Roman Khassraf | d38206c | 2015-06-07 16:26:29 +0200 | [diff] [blame] | 1 | /* |
Piotr Krysik | b9a87a1 | 2017-08-23 15:59:28 +0200 | [diff] [blame] | 2 | * Copyright 2013, 2014 Range Networks, Inc. |
| 3 | * |
| 4 | * This program is free software: you can redistribute it and/or modify |
| 5 | * it under the terms of the GNU Affero General Public License as published by |
| 6 | * the Free Software Foundation, either version 3 of the License, or |
| 7 | * (at your option) any later version. |
Roman Khassraf | d38206c | 2015-06-07 16:26:29 +0200 | [diff] [blame] | 8 | |
Piotr Krysik | b9a87a1 | 2017-08-23 15:59:28 +0200 | [diff] [blame] | 9 | * This program is distributed in the hope that it will be useful, |
| 10 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
| 11 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| 12 | * GNU Affero General Public License for more details. |
| 13 | * |
| 14 | * You should have received a copy of the GNU Affero General Public License |
| 15 | * along with this program. If not, see <http://www.gnu.org/licenses/>. |
| 16 | * |
| 17 | * This use of this software may be subject to additional restrictions. |
| 18 | * See the LEGAL file in the main directory for details. |
| 19 | */ |
Roman Khassraf | d38206c | 2015-06-07 16:26:29 +0200 | [diff] [blame] | 20 | |
Roman Khassraf | d38206c | 2015-06-07 16:26:29 +0200 | [diff] [blame] | 21 | #ifndef _AMRCODER_H_ |
| 22 | #define _AMRCODER_H_ |
| 23 | #include <stdint.h> |
| 24 | #include "BitVector.h" |
| 25 | #include "Viterbi.h" |
| 26 | |
| 27 | |
| 28 | |
| 29 | /** |
| 30 | Class to represent recursive systematic convolutional coders/decoders of rate 1/2, memory length 4. |
| 31 | */ |
| 32 | class ViterbiTCH_AFS12_2 : public ViterbiBase { |
| 33 | |
| 34 | private: |
| 35 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 36 | //@{ |
| 37 | /**@name Core values. */ |
| 38 | //@{ |
| 39 | static const unsigned mIRate = 2; ///< reciprocal of rate |
| 40 | static const unsigned mOrder = 4; ///< memory length of generators |
| 41 | //@} |
| 42 | /**@name Derived values. */ |
| 43 | //@{ |
| 44 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 45 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 46 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 47 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 48 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 49 | static const unsigned mDeferral = 6*mOrder; ///< deferral to be used |
| 50 | //@} |
| 51 | //@} |
| 52 | |
| 53 | /** Precomputed tables. */ |
| 54 | //@{ |
| 55 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 56 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 57 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 58 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 59 | //@} |
| 60 | |
| 61 | public: |
| 62 | |
| 63 | /** |
| 64 | A candidate sequence in a Viterbi decoder. |
| 65 | The 32-bit state register can support a deferral of 6 with a 4th-order coder. |
| 66 | */ |
| 67 | typedef struct candStruct { |
| 68 | uint32_t iState; ///< encoder input associated with this candidate |
| 69 | uint32_t oState; ///< encoder output associated with this candidate |
| 70 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 71 | float cost; ///< cost (metric value), float to support soft inputs |
| 72 | } vCand; |
| 73 | |
| 74 | /** Clear a structure. */ |
| 75 | void vitClear(vCand& v) |
| 76 | { |
| 77 | v.iState=0; |
| 78 | v.oState=0; |
| 79 | v.cost=0; |
| 80 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 81 | } |
| 82 | |
| 83 | |
| 84 | private: |
| 85 | |
| 86 | /**@name Survivors and candidates. */ |
| 87 | //@{ |
| 88 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 89 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 90 | //@} |
| 91 | |
| 92 | public: |
| 93 | |
| 94 | unsigned iRate() const { return mIRate; } |
| 95 | uint32_t cMask() const { return mCMask; } |
| 96 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 97 | unsigned deferral() const { return mDeferral; } |
| 98 | |
| 99 | |
| 100 | ViterbiTCH_AFS12_2(); |
| 101 | |
