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sdrangel/plugins/channelrx/demoddatv/leansdr/viterbi.h

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#ifndef LEANSDR_VITERBI_H
#define LEANSDR_VITERBI_H
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
// This is a generic implementation of Viterbi with explicit
// representation of the trellis. There is special support for
// convolutional coding, but the code can handle other schemes.
// TBD This is very inefficient. For a specific trellis all loops
// can be be unrolled.
namespace leansdr
{
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// TS is an integer type for a least NSTATES+1 states.
// NSTATES is the number of states (e.g. 2^(K-1)).
// TUS is an integer type for uncoded symbols (branch identifiers).
// NUS is the number of uncoded symbols.
// TCS is an integer type for coded symbols (branch labels).
// NCS is the number of coded symbols.
// TP is a type for representing paths.
// TPM, TBM are unsigned integer types for path/branch metrics.
// TPM is at least as wide as TBM.
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template<typename TS, int NSTATES, typename TUS, int NUS, int NCS>
struct trellis
{
static const int NOSTATE = NSTATES + 1;
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struct state
{
struct branch
{
TS pred; // Predecessor state or NOSTATE
TUS us; // Uncoded symbol
} branches[NCS]; // Incoming branches indexed by coded symbol
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} states[NSTATES];
trellis()
{
for (TS s = 0; s < NSTATES; ++s)
for (int cs = 0; cs < NCS; ++cs)
states[s].branches[cs].pred = NOSTATE;
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}
// TBD Polynomial width should be a template parameter ?
void init_convolutional(const uint16_t G[])
{
if (NCS & (NCS - 1))
{
fprintf(stderr, "leansdr::trellis::init_convolutional: NCS must be a power of 2\n");
return;
}
// Derive number of polynomials from NCS.
int nG = log2i(NCS);
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for (TS s = 0; s < NSTATES; ++s)
{
for (TUS us = 0; us < NUS; ++us)
{
// Run the convolutional encoder from state s with input us
uint64_t shiftreg = s; // TBD type
// Reverse bits
TUS us_rev = 0;
for (int b = 1; b < NUS; b *= 2)
if (us & b)
us_rev |= (NUS / 2 / b);
shiftreg |= us_rev * NSTATES;
uint32_t cs = 0; // TBD type
for (int g = 0; g < nG; ++g)
cs = (cs << 1) | parity(shiftreg & G[g]);
shiftreg /= NUS; // Shift bits for 1 uncoded symbol
// [us] at state [s] emits [cs] and leads to state [shiftreg].
typename state::branch *b = &states[shiftreg].branches[cs];
if (b->pred != NOSTATE)
{
fprintf(stderr, "leansdr::trellis::init_convolutional: Invalid convolutional code\n");
return;
}
b->pred = s;
b->us = us;
}
}
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}
void dump()
{
for (int s = 0; s < NSTATES; ++s)
{
fprintf(stderr, "State %02x:", s);
for (int cs = 0; cs < NCS; ++cs)
{
typename state::branch *b = &states[s].branches[cs];
if (b->pred == NOSTATE)
fprintf(stderr, " - ");
else
fprintf(stderr, " %02x+%x", b->pred, b->us);
}
fprintf(stderr, "\n");
}
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}
};
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// Interface that hides the templated internals.
template<typename TUS, typename TCS, typename TBM, typename TPM>
struct viterbi_dec_interface
{
virtual TUS update(TBM costs[], TPM *quality = NULL)=0;
virtual TUS update(TCS s, TBM cost, TPM *quality = NULL)=0;
virtual TUS update(int nm, TCS cs[], TBM costs[], TPM *quality = NULL)=0;
};
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template<typename TS, int NSTATES, typename TUS, int NUS, typename TCS, int NCS, typename TBM, typename TPM, typename TP>
struct viterbi_dec: viterbi_dec_interface<TUS, TCS, TBM, TPM>
{
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trellis<TS, NSTATES, TUS, NUS, NCS> *trell;
struct state
{
TPM cost; // Metric of best path leading to this state
TP path; // Best path leading to this state
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};
typedef state statebank[NSTATES];
state statebanks[2][NSTATES];
statebank *states, *newstates; // Alternate between banks
viterbi_dec(trellis<TS, NSTATES, TUS, NUS, NCS> *_trellis) :
trell(_trellis)
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{
states = &statebanks[0];
newstates = &statebanks[1];
for (TS s = 0; s < NSTATES; ++s)
(*states)[s].cost = 0;
// Determine max value that can fit in TPM
max_tpm = (TPM) 0 - 1;
if (max_tpm < 0)
{
// TPM is signed
for (max_tpm = 0; max_tpm * 2 + 1 > max_tpm; max_tpm = max_tpm * 2 + 1)
;
}
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}
// Update with full metric
TUS update(TBM costs[NCS], TPM *quality = NULL)
{
TPM best_tpm = max_tpm, best2_tpm = max_tpm;
TS best_state = 0;
// Update all states
for (int s = 0; s < NSTATES; ++s)
{
TPM best_m = max_tpm;
typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *best_b = NULL;
// Select best branch
for (int cs = 0; cs < NCS; ++cs)
{
typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *b = &trell->states[s].branches[cs];
if (b->pred == trell->NOSTATE)
continue;
TPM m = (*states)[b->pred].cost + costs[cs];
if (m <= best_m)
{ // <= guarantees one match
best_m = m;
best_b = b;
}
}
(*newstates)[s].path = (*states)[best_b->pred].path;
(*newstates)[s].path.append(best_b->us);
(*newstates)[s].cost = best_m;
// Select best and second-best states
if (best_m < best_tpm)
{
best_state = s;
best2_tpm = best_tpm;
best_tpm = best_m;
}
else if (best_m < best2_tpm)
best2_tpm = best_m;
}
// Swap banks
{
statebank *tmp = states;
states = newstates;
newstates = tmp;
}
// Prevent overflow of path metrics
for (TS s = 0; s < NSTATES; ++s)
(*states)[s].cost -= best_tpm;
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#if 0
// Observe that the min-max range remains bounded
fprintf(stderr,"-%2d = [", best_tpm);
for ( TS s=0; s<NSTATES; ++s ) fprintf(stderr," %d", (*states)[s].cost);
fprintf(stderr," ]\n");
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#endif
// Return difference between best and second-best as quality metric.
