.s[0];
    242     }
    243     d++;
    244     /* Swap pointers to old and new metrics */
    245     tmp = vp->old_metrics;
    246     vp->old_metrics = vp->new_metrics;
    247     vp->new_metrics = tmp;
    248   }
    249   vp->dp = d;
    250   return path_metric;
    251 }
    252