| 102 | /** Set all cost metrics to zero. */ |
| 103 | void initializeStates(); |
| 104 | |
| 105 | /** |
| 106 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 107 | @return reference to minimum-cost candidate. |
| 108 | */ |
| 109 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 110 | |
| 111 | private: |
| 112 | |
| 113 | /** Branch survivors into new candidates. */ |
| 114 | void branchCandidates(); |
| 115 | |
| 116 | /** Compute cost metrics for soft-inputs. */ |
| 117 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 118 | |
| 119 | /** Select survivors from the candidate set. */ |
| 120 | void pruneCandidates(); |
| 121 | |
| 122 | /** Find the minimum cost survivor. */ |
| 123 | const vCand& minCost() const; |
| 124 | |
| 125 | /** |
| 126 | Precompute the state tables. |
| 127 | @param g Generator index 0..((1/rate)-1) |
| 128 | */ |
| 129 | void computeStateTables(unsigned g); |
| 130 | |
| 131 | /** |
| 132 | Precompute the generator outputs. |
| 133 | mCoeffs must be defined first. |
| 134 | */ |
| 135 | void computeGeneratorTable(); |
| 136 | void encode(const BitVector &in, BitVector& target) const; |
| 137 | void decode(const SoftVector &in, BitVector& target); |
| 138 | }; |
| 139 | |
| 140 | |
| 141 | |
| 142 | /** |
| 143 | Class to represent recursive systematic convolutional coders/decoders of rate 1/3, memory length 4. |
| 144 | */ |
| 145 | class ViterbiTCH_AFS10_2 : public ViterbiBase { |
| 146 | |
| 147 | private: |
| 148 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 149 | //@{ |
| 150 | /**@name Core values. */ |
| 151 | //@{ |
| 152 | static const unsigned mIRate = 3; ///< reciprocal of rate |
| 153 | static const unsigned mOrder = 4; ///< memory length of generators |
| 154 | //@} |
| 155 | /**@name Derived values. */ |
| 156 | //@{ |
| 157 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 158 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 159 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 160 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 161 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 162 | static const unsigned mDeferral = 6*mOrder; ///< deferral to be used |
| 163 | //@} |
| 164 | //@} |
| 165 | |
| 166 | /** Precomputed tables. */ |
| 167 | //@{ |
| 168 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 169 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 170 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 171 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 172 | //@} |
| 173 | |
| 174 | public: |
| 175 | |
| 176 | /** |
| 177 | A candidate sequence in a Viterbi decoder. |
| 178 | The 32-bit state register can support a deferral of 6 with a 4th-order coder. |
| 179 | */ |
| 180 | typedef struct candStruct { |
| 181 | uint32_t iState; ///< encoder input associated with this candidate |
| 182 | uint32_t oState; ///< encoder output associated with this candidate |
| 183 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 184 | float cost; ///< cost (metric value), float to support soft inputs |
| 185 | } vCand; |
| 186 | |
| 187 | /** Clear a structure. */ |
| 188 | void vitClear(vCand& v) |
| 189 | { |
| 190 | v.iState=0; |
| 191 | v.oState=0; |
| 192 | v.cost=0; |
| 193 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 194 | } |
| 195 | |
| 196 | |
| 197 | private: |
| 198 | |
| 199 | /**@name Survivors and candidates. */ |
| 200 | //@{ |
| 201 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 202 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 203 | //@} |
| 204 | |
| 205 | public: |
| 206 | |
| 207 | unsigned iRate() const { return mIRate; } |
| 208 | uint32_t cMask() const { return mCMask; } |
| 209 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 210 | unsigned deferral() const { return mDeferral; } |
| 211 | |
| 212 | |
| 213 | ViterbiTCH_AFS10_2(); |
| 214 | |
| 215 | /** Set all cost metrics to zero. */ |
| 216 | void initializeStates(); |
| 217 | |
| 218 | /** |
| 219 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 220 | @return reference to minimum-cost candidate. |
| 221 | */ |
| 222 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 223 | |
