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403 lines
12 KiB
C++
403 lines
12 KiB
C++
///////////////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2018-2019, 2021 Edouard Griffiths, F4EXB <f4exb06@gmail.com> //
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// //
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// This file is part of LeanSDR Copyright (C) 2016-2019 <pabr@pabr.org>. //
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// //
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// This program is free software; you can redistribute it and/or modify //
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// it under the terms of the GNU General Public License as published by //
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// the Free Software Foundation as version 3 of the License, or //
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// (at your option) any later version. //
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// //
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// This program is distributed in the hope that it will be useful, //
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// but WITHOUT ANY WARRANTY; without even the implied warranty of //
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
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// GNU General Public License V3 for more details. //
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// //
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// You should have received a copy of the GNU General Public License //
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// along with this program. If not, see <http://www.gnu.org/licenses/>. //
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///////////////////////////////////////////////////////////////////////////////////////
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#ifndef LEANSDR_VITERBI_H
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#define LEANSDR_VITERBI_H
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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// This is a generic implementation of Viterbi with explicit
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// representation of the trellis. There is special support for
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// convolutional coding, but the code can handle other schemes.
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// TBD This is very inefficient. For a specific trellis all loops
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// can be be unrolled.
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namespace leansdr
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{
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// TS is an integer type for a least NSTATES+1 states.
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// NSTATES is the number of states (e.g. 2^(K-1)).
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// TUS is an integer type for uncoded symbols (branch identifiers).
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// NUS is the number of uncoded symbols.
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// TCS is an integer type for coded symbols (branch labels).
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// NCS is the number of coded symbols.
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// TP is a type for representing paths.
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// TPM, TBM are unsigned integer types for path/branch metrics.
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// TPM is at least as wide as TBM.
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template <typename TS, int NSTATES, typename TUS, int NUS, int NCS>
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struct trellis
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{
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static const int NOSTATE = NSTATES + 1;
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struct state
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{
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struct branch
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{
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TS pred; // Predecessor state or NOSTATE
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TUS us; // Uncoded symbol
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} branches[NCS]; // Incoming branches indexed by coded symbol
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} states[NSTATES];
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trellis()
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{
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for (TS s = 0; s < NSTATES; ++s)
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{
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for (int cs = 0; cs < NCS; ++cs) {
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states[s].branches[cs].pred = NOSTATE;
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}
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}
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}
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// TBD Polynomial width should be a template parameter ?
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void init_convolutional(const uint16_t G[])
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{
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if (NCS & (NCS - 1)) {
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fprintf(stderr, "NCS must be a power of 2\n");
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}
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// Derive number of polynomials from NCS.
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int nG = log2i(NCS);
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for (TS s = 0; s < NSTATES; ++s)
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{
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for (TUS us = 0; us < NUS; ++us)
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{
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// Run the convolutional encoder from state s with input us
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uint64_t shiftreg = s; // TBD type
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// Reverse bits
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TUS us_rev = 0;
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for (int b = 1; b < NUS; b *= 2)
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{
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if (us & b) {
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us_rev |= (NUS / 2 / b);
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}
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}
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shiftreg |= us_rev * NSTATES;
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uint32_t cs = 0; // TBD type
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for (int g = 0; g < nG; ++g) {
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cs = (cs << 1) | parity(shiftreg & G[g]);
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}
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shiftreg /= NUS; // Shift bits for 1 uncoded symbol
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// [us] at state [s] emits [cs] and leads to state [shiftreg].
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typename state::branch *b = &states[shiftreg].branches[cs];
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if (b->pred != NOSTATE) {
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fprintf(stderr, "Invalid convolutional code\n");
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}
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b->pred = s;
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b->us = us;
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}
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}
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}
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void dump()
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{
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for (int s = 0; s < NSTATES; ++s)
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{
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fprintf(stderr, "State %02x:", s);
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for (int cs = 0; cs < NCS; ++cs)
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{
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typename state::branch *b = &states[s].branches[cs];
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if (b->pred == NOSTATE) {
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fprintf(stderr, " - ");
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} else {
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fprintf(stderr, " %02x+%x", b->pred, b->us);
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}
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}
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fprintf(stderr, "\n");
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}
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}
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};
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// Interface that hides the templated internals.