if (quality)
*quality = best2_tpm - best_tpm;
// Return uncoded symbol of best path
return (*states)[best_state].path.read();
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}
// Update with partial metrics.
// The costs provided must be negative.
// The other symbols will be assigned a cost of 0.
TUS update(int nm, TCS cs[], TBM costs[], TPM *quality = NULL)
{
TPM best_tpm = max_tpm, best2_tpm = max_tpm;
TS best_state = 0;
// Update all states
for (int s = 0; s < NSTATES; ++s)
{
// Select best branch among those for with metrics are provided
TPM best_m = max_tpm;
typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *best_b = NULL;
for (int im = 0; im < nm; ++im)
{
typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *b = &trell->states[s].branches[cs[im]];
if (b->pred == trell->NOSTATE)
continue;
TPM m = (*states)[b->pred].cost + costs[im];
if (m <= best_m)
{ // <= guarantees one match
best_m = m;
best_b = b;
}
}
if (nm != NCS)
{
// Also scan the other branches.
// We actually rescan the branches with metrics.
// This works because costs are negative.
for (int cs = 0; cs < NCS; ++cs)
{
typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *b = &trell->states[s].branches[cs];
if (b->pred == trell->NOSTATE)
continue;
TPM m = (*states)[b->pred].cost;
if (m <= best_m)
{
best_m = m;
best_b = b;
}
}
}
(*newstates)[s].path = (*states)[best_b->pred].path;
(*newstates)[s].path.append(best_b->us);
(*newstates)[s].cost = best_m;
// Select best states
if (best_m < best_tpm)
{
best_state = s;
best2_tpm = best_tpm;
best_tpm = best_m;
}
else if (best_m < best2_tpm)
best2_tpm = best_m;
}
// Swap banks
{
statebank *tmp = states;
states = newstates;
newstates = tmp;
}
// Prevent overflow of path metrics
for (TS s = 0; s < NSTATES; ++s)
(*states)[s].cost -= best_tpm;
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#if 0
// Observe that the min-max range remains bounded
fprintf(stderr,"-%2d = [", best_tpm);
for ( TS s=0; s<NSTATES; ++s ) fprintf(stderr," %d", (*states)[s].cost);
fprintf(stderr," ]\n");
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#endif
// Return difference between best and second-best as quality metric.
if (quality)
*quality = best2_tpm - best_tpm;
// Return uncoded symbol of best path
return (*states)[best_state].path.read();
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}
// Update with single-symbol metric.
// cost must be negative.
TUS update(TCS cs, TBM cost, TPM *quality = NULL)
{
return update(1, &cs, &cost, quality);
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}
void dump()
{
fprintf(stderr, "[");
for (TS s = 0; s < NSTATES; ++s)
if (states[s].cost)
fprintf(stderr, " %02x:%d", s, states[s].cost);
fprintf(stderr, "\n");
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}
private:
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TPM max_tpm;
};
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// Paths (sequences of uncoded symbols) represented as bitstreams.
// NBITS is the number of bits per symbol.
// DEPTH is the number of symbols stored in the path.
// T is an unsigned integer type wider than NBITS*DEPTH.
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template<typename T, typename TUS, int NBITS, int DEPTH>
struct bitpath
{
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T val;
bitpath() :
val(0)
{
}
void append(TUS us)
{
val = (val << NBITS) | us;
}
TUS read()
{
return (val >> (DEPTH - 1) * NBITS) & ((1 << NBITS) - 1);
}
};
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} // namespace
#endif // LEANSDR_VITERBI_H