| 224 | private: |
| 225 | |
| 226 | /** Branch survivors into new candidates. */ |
| 227 | void branchCandidates(); |
| 228 | |
| 229 | /** Compute cost metrics for soft-inputs. */ |
| 230 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 231 | |
| 232 | /** Select survivors from the candidate set. */ |
| 233 | void pruneCandidates(); |
| 234 | |
| 235 | /** Find the minimum cost survivor. */ |
| 236 | const vCand& minCost() const; |
| 237 | |
| 238 | /** |
| 239 | Precompute the state tables. |
| 240 | @param g Generator index 0..((1/rate)-1) |
| 241 | */ |
| 242 | void computeStateTables(unsigned g); |
| 243 | |
| 244 | /** |
| 245 | Precompute the generator outputs. |
| 246 | mCoeffs must be defined first. |
| 247 | */ |
| 248 | void computeGeneratorTable(); |
| 249 | void encode(const BitVector &in, BitVector& target) const; |
| 250 | void decode(const SoftVector &in, BitVector& target); |
| 251 | |
| 252 | }; |
| 253 | |
| 254 | |
| 255 | |
| 256 | /** |
| 257 | Class to represent recursive systematic convolutional coders/decoders of rate 1/3, memory length 6. |
| 258 | */ |
| 259 | class ViterbiTCH_AFS7_95 : public ViterbiBase { |
| 260 | |
| 261 | private: |
| 262 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 263 | //@{ |
| 264 | /**@name Core values. */ |
| 265 | //@{ |
| 266 | static const unsigned mIRate = 3; ///< reciprocal of rate |
| 267 | static const unsigned mOrder = 6; ///< memory length of generators |
| 268 | //@} |
| 269 | /**@name Derived values. */ |
| 270 | //@{ |
| 271 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 272 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 273 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 274 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 275 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 276 | static const unsigned mDeferral = 5*mOrder; ///< deferral to be used |
| 277 | //@} |
| 278 | //@} |
| 279 | |
| 280 | /** Precomputed tables. */ |
| 281 | //@{ |
| 282 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 283 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 284 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 285 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 286 | //@} |
| 287 | |
| 288 | public: |
| 289 | |
| 290 | /** |
| 291 | A candidate sequence in a Viterbi decoder. |
| 292 | The 32-bit state register can support a deferral of 5*order with a 6th-order coder. |
| 293 | */ |
| 294 | typedef struct candStruct { |
| 295 | uint32_t iState; ///< encoder input associated with this candidate |
| 296 | uint32_t oState; ///< encoder output associated with this candidate |
| 297 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 298 | float cost; ///< cost (metric value), float to support soft inputs |
| 299 | } vCand; |
| 300 | |
| 301 | /** Clear a structure. */ |
| 302 | void vitClear(vCand& v) |
| 303 | { |
| 304 | v.iState=0; |
| 305 | v.oState=0; |
| 306 | v.cost=0; |
| 307 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 308 | } |
| 309 | |
| 310 | |
| 311 | private: |
| 312 | |
| 313 | /**@name Survivors and candidates. */ |
| 314 | //@{ |
| 315 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 316 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 317 | //@} |
| 318 | |
| 319 | public: |
| 320 | |
| 321 | unsigned iRate() const { return mIRate; } |
| 322 | uint32_t cMask() const { return mCMask; } |
| 323 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 324 | unsigned deferral() const { return mDeferral; } |
| 325 | |
| 326 | |
| 327 | ViterbiTCH_AFS7_95(); |
| 328 | |
| 329 | /** Set all cost metrics to zero. */ |
| 330 | void initializeStates(); |
| 331 | |
| 332 | /** |
| 333 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 334 | @return reference to minimum-cost candidate. |
| 335 | */ |
| 336 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 337 | |
| 338 | private: |
| 339 | |
| 340 | /** Branch survivors into new candidates. */ |
| 341 | void branchCandidates(); |
| 342 | |
| 343 | /** Compute cost metrics for soft-inputs. */ |
| 344 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 345 | |