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template <typename TUS,
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typename TCS,
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typename TBM,
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typename TPM>
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struct viterbi_dec_interface
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{
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virtual ~viterbi_dec_interface() {}
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virtual TUS update(TBM *costs, TPM *quality = nullptr) = 0;
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virtual TUS update(TCS s, TBM cost, TPM *quality = nullptr) = 0;
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};
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template <typename TS, int NSTATES,
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typename TUS, int NUS,
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typename TCS, int NCS,
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typename TBM, typename TPM,
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typename TP>
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struct viterbi_dec : viterbi_dec_interface<TUS, TCS, TBM, TPM>
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{
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trellis<TS, NSTATES, TUS, NUS, NCS> *trell;
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struct state
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{
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TPM cost; // Metric of best path leading to this state
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TP path; // Best path leading to this state
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};
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typedef state statebank[NSTATES];
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state statebanks[2][NSTATES];
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statebank *states, *newstates; // Alternate between banks
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viterbi_dec(trellis<TS, NSTATES, TUS, NUS, NCS> *_trellis) : trell(_trellis)
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{
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states = &statebanks[0];
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newstates = &statebanks[1];
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for (TS s = 0; s < NSTATES; ++s) {
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(*states)[s].cost = 0;
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}
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// Determine max value that can fit in TPM
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max_tpm = (TPM)0 - 1;
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if (max_tpm < 0)
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{
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// TPM is signed
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for (max_tpm = 0; max_tpm * 2 + 1 > max_tpm; max_tpm = max_tpm * 2 + 1);
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}
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}
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// Update with full metric
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TUS update(TBM costs[NCS], TPM *quality = nullptr)
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{
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TPM best_tpm = max_tpm, best2_tpm = max_tpm;
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TS best_state = 0;
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// Update all states
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for (int s = 0; s < NSTATES; ++s)
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{
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TPM best_m = max_tpm;
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typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *best_b = nullptr;
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// Select best branch
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for (int cs = 0; cs < NCS; ++cs)
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{
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typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *b =
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&trell->states[s].branches[cs];
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if (b->pred == trell->NOSTATE) {
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continue;
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}
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TPM m = (*states)[b->pred].cost + costs[cs];
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if (m <= best_m)
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{ // <= guarantees one match
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best_m = m;
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best_b = b;
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}
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}
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(*newstates)[s].path = (*states)[best_b->pred].path;
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(*newstates)[s].path.append(best_b->us);
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(*newstates)[s].cost = best_m;
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// Select best and second-best states
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if (best_m < best_tpm)
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{
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best_state = s;
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best2_tpm = best_tpm;
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best_tpm = best_m;
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}
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else if (best_m < best2_tpm)
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{
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best2_tpm = best_m;
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}
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}
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// Swap banks
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{
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statebank *tmp = states;
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states = newstates;
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newstates = tmp;
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}
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// Prevent overflow of path metrics
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for (TS s = 0; s < NSTATES; ++s) {
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(*states)[s].cost -= best_tpm;
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}
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#if 0
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// Observe that the min-max range remains bounded
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fprintf(stderr,"-%2d = [", best_tpm);
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for ( TS s=0; s<NSTATES; ++s ) fprintf(stderr," %d", (*states)[s].cost);
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fprintf(stderr," ]\n");
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#endif
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// Return difference between best and second-best as quality metric.
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if (quality) {
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*quality = best2_tpm - best_tpm;
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}
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// Return uncoded symbol of best path
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return (*states)[best_state].path.read();
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}
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// Update with partial metrics.
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// The costs provided must be negative.
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// The other symbols will be assigned a cost of 0.
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TUS update(int nm, TCS cs[], TBM costs[], TPM *quality = nullptr)
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{
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TPM best_tpm = max_tpm, best2_tpm = max_tpm;
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TS best_state = 0;
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// Update all states
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for (int s = 0; s < NSTATES; ++s)
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{
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// Select best branch among those for with metrics are provided
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TPM best_m = max_tpm;
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typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *best_b = nullptr;
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for (int im = 0; im < nm; ++im)
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{
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typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *b =
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&trell->states[s].branches[cs[im]];
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if (b->pred == trell->NOSTATE) {
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continue;
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}
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TPM m = (*states)[b->pred].cost + costs[im];
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if (m <= best_m)
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{ // <= guarantees one match
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best_m = m;
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best_b = b;
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}
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}
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if (nm != NCS)
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{
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// Also scan the other branches.
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// We actually rescan the branches with metrics.
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// This works because costs are negative.
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for (int cs = 0; cs < NCS; ++cs)
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{
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typename trellis<TS, NSTATES, TUS, NUS, NCS>::state::branch *b =
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&trell->states[s].branches[cs];
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if (b->pred == trell->NOSTATE) {
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continue;
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}
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TPM m = (*states)[b->pred].cost;
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if (m <= best_m)
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{
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best_m = m;
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best_b = b;
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}
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}
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}
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(*newstates)[s].path = (*states)[best_b->pred].path;
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(*newstates)[s].path.append(best_b->us);
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(*newstates)[s].cost = best_m;
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// Select best states
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if (best_m < best_tpm)
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{
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best_state = s;
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best2_tpm = best_tpm;
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best_tpm = best_m;
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}
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else if (best_m < best2_tpm)
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{
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best2_tpm = best_m;
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}
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}
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// Swap banks
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{
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statebank *tmp = states;
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states = newstates;
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newstates = tmp;
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}
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// Prevent overflow of path metrics
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for (TS s = 0; s < NSTATES; ++s) {
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(*states)[s].cost -= best_tpm;
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}
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#if 0
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// Observe that the min-max range remains bounded
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fprintf(stderr,"-%2d = [", best_tpm);
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for ( TS s=0; s<NSTATES; ++s ) fprintf(stderr," %d", (*states)[s].cost);
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fprintf(stderr," ]\n");
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#endif
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// Return difference between best and second-best as quality metric.
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if (quality) {
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*quality = best2_tpm - best_tpm;
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}
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// Return uncoded symbol of best path
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return (*states)[best_state].path.read();
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}
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// Update with single-symbol metric.
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// cost must be negative.
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TUS update(TCS cs, TBM cost, TPM *quality = nullptr) {
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return update(1, &cs, &cost, quality);
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}
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void dump()
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{
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fprintf(stderr, "[");
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for (TS s = 0; s < NSTATES; ++s)
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{
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if (states[s].cost) {
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fprintf(stderr, " %02x:%d", s, states[s].cost);
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}
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}
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fprintf(stderr, "\n");
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}
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private:
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TPM max_tpm;
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};
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// Paths (sequences of uncoded symbols) represented as bitstreams.
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// NBITS is the number of bits per symbol.
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// DEPTH is the number of symbols stored in the path.
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// T is an unsigned integer type wider than NBITS*DEPTH.
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template <typename T, typename TUS, int NBITS, int DEPTH>
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struct bitpath
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{
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T val;
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bitpath() : val(0) {}
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void append(TUS us) { val = (val << NBITS) | us; }
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TUS read() { return (val >> (DEPTH - 1) * NBITS) & ((1 << NBITS) - 1); }
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};
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} // namespace leansdr
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#endif // LEANSDR_VITERBI_H
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