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Diffstat (limited to 'src/lib')
| -rw-r--r-- | src/lib/viterbi_detector.h | 552 |
1 files changed, 552 insertions, 0 deletions
diff --git a/src/lib/viterbi_detector.h b/src/lib/viterbi_detector.h new file mode 100644 index 0000000..2a2fede --- /dev/null +++ b/src/lib/viterbi_detector.h @@ -0,0 +1,552 @@ +/*************************************************************************** + * Copyright (C) 2008 by Piotr Krysik * + * pkrysik@stud.elka.pw.edu.pl * + * * + * This program is free software; you can redistribute it and/or modify * + * it under the terms of the GNU General Public License as published by * + * the Free Software Foundation; either version 2 of the License, or * + * (at your option) any later version. * + * * + * This program 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 General Public License for more details. * + * * + * You should have received a copy of the GNU General Public License * + * along with this program; if not, write to the * + * Free Software Foundation, Inc., * + * 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. * + ***************************************************************************/ + +/* +** viterbi_detector: +** This part does the detection of received sequnece. +** Employed algorithm is viterbi Maximum Likehood Sequence Estimation. +** At this moment it gives hard decisions on the output, but +** it was designed with soft decisions in mind. +** +** SYNTAX: void viterbi_detector( +** const gr_complex * input, +** unsigned int samples_num, +** gr_complex * rhh, +** unsigned int start_state, +** const unsigned int * stop_states, +** unsigned int stops_num, +** float * output) +** +** INPUT: input: Complex received signal afted matched filtering. +** samples_num: Number of samples in the input table. +** rhh: The autocorrelation of the estimated channel +** impulse response. +** start_state: Number of the start point. In GSM each burst +** starts with sequence of three bits (0,0,0) which +** indicates start point of the algorithm. +** stop_states: Table with numbers of possible stop states. +** stops_num: Number of possible stop states +** +** +** OUTPUT: output: Differentially decoded hard output of the algorithm: +** -1 for logical "0" and 1 for logical "1" +** +** SUB_FUNC: none +** +** TEST(S): Tested with real world normal burst. +*/ + +#include <gnuradio/gr_complex.h> +#include <gsm_constants.h> +#define PATHS_NUM (1 << (CHAN_IMP_RESP_LENGTH-1)) + +void viterbi_detector(const gr_complex * input, unsigned int samples_num, gr_complex * rhh, unsigned int start_state, const unsigned int * stop_states, unsigned int stops_num, float * output) +{ + float increment[8]; + float path_metrics1[16]; + float path_metrics2[16]; + float * new_path_metrics; + float * old_path_metrics; + float * tmp; + float trans_table[BURST_SIZE][16]; + float pm_candidate1, pm_candidate2; + bool real_imag; + float input_symbol_real, input_symbol_imag; + unsigned int i, sample_nr; + +/* +* Setup first path metrics, so only state pointed by start_state is possible. +* Start_state metric is equal to zero, the rest is written with some very low value, +* which makes them practically impossible to occur. +*/ + for(i=0; i<PATHS_NUM; i++){ + path_metrics1[i]=(-10e30); + } + path_metrics1[start_state]=0; + +/* +* Compute Increment - a table of values which does not change for subsequent input samples. +* Increment is table of reference levels for computation of branch metrics: +* branch metric = (+/-)received_sample (+/-) reference_level +*/ + increment[0] = -rhh[1].imag() -rhh[2].real() -rhh[3].imag() +rhh[4].real(); + increment[1] = rhh[1].imag() -rhh[2].real() -rhh[3].imag() +rhh[4].real(); + increment[2] = -rhh[1].imag() +rhh[2].real() -rhh[3].imag() +rhh[4].real(); + increment[3] = rhh[1].imag() +rhh[2].real() -rhh[3].imag() +rhh[4].real(); + increment[4] = -rhh[1].imag() -rhh[2].real() +rhh[3].imag() +rhh[4].real(); + increment[5] = rhh[1].imag() -rhh[2].real() +rhh[3].imag() +rhh[4].real(); + increment[6] = -rhh[1].imag() +rhh[2].real() +rhh[3].imag() +rhh[4].real(); + increment[7] = rhh[1].imag() +rhh[2].real() +rhh[3].imag() +rhh[4].real(); + + +/* +* Computation of path metrics and decisions (Add-Compare-Select). +* It's composed of two parts: one for odd input samples (imaginary numbers) +* and one for even samples (real numbers). +* Each part is composed of independent (parallelisable) statements like +* this one: +* pm_candidate1 = old_path_metrics[0] - input_symbol_real - increment[7]; +* pm_candidate2 = old_path_metrics[8] - input_symbol_real + increment[0]; +* if(pm_candidate1 > pm_candidate2){ +* new_path_metrics[0] = pm_candidate1; +* trans_table[sample_nr][0] = -1.0; +* } +* else{ +* new_path_metrics[0] = pm_candidate2; +* trans_table[sample_nr][0] = 1.0; +* } +* This is very good point for optimisations (SIMD or OpenMP) as it's most time +* consuming part of this function. +*/ + sample_nr=0; + old_path_metrics=path_metrics1; + new_path_metrics=path_metrics2; + while(sample_nr<samples_num){ + //Processing imag states + real_imag=1; + input_symbol_imag = input[sample_nr].imag(); + + pm_candidate1 = old_path_metrics[0] + input_symbol_imag - increment[2]; + pm_candidate2 = old_path_metrics[8] + input_symbol_imag + increment[5]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[0] = pm_candidate1; + trans_table[sample_nr][0] = -1.0; + } + else{ + new_path_metrics[0] = pm_candidate2; + trans_table[sample_nr][0] = 1.0; + } + + pm_candidate1 = old_path_metrics[0] - input_symbol_imag + increment[2]; + pm_candidate2 = old_path_metrics[8] - input_symbol_imag - increment[5]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[1] = pm_candidate1; + trans_table[sample_nr][1] = -1.0; + } + else{ + new_path_metrics[1] = pm_candidate2; + trans_table[sample_nr][1] = 1.0; + } + + pm_candidate1 = old_path_metrics[1] + input_symbol_imag - increment[3]; + pm_candidate2 = old_path_metrics[9] + input_symbol_imag + increment[4]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[2] = pm_candidate1; + trans_table[sample_nr][2] = -1.0; + } + else{ + new_path_metrics[2] = pm_candidate2; + trans_table[sample_nr][2] = 1.0; + } + + pm_candidate1 = old_path_metrics[1] - input_symbol_imag + increment[3]; + pm_candidate2 = old_path_metrics[9] - input_symbol_imag - increment[4]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[3] = pm_candidate1; + trans_table[sample_nr][3] = -1.0; + } + else{ + new_path_metrics[3] = pm_candidate2; + trans_table[sample_nr][3] = 1.0; + } + + pm_candidate1 = old_path_metrics[2] + input_symbol_imag - increment[0]; + pm_candidate2 = old_path_metrics[10] + input_symbol_imag + increment[7]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[4] = pm_candidate1; + trans_table[sample_nr][4] = -1.0; + } + else{ + new_path_metrics[4] = pm_candidate2; + trans_table[sample_nr][4] = 1.0; + } + + pm_candidate1 = old_path_metrics[2] - input_symbol_imag + increment[0]; + pm_candidate2 = old_path_metrics[10] - input_symbol_imag - increment[7]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[5] = pm_candidate1; + trans_table[sample_nr][5] = -1.0; + } + else{ + new_path_metrics[5] = pm_candidate2; + trans_table[sample_nr][5] = 1.0; + } + + pm_candidate1 = old_path_metrics[3] + input_symbol_imag - increment[1]; + pm_candidate2 = old_path_metrics[11] + input_symbol_imag + increment[6]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[6] = pm_candidate1; + trans_table[sample_nr][6] = -1.0; + } + else{ + new_path_metrics[6] = pm_candidate2; + trans_table[sample_nr][6] = 1.0; + } + + pm_candidate1 = old_path_metrics[3] - input_symbol_imag + increment[1]; + pm_candidate2 = old_path_metrics[11] - input_symbol_imag - increment[6]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[7] = pm_candidate1; + trans_table[sample_nr][7] = -1.0; + } + else{ + new_path_metrics[7] = pm_candidate2; + trans_table[sample_nr][7] = 1.0; + } + + pm_candidate1 = old_path_metrics[4] + input_symbol_imag - increment[6]; + pm_candidate2 = old_path_metrics[12] + input_symbol_imag + increment[1]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[8] = pm_candidate1; + trans_table[sample_nr][8] = -1.0; + } + else{ + new_path_metrics[8] = pm_candidate2; + trans_table[sample_nr][8] = 1.0; + } + + pm_candidate1 = old_path_metrics[4] - input_symbol_imag + increment[6]; + pm_candidate2 = old_path_metrics[12] - input_symbol_imag - increment[1]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[9] = pm_candidate1; + trans_table[sample_nr][9] = -1.0; + } + else{ + new_path_metrics[9] = pm_candidate2; + trans_table[sample_nr][9] = 1.0; + } + + pm_candidate1 = old_path_metrics[5] + input_symbol_imag - increment[7]; + pm_candidate2 = old_path_metrics[13] + input_symbol_imag + increment[0]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[10] = pm_candidate1; + trans_table[sample_nr][10] = -1.0; + } + else{ + new_path_metrics[10] = pm_candidate2; + trans_table[sample_nr][10] = 1.0; + } + + pm_candidate1 = old_path_metrics[5] - input_symbol_imag + increment[7]; + pm_candidate2 = old_path_metrics[13] - input_symbol_imag - increment[0]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[11] = pm_candidate1; + trans_table[sample_nr][11] = -1.0; + } + else{ + new_path_metrics[11] = pm_candidate2; + trans_table[sample_nr][11] = 1.0; + } + + pm_candidate1 = old_path_metrics[6] + input_symbol_imag - increment[4]; + pm_candidate2 = old_path_metrics[14] + input_symbol_imag + increment[3]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[12] = pm_candidate1; + trans_table[sample_nr][12] = -1.0; + } + else{ + new_path_metrics[12] = pm_candidate2; + trans_table[sample_nr][12] = 1.0; + } + + pm_candidate1 = old_path_metrics[6] - input_symbol_imag + increment[4]; + pm_candidate2 = old_path_metrics[14] - input_symbol_imag - increment[3]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[13] = pm_candidate1; + trans_table[sample_nr][13] = -1.0; + } + else{ + new_path_metrics[13] = pm_candidate2; + trans_table[sample_nr][13] = 1.0; + } + + pm_candidate1 = old_path_metrics[7] + input_symbol_imag - increment[5]; + pm_candidate2 = old_path_metrics[15] + input_symbol_imag + increment[2]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[14] = pm_candidate1; + trans_table[sample_nr][14] = -1.0; + } + else{ + new_path_metrics[14] = pm_candidate2; + trans_table[sample_nr][14] = 1.0; + } + + pm_candidate1 = old_path_metrics[7] - input_symbol_imag + increment[5]; + pm_candidate2 = old_path_metrics[15] - input_symbol_imag - increment[2]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[15] = pm_candidate1; + trans_table[sample_nr][15] = -1.0; + } + else{ + new_path_metrics[15] = pm_candidate2; + trans_table[sample_nr][15] = 1.0; + } + tmp=old_path_metrics; + old_path_metrics=new_path_metrics; + new_path_metrics=tmp; + + sample_nr++; + if(sample_nr==samples_num) + break; + + //Processing real states + real_imag=0; + input_symbol_real = input[sample_nr].real(); + + pm_candidate1 = old_path_metrics[0] - input_symbol_real - increment[7]; + pm_candidate2 = old_path_metrics[8] - input_symbol_real + increment[0]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[0] = pm_candidate1; + trans_table[sample_nr][0] = -1.0; + } + else{ + new_path_metrics[0] = pm_candidate2; + trans_table[sample_nr][0] = 1.0; + } + + pm_candidate1 = old_path_metrics[0] + input_symbol_real + increment[7]; + pm_candidate2 = old_path_metrics[8] + input_symbol_real - increment[0]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[1] = pm_candidate1; + trans_table[sample_nr][1] = -1.0; + } + else{ + new_path_metrics[1] = pm_candidate2; + trans_table[sample_nr][1] = 1.0; + } + + pm_candidate1 = old_path_metrics[1] - input_symbol_real - increment[6]; + pm_candidate2 = old_path_metrics[9] - input_symbol_real + increment[1]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[2] = pm_candidate1; + trans_table[sample_nr][2] = -1.0; + } + else{ + new_path_metrics[2] = pm_candidate2; + trans_table[sample_nr][2] = 1.0; + } + + pm_candidate1 = old_path_metrics[1] + input_symbol_real + increment[6]; + pm_candidate2 = old_path_metrics[9] + input_symbol_real - increment[1]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[3] = pm_candidate1; + trans_table[sample_nr][3] = -1.0; + } + else{ + new_path_metrics[3] = pm_candidate2; + trans_table[sample_nr][3] = 1.0; + } + + pm_candidate1 = old_path_metrics[2] - input_symbol_real - increment[5]; + pm_candidate2 = old_path_metrics[10] - input_symbol_real + increment[2]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[4] = pm_candidate1; + trans_table[sample_nr][4] = -1.0; + } + else{ + new_path_metrics[4] = pm_candidate2; + trans_table[sample_nr][4] = 1.0; + } + + pm_candidate1 = old_path_metrics[2] + input_symbol_real + increment[5]; + pm_candidate2 = old_path_metrics[10] + input_symbol_real - increment[2]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[5] = pm_candidate1; + trans_table[sample_nr][5] = -1.0; + } + else{ + new_path_metrics[5] = pm_candidate2; + trans_table[sample_nr][5] = 1.0; + } + + pm_candidate1 = old_path_metrics[3] - input_symbol_real - increment[4]; + pm_candidate2 = old_path_metrics[11] - input_symbol_real + increment[3]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[6] = pm_candidate1; + trans_table[sample_nr][6] = -1.0; + } + else{ + new_path_metrics[6] = pm_candidate2; + trans_table[sample_nr][6] = 1.0; + } + + pm_candidate1 = old_path_metrics[3] + input_symbol_real + increment[4]; + pm_candidate2 = old_path_metrics[11] + input_symbol_real - increment[3]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[7] = pm_candidate1; + trans_table[sample_nr][7] = -1.0; + } + else{ + new_path_metrics[7] = pm_candidate2; + trans_table[sample_nr][7] = 1.0; + } + + pm_candidate1 = old_path_metrics[4] - input_symbol_real - increment[3]; + pm_candidate2 = old_path_metrics[12] - input_symbol_real + increment[4]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[8] = pm_candidate1; + trans_table[sample_nr][8] = -1.0; + } + else{ + new_path_metrics[8] = pm_candidate2; + trans_table[sample_nr][8] = 1.0; + } + + pm_candidate1 = old_path_metrics[4] + input_symbol_real + increment[3]; + pm_candidate2 = old_path_metrics[12] + input_symbol_real - increment[4]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[9] = pm_candidate1; + trans_table[sample_nr][9] = -1.0; + } + else{ + new_path_metrics[9] = pm_candidate2; + trans_table[sample_nr][9] = 1.0; + } + + pm_candidate1 = old_path_metrics[5] - input_symbol_real - increment[2]; + pm_candidate2 = old_path_metrics[13] - input_symbol_real + increment[5]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[10] = pm_candidate1; + trans_table[sample_nr][10] = -1.0; + } + else{ + new_path_metrics[10] = pm_candidate2; + trans_table[sample_nr][10] = 1.0; + } + + pm_candidate1 = old_path_metrics[5] + input_symbol_real + increment[2]; + pm_candidate2 = old_path_metrics[13] + input_symbol_real - increment[5]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[11] = pm_candidate1; + trans_table[sample_nr][11] = -1.0; + } + else{ + new_path_metrics[11] = pm_candidate2; + trans_table[sample_nr][11] = 1.0; + } + + pm_candidate1 = old_path_metrics[6] - input_symbol_real - increment[1]; + pm_candidate2 = old_path_metrics[14] - input_symbol_real + increment[6]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[12] = pm_candidate1; + trans_table[sample_nr][12] = -1.0; + } + else{ + new_path_metrics[12] = pm_candidate2; + trans_table[sample_nr][12] = 1.0; + } + + pm_candidate1 = old_path_metrics[6] + input_symbol_real + increment[1]; + pm_candidate2 = old_path_metrics[14] + input_symbol_real - increment[6]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[13] = pm_candidate1; + trans_table[sample_nr][13] = -1.0; + } + else{ + new_path_metrics[13] = pm_candidate2; + trans_table[sample_nr][13] = 1.0; + } + + pm_candidate1 = old_path_metrics[7] - input_symbol_real - increment[0]; + pm_candidate2 = old_path_metrics[15] - input_symbol_real + increment[7]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[14] = pm_candidate1; + trans_table[sample_nr][14] = -1.0; + } + else{ + new_path_metrics[14] = pm_candidate2; + trans_table[sample_nr][14] = 1.0; + } + + pm_candidate1 = old_path_metrics[7] + input_symbol_real + increment[0]; + pm_candidate2 = old_path_metrics[15] + input_symbol_real - increment[7]; + if(pm_candidate1 > pm_candidate2){ + new_path_metrics[15] = pm_candidate1; + trans_table[sample_nr][15] = -1.0; + } + else{ + new_path_metrics[15] = pm_candidate2; + trans_table[sample_nr][15] = 1.0; + } + tmp=old_path_metrics; + old_path_metrics=new_path_metrics; + new_path_metrics=tmp; + + sample_nr++; + } + +/* +* Find the best from the stop states by comparing their path metrics. +* Not every stop state is always possible, so we are searching in +* a subset of them. +*/ + unsigned int best_stop_state; + float stop_state_metric, max_stop_state_metric; + best_stop_state = stop_states[0]; + max_stop_state_metric = old_path_metrics[best_stop_state]; + for(i=1; i< stops_num; i++){ + stop_state_metric = old_path_metrics[stop_states[i]]; + if(stop_state_metric > max_stop_state_metric){ + max_stop_state_metric = stop_state_metric; + best_stop_state = stop_states[i]; + } + } + +/* +* This table was generated with hope that it gives a litle speedup during +* traceback stage. +* Received bit is related to the number of state in the trellis. +* I've numbered states so their parity (number of ones) is related +* to a received bit. +*/ + static const unsigned int parity_table[PATHS_NUM] = { 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, }; + +/* +* Table of previous states in the trellis diagram. +* For GMSK modulation every state has two previous states. +* Example: +* previous_state_nr1 = prev_table[current_state_nr][0] +* previous_state_nr2 = prev_table[current_state_nr][1] +*/ + static const unsigned int prev_table[PATHS_NUM][2] = { {0,8}, {0,8}, {1,9}, {1,9}, {2,10}, {2,10}, {3,11}, {3,11}, {4,12}, {4,12}, {5,13}, {5,13}, {6,14}, {6,14}, {7,15}, {7,15}, }; + +/* +* Traceback and differential decoding of received sequence. +* Decisions stored in trans_table are used to restore best path in the trellis. +*/ + sample_nr=samples_num; + unsigned int state_nr=best_stop_state; + unsigned int decision; + bool out_bit=0; + + while(sample_nr>0){ + sample_nr--; + decision = (trans_table[sample_nr][state_nr]>0); + + if(decision != out_bit) + output[sample_nr]=-trans_table[sample_nr][state_nr]; + else + output[sample_nr]=trans_table[sample_nr][state_nr]; + + out_bit = out_bit ^ real_imag ^ parity_table[state_nr]; + state_nr = prev_table[state_nr][decision]; + real_imag = !real_imag; + } +} |