| 346 | /** Select survivors from the candidate set. */ |
| 347 | void pruneCandidates(); |
| 348 | |
| 349 | /** Find the minimum cost survivor. */ |
| 350 | const vCand& minCost() const; |
| 351 | |
| 352 | /** |
| 353 | Precompute the state tables. |
| 354 | @param g Generator index 0..((1/rate)-1) |
| 355 | */ |
| 356 | void computeStateTables(unsigned g); |
| 357 | |
| 358 | /** |
| 359 | Precompute the generator outputs. |
| 360 | mCoeffs must be defined first. |
| 361 | */ |
| 362 | void computeGeneratorTable(); |
| 363 | void encode(const BitVector &in, BitVector& target) const; |
| 364 | void decode(const SoftVector &in, BitVector& target); |
| 365 | |
| 366 | }; |
| 367 | |
| 368 | |
| 369 | |
| 370 | /** |
| 371 | Class to represent recursive systematic convolutional coders/decoders of rate 1/3, memory length 4. |
| 372 | */ |
| 373 | class ViterbiTCH_AFS7_4 : public ViterbiBase { |
| 374 | |
| 375 | private: |
| 376 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 377 | //@{ |
| 378 | /**@name Core values. */ |
| 379 | //@{ |
| 380 | static const unsigned mIRate = 3; ///< reciprocal of rate |
| 381 | static const unsigned mOrder = 4; ///< memory length of generators |
| 382 | //@} |
| 383 | /**@name Derived values. */ |
| 384 | //@{ |
| 385 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 386 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 387 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 388 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 389 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 390 | static const unsigned mDeferral = 6*mOrder; ///< deferral to be used |
| 391 | //@} |
| 392 | //@} |
| 393 | |
| 394 | /** Precomputed tables. */ |
| 395 | //@{ |
| 396 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 397 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 398 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 399 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 400 | //@} |
| 401 | |
| 402 | public: |
| 403 | |
| 404 | /** |
| 405 | A candidate sequence in a Viterbi decoder. |
| 406 | The 32-bit state register can support a deferral of 6 with a 4th-order coder. |
| 407 | */ |
| 408 | typedef struct candStruct { |
| 409 | uint32_t iState; ///< encoder input associated with this candidate |
| 410 | uint32_t oState; ///< encoder output associated with this candidate |
| 411 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 412 | float cost; ///< cost (metric value), float to support soft inputs |
| 413 | } vCand; |
| 414 | |
| 415 | /** Clear a structure. */ |
| 416 | void vitClear(vCand& v) |
| 417 | { |
| 418 | v.iState=0; |
| 419 | v.oState=0; |
| 420 | v.cost=0; |
| 421 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 422 | } |
| 423 | |
| 424 | |
| 425 | private: |
| 426 | |
| 427 | /**@name Survivors and candidates. */ |
| 428 | //@{ |
| 429 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 430 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 431 | //@} |
| 432 | |
| 433 | public: |
| 434 | |
| 435 | unsigned iRate() const { return mIRate; } |
| 436 | uint32_t cMask() const { return mCMask; } |
| 437 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 438 | unsigned deferral() const { return mDeferral; } |
| 439 | |
| 440 | |
| 441 | ViterbiTCH_AFS7_4(); |
| 442 | |
| 443 | /** Set all cost metrics to zero. */ |
| 444 | void initializeStates(); |
| 445 | |
| 446 | /** |
| 447 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 448 | @return reference to minimum-cost candidate. |
| 449 | */ |
| 450 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 451 | |
| 452 | private: |
| 453 | |
| 454 | /** Branch survivors into new candidates. */ |
| 455 | void branchCandidates(); |
| 456 | |
| 457 | /** Compute cost metrics for soft-inputs. */ |
| 458 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 459 | |
| 460 | /** Select survivors from the candidate set. */ |
| 461 | void pruneCandidates(); |
| 462 | |
| 463 | /** Find the minimum cost survivor. */ |
| 464 | const vCand& minCost() const; |
| 465 | |
| 466 | /** |
