Initial commit - gsm-receiver with removed quick hacks
diff --git a/lib/viterbi_detector.cc b/lib/viterbi_detector.cc
new file mode 100644
index 0000000..f3445cf
--- /dev/null
+++ b/lib/viterbi_detector.cc
@@ -0,0 +1,554 @@
+/* -*- c++ -*- */
+/*
+ * @file
+ * @author Piotr Krysik <pkrysik@stud.elka.pw.edu.pl>
+ * @section LICENSE
+ *
+ * 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 3, 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; see the file COPYING. If not, write to
+ * the Free Software Foundation, Inc., 51 Franklin Street,
+ * Boston, MA 02110-1301, 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;
+ }
+}