| 467 | Precompute the state tables. |
| 468 | @param g Generator index 0..((1/rate)-1) |
| 469 | */ |
| 470 | void computeStateTables(unsigned g); |
| 471 | |
| 472 | /** |
| 473 | Precompute the generator outputs. |
| 474 | mCoeffs must be defined first. |
| 475 | */ |
| 476 | void computeGeneratorTable(); |
| 477 | void encode(const BitVector &in, BitVector& target) const; |
| 478 | void decode(const SoftVector &in, BitVector& target); |
| 479 | |
| 480 | }; |
| 481 | |
| 482 | |
| 483 | |
| 484 | /** |
| 485 | Class to represent recursive systematic convolutional coders/decoders of rate 1/4, memory length 4. |
| 486 | */ |
| 487 | class ViterbiTCH_AFS6_7 : public ViterbiBase { |
| 488 | |
| 489 | private: |
| 490 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 491 | //@{ |
| 492 | /**@name Core values. */ |
| 493 | //@{ |
| 494 | static const unsigned mIRate = 4; ///< reciprocal of rate |
| 495 | static const unsigned mOrder = 4; ///< memory length of generators |
| 496 | //@} |
| 497 | /**@name Derived values. */ |
| 498 | //@{ |
| 499 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 500 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 501 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 502 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 503 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 504 | static const unsigned mDeferral = 6*mOrder; ///< deferral to be used |
| 505 | //@} |
| 506 | //@} |
| 507 | |
| 508 | /** Precomputed tables. */ |
| 509 | //@{ |
| 510 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 511 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 512 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 513 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 514 | //@} |
| 515 | |
| 516 | public: |
| 517 | |
| 518 | /** |
| 519 | A candidate sequence in a Viterbi decoder. |
| 520 | The 32-bit state register can support a deferral of 6 with a 4th-order coder. |
| 521 | */ |
| 522 | typedef struct candStruct { |
| 523 | uint32_t iState; ///< encoder input associated with this candidate |
| 524 | uint32_t oState; ///< encoder output associated with this candidate |
| 525 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 526 | float cost; ///< cost (metric value), float to support soft inputs |
| 527 | } vCand; |
| 528 | |
| 529 | /** Clear a structure. */ |
| 530 | void vitClear(vCand& v) |
| 531 | { |
| 532 | v.iState=0; |
| 533 | v.oState=0; |
| 534 | v.cost=0; |
| 535 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 536 | } |
| 537 | |
| 538 | |
| 539 | private: |
| 540 | |
| 541 | /**@name Survivors and candidates. */ |
| 542 | //@{ |
| 543 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 544 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 545 | //@} |
| 546 | |
| 547 | public: |
| 548 | |
| 549 | unsigned iRate() const { return mIRate; } |
| 550 | uint32_t cMask() const { return mCMask; } |
| 551 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 552 | unsigned deferral() const { return mDeferral; } |
| 553 | |
| 554 | |
| 555 | ViterbiTCH_AFS6_7(); |
| 556 | |
| 557 | /** Set all cost metrics to zero. */ |
| 558 | void initializeStates(); |
| 559 | |
| 560 | /** |
| 561 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 562 | @return reference to minimum-cost candidate. |
| 563 | */ |
| 564 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 565 | |
| 566 | private: |
| 567 | |
| 568 | /** Branch survivors into new candidates. */ |
| 569 | void branchCandidates(); |
| 570 | |
| 571 | /** Compute cost metrics for soft-inputs. */ |
| 572 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 573 | |
| 574 | /** Select survivors from the candidate set. */ |
| 575 | void pruneCandidates(); |
| 576 | |
| 577 | /** Find the minimum cost survivor. */ |
| 578 | const vCand& minCost() const; |
| 579 | |
| 580 | /** |
| 581 | Precompute the state tables. |
| 582 | @param g Generator index 0..((1/rate)-1) |
| 583 | */ |
| 584 | void computeStateTables(unsigned g); |
| 585 | |
| 586 | /** |
| 587 | Precompute the generator outputs. |
| 588 | mCoeffs must be defined first. |
| 589 | */ |
| 590 | void computeGeneratorTable(); |
| 591 | void encode(const BitVector &in, BitVector& target) const; |
| 592 | void decode(const SoftVector &in, BitVector& target); |
| 593 | |
| 594 | }; |
| 595 | |
| 596 | |
| 597 | |
| 598 | /** |
| 599 | Class to represent recursive systematic convolutional coders/decoders of rate 1/4, memory length 6. |
| 600 | */ |
| 601 | class ViterbiTCH_AFS5_9 : public ViterbiBase { |
| 602 | |
| 603 | private: |
| 604 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 605 | //@{ |
| 606 | /**@name Core values. */ |
| 607 | //@{ |
| 608 | static const unsigned mIRate = 4; ///< reciprocal of rate |
| 609 | static const unsigned mOrder = 6; ///< memory length of generators |
| 610 | //@} |
| 611 | /**@name Derived values. */ |
| 612 | //@{ |
| 613 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 614 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 615 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 616 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 617 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 618 | static const unsigned mDeferral = 5*mOrder; ///< deferral to be used |
| 619 | //@} |
| 620 | //@} |
| 621 | |
| 622 | /** Precomputed tables. */ |
| 623 | //@{ |
| 624 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 625 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 626 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 627 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 628 | //@} |
| 629 | |
| 630 | public: |
| 631 | |
| 632 | /** |
| 633 | A candidate sequence in a Viterbi decoder. |
| 634 | The 32-bit state register can support a deferral of 5*order with a 6th-order coder. |
| 635 | */ |
| 636 | typedef struct candStruct { |
| 637 | uint32_t iState; ///< encoder input associated with this candidate |
| 638 | uint32_t oState; ///< encoder output associated with this candidate |
| 639 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 640 | float cost; ///< cost (metric value), float to support soft inputs |
| 641 | } vCand; |
| 642 | |
| 643 | /** Clear a structure. */ |
| 644 | void vitClear(vCand& v) |
| 645 | { |
| 646 | v.iState=0; |
| 647 | v.oState=0; |
| 648 | v.cost=0; |
| 649 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 650 | } |
| 651 | |
| 652 | |
| 653 | private: |
| 654 | |
| 655 | /**@name Survivors and candidates. */ |
| 656 | //@{ |
| 657 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 658 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 659 | //@} |
| 660 | |
| 661 | public: |
| 662 | |
| 663 | unsigned iRate() const { return mIRate; } |
| 664 | uint32_t cMask() const { return mCMask; } |
| 665 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 666 | unsigned deferral() const { return mDeferral; } |
| 667 | |
| 668 | |
| 669 | ViterbiTCH_AFS5_9(); |
| 670 | |
| 671 | /** Set all cost metrics to zero. */ |
| 672 | void initializeStates(); |
| 673 | |
| 674 | /** |
| 675 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 676 | @return reference to minimum-cost candidate. |
| 677 | */ |
| 678 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 679 | |
| 680 | private: |
| 681 | |
| 682 | /** Branch survivors into new candidates. */ |
| 683 | void branchCandidates(); |
| 684 | |
| 685 | /** Compute cost metrics for soft-inputs. */ |
| 686 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 687 | |
| 688 | /** Select survivors from the candidate set. */ |
| 689 | void pruneCandidates(); |
| 690 | |
| 691 | /** Find the minimum cost survivor. */ |
| 692 | const vCand& minCost() const; |
| 693 | |
| 694 | /** |
| 695 | Precompute the state tables. |
| 696 | @param g Generator index 0..((1/rate)-1) |
| 697 | */ |
| 698 | void computeStateTables(unsigned g); |
| 699 | |
| 700 | /** |
| 701 | Precompute the generator outputs. |
| 702 | mCoeffs must be defined first. |
| 703 | */ |
| 704 | void computeGeneratorTable(); |
| 705 | void encode(const BitVector &in, BitVector& target) const; |
| 706 | void decode(const SoftVector &in, BitVector& target); |
| 707 | |
| 708 | }; |
| 709 | |
| 710 | |
| 711 | |
| 712 | /** |
| 713 | Class to represent recursive systematic convolutional coders/decoders of rate 1/5, memory length 4. |
| 714 | */ |
| 715 | class ViterbiTCH_AFS5_15 : public ViterbiBase { |
| 716 | |
| 717 | private: |
| 718 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 719 | //@{ |
| 720 | /**@name Core values. */ |
| 721 | //@{ |
| 722 | static const unsigned mIRate = 5; ///< reciprocal of rate |
| 723 | static const unsigned mOrder = 4; ///< memory length of generators |
| 724 | //@} |
| 725 | /**@name Derived values. */ |
| 726 | //@{ |
| 727 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 728 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 729 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 730 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 731 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 732 | static const unsigned mDeferral = 6*mOrder; ///< deferral to be used |
| 733 | //@} |
| 734 | //@} |
| 735 | |
| 736 | /** Precomputed tables. */ |
| 737 | //@{ |
| 738 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 739 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 740 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 741 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 742 | //@} |
| 743 | |
| 744 | public: |
| 745 | |
| 746 | /** |
| 747 | A candidate sequence in a Viterbi decoder. |
| 748 | The 32-bit state register can support a deferral of 6 with a 4th-order coder. |
| 749 | */ |
| 750 | typedef struct candStruct { |
| 751 | uint32_t iState; ///< encoder input associated with this candidate |
| 752 | uint32_t oState; ///< encoder output associated with this candidate |
| 753 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 754 | float cost; ///< cost (metric value), float to support soft inputs |
| 755 | } vCand; |
| 756 | |
| 757 | /** Clear a structure. */ |
| 758 | void vitClear(vCand& v) |
| 759 | { |
| 760 | v.iState=0; |
| 761 | v.oState=0; |
| 762 | v.cost=0; |
| 763 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 764 | } |
| 765 | |
| 766 | |
| 767 | private: |
| 768 | |
| 769 | /**@name Survivors and candidates. */ |
| 770 | //@{ |
| 771 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 772 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 773 | //@} |
| 774 | |
| 775 | public: |
| 776 | |
| 777 | unsigned iRate() const { return mIRate; } |
| 778 | uint32_t cMask() const { return mCMask; } |
| 779 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 780 | unsigned deferral() const { return mDeferral; } |
| 781 | |
| 782 | |
| 783 | ViterbiTCH_AFS5_15(); |
| 784 | |
| 785 | /** Set all cost metrics to zero. */ |
| 786 | void initializeStates(); |
| 787 | |
| 788 | /** |
| 789 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 790 | @return reference to minimum-cost candidate. |
| 791 | */ |
| 792 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 793 | |
| 794 | private: |
| 795 | |
| 796 | /** Branch survivors into new candidates. */ |
| 797 | void branchCandidates(); |
| 798 | |
| 799 | /** Compute cost metrics for soft-inputs. */ |
| 800 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 801 | |
| 802 | /** Select survivors from the candidate set. */ |
| 803 | void pruneCandidates(); |
| 804 | |
| 805 | /** Find the minimum cost survivor. */ |
| 806 | const vCand& minCost() const; |
| 807 | |
| 808 | /** |
| 809 | Precompute the state tables. |
| 810 | @param g Generator index 0..((1/rate)-1) |
| 811 | */ |
| 812 | void computeStateTables(unsigned g); |
| 813 | |
| 814 | /** |
| 815 | Precompute the generator outputs. |
| 816 | mCoeffs must be defined first. |
| 817 | */ |
| 818 | void computeGeneratorTable(); |
| 819 | void encode(const BitVector &in, BitVector& target) const; |
| 820 | void decode(const SoftVector &in, BitVector& target); |
| 821 | |
| 822 | }; |
| 823 | |
| 824 | |
| 825 | |
| 826 | /** |
| 827 | Class to represent recursive systematic convolutional coders/decoders of rate 1/5, memory length 6. |
| 828 | */ |
| 829 | class ViterbiTCH_AFS4_75 : public ViterbiBase { |
| 830 | |
| 831 | private: |
| 832 | /**name Lots of precomputed elements so the compiler can optimize like hell. */ |
| 833 | //@{ |
| 834 | /**@name Core values. */ |
| 835 | //@{ |
| 836 | static const unsigned mIRate = 5; ///< reciprocal of rate |
| 837 | static const unsigned mOrder = 6; ///< memory length of generators |
| 838 | //@} |
| 839 | /**@name Derived values. */ |
| 840 | //@{ |
| 841 | static const unsigned mIStates = 0x01 << mOrder; ///< number of states, number of survivors |
| 842 | static const uint32_t mSMask = mIStates-1; ///< survivor mask |
| 843 | static const uint32_t mCMask = (mSMask<<1) | 0x01; ///< candidate mask |
| 844 | static const uint32_t mOMask = (0x01<<mIRate)-1; ///< ouput mask, all iRate low bits set |
| 845 | static const unsigned mNumCands = mIStates*2; ///< number of candidates to generate during branching |
| 846 | static const unsigned mDeferral = 5*mOrder; ///< deferral to be used |
| 847 | //@} |
| 848 | //@} |
| 849 | |
| 850 | /** Precomputed tables. */ |
| 851 | //@{ |
| 852 | uint32_t mCoeffs[mIRate]; ///< output polynomial for each generator |
| 853 | uint32_t mCoeffsFB[mIRate]; ///< feedback polynomial for each generator |
| 854 | uint32_t mStateTable[mIRate][2*mIStates]; ///< precomputed generator output tables |
| 855 | uint32_t mGeneratorTable[2*mIStates]; ///< precomputed coder output table |
| 856 | //@} |
| 857 | |
| 858 | public: |
| 859 | |
| 860 | /** |
| 861 | A candidate sequence in a Viterbi decoder. |
| 862 | The 32-bit state register can support a deferral of 5*order with a 6th-order coder. |
| 863 | */ |
| 864 | typedef struct candStruct { |
| 865 | uint32_t iState; ///< encoder input associated with this candidate |
| 866 | uint32_t oState; ///< encoder output associated with this candidate |
| 867 | char rState[mIRate];///< real states of encoders associated with this candidate |
| 868 | float cost; ///< cost (metric value), float to support soft inputs |
| 869 | } vCand; |
| 870 | |
| 871 | /** Clear a structure. */ |
| 872 | void vitClear(vCand& v) |
| 873 | { |
| 874 | v.iState=0; |
| 875 | v.oState=0; |
| 876 | v.cost=0; |
| 877 | for (unsigned i = 0; i < mIRate; i++) v.rState[i] = 0; |
| 878 | } |
| 879 | |
| 880 | |
| 881 | private: |
| 882 | |
| 883 | /**@name Survivors and candidates. */ |
| 884 | //@{ |
| 885 | vCand mSurvivors[mIStates]; ///< current survivor pool |
| 886 | vCand mCandidates[2*mIStates]; ///< current candidate pool |
| 887 | //@} |
| 888 | |
| 889 | public: |
| 890 | |
| 891 | unsigned iRate() const { return mIRate; } |
| 892 | uint32_t cMask() const { return mCMask; } |
| 893 | uint32_t stateTable(unsigned g, unsigned i) const { return mStateTable[g][i]; } |
| 894 | unsigned deferral() const { return mDeferral; } |
| 895 | |
| 896 | |
| 897 | ViterbiTCH_AFS4_75(); |
| 898 | |
| 899 | /** Set all cost metrics to zero. */ |
| 900 | void initializeStates(); |
| 901 | |
| 902 | /** |
| 903 | Full cycle of the Viterbi algorithm: branch, metrics, prune, select. |
| 904 | @return reference to minimum-cost candidate. |
| 905 | */ |
| 906 | const vCand& step(uint32_t inSample, const float *probs, const float *iprobs); |
| 907 | |
| 908 | private: |
| 909 | |
| 910 | /** Branch survivors into new candidates. */ |
| 911 | void branchCandidates(); |
| 912 | |
| 913 | /** Compute cost metrics for soft-inputs. */ |
| 914 | void getSoftCostMetrics(uint32_t inSample, const float *probs, const float *iprobs); |
| 915 | |
| 916 | /** Select survivors from the candidate set. */ |
| 917 | void pruneCandidates(); |
| 918 | |
| 919 | /** Find the minimum cost survivor. */ |
| 920 | const vCand& minCost() const; |
| 921 | |
| 922 | /** |
| 923 | Precompute the state tables. |
| 924 | @param g Generator index 0..((1/rate)-1) |
| 925 | */ |
| 926 | void computeStateTables(unsigned g); |
| 927 | |
| 928 | /** |
| 929 | Precompute the generator outputs. |
| 930 | mCoeffs must be defined first. |
| 931 | */ |
| 932 | void computeGeneratorTable(); |
| 933 | void encode(const BitVector &in, BitVector& target) const; |
| 934 | void decode(const SoftVector &in, BitVector& target); |
| 935 | |
| 936 | }; |
| 937 | |
| 938 | |
| 939 | |
| 940 | |
| 941 | #endif |