/*! * \file convolutional.h * \brief General functions used to implement convolutional encoding. * \author Matthew C. Valenti * * ------------------------------------------------------------------------- * * Copyright (C) 2006-2008 Matthew C. Valenti * * GNSS-SDR is a software defined Global Navigation * Satellite Systems receiver * * This file is part of GNSS-SDR. * * GNSS-SDR 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 of the License, or * (at your option) any later version. * * This file is a derived work of the original file, which had this note: * * Last updated on May 22, 2008 * * The functions in this file are part of the Iterative Solutions * Coded Modulation Library. The Iterative Solutions Coded Modulation * Library is free software; you can redistribute it and/or modify it * under the terms of the GNU Lesser General Public License as published * by the Free Software Foundation; either version 2.1 of the License, * or (at your option) any later version. * * This library 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 * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this library; if not, write to the Free Software * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef GNSS_SDR_CONVOLUTIONAL_H_ #define GNSS_SDR_CONVOLUTIONAL_H_ #include // for calloc /* define constants used throughout the library */ const float MAXLOG = 1e7; /* Define infinity */ /*! * \brief Determines if a symbol has odd (1) or even (0) parity * Output parameters: * \return (returned int): The symbol's parity = 1 for odd and 0 for even * * \param[in] symbol The integer-valued symbol * \param[in] length The highest bit position in the symbol * * This function is used by nsc_enc_bit(), rsc_enc_bit(), and rsc_tail() */ inline static int parity_counter(int symbol, int length) { int counter; int temp_parity = 0; for (counter = 0; counter < length; counter++) { temp_parity = temp_parity^(symbol & 1); symbol = symbol >> 1; } return(temp_parity); } /*! * \brief Convolutionally encodes a single bit using a rate 1/n encoder. * Takes in one input bit at a time, and produces a n-bit output. * * \param[in] input The input data bit (i.e. a 0 or 1). * \param[in] state_in The starting state of the encoder (an int from 0 to 2^m-1). * \param[in] g[] An n-element vector containing the code generators in binary form. * \param[in] KK The constraint length of the convolutional code. * \param[out] output_p[] An n-element vector containing the encoded bits. * \param[out] state_out_p[] An integer containing the final state of the encoder * (i.e. the state after encoding this bit) * * This function is used by nsc_transit() */ inline static int nsc_enc_bit(int state_out_p[], int input, int state_in, int g[], int KK, int nn) { /* declare variables */ int state, i; int out_ = 0; /* create a word made up of state and new input */ state = (input << (KK - 1))^state_in; /* AND the word with the generators */ for (i = 0; i < nn; i++) { /* update output symbol */ out_ = (out_ << 1) + parity_counter(state & g[i], KK); } /* shift the state to make the new state */ state_out_p[0] = state >> 1; return(out_); } /*! * \brief Function that creates the transit and output vectors */ inline static void nsc_transit(int output_p[], int trans_p[], int input, int g[], int KK, int nn) { int nextstate[1]; int state, states; states = (1 << (KK - 1)); /* The number of states: 2^mm */ /* Determine the output and next state for each possible starting state */ for(state = 0; state < states; state++) { output_p[state] = nsc_enc_bit(nextstate, input, state, g, KK, nn); trans_p[state] = nextstate[0]; } return; } /*! * \brief Computes the branch metric used for decoding. * \return (returned float) The metric between the hypothetical symbol and the received vector * \param[in] rec_array The received vector, of length nn * \param[in] symbol The hypothetical symbol * \param[in] nn The length of the received vector * */ inline static float Gamma(float rec_array[], int symbol, int nn) { float rm = 0; int i; int mask = 1; for (i = 0; i < nn; i++) { if (symbol & mask) rm += rec_array[nn - i - 1]; mask = mask << 1; } return(rm); } /*! * \brief Uses the Viterbi algorithm to perform hard-decision decoding of a convolutional code. * \param[in] out0[] The output bits for each state if input is a 0. * \param[in] state0[] The next state if input is a 0. * \param[in] out1[] The output bits for each state if input is a 1. * \param[in] state1[] The next state if input is a 1. * \param[in] r[] The received signal in LLR-form. For BPSK, must be in form r = 2*a*y/(sigma^2). * \param[in] KK The constraint length of the convolutional code. * \param[in] LL The number of data bits. * \param[out] output_u_int[] Hard decisions on the data bits * */ inline static void Viterbi(int output_u_int[], int out0[], int state0[], int out1[], int state1[], double input_c[], int KK, int nn, int LL) { int i, t, state, mm, states; int number_symbols; float metric; float *prev_section, *next_section; int *prev_bit; int *prev_state; float *metric_c; /* Set of all possible branch metrics */ float *rec_array; /* Received values for one trellis section */ float max_val; /* some derived constants */ mm = KK - 1; states = 1 << mm; /* 2^mm */ number_symbols = 1 << nn; /* 2^nn */ /* dynamically allocate memory */ prev_section = static_cast(calloc( states, sizeof(float) )); next_section = static_cast(calloc( states, sizeof(float) )); prev_bit = static_cast(calloc( states*(LL + mm), sizeof(int) )); prev_state = static_cast(calloc( states*(LL + mm), sizeof(int) )); rec_array = static_cast(calloc( nn, sizeof(float) )); metric_c = static_cast(calloc( number_symbols, sizeof(float) )); /* initialize trellis */ for (state = 0; state < states; state++) { prev_section[state] = -MAXLOG; next_section[state] = -MAXLOG; } prev_section[0] = 0; /* start in all-zeros state */ /* go through trellis */ for (t = 0; t < LL + mm; t++) { for (i = 0; i < nn; i++) rec_array[i] = static_cast(input_c[nn*t + i]); /* precompute all possible branch metrics */ for (i = 0; i < number_symbols; i++) metric_c[i] = Gamma( rec_array, i, nn ); /* step through all states */ for (state = 0; state < states; state++) { /* hypothesis: info bit is a zero */ metric = prev_section[state] + metric_c[ out0[ state ] ]; /* store new metric if more than metric in storage */ if ( metric > next_section[state0[state]] ) { next_section[state0[state]] = metric; prev_state[t*states + state0[state]] = state; prev_bit[t*states + state0[state]] = 0; } /* hypothesis: info bit is a one */ metric = prev_section[state] + metric_c[ out1[ state ] ]; /* store new metric if more than metric in storage */ if ( metric > next_section[state1[state]] ) { next_section[state1[state]] = metric; prev_state[t*states + state1[state]] = state; prev_bit[t*states + state1[state]] = 1; } } /* normalize */ max_val = 0; for (state = 0; state < states; state++) { if (next_section[state] > max_val) { max_val = next_section[state]; } } for (state = 0; state < states; state++) { prev_section[state] = next_section[state] - max_val; next_section[state] = -MAXLOG; } } /* trace-back operation */ state = 0; /* tail, no need to output */ for (t = LL + mm - 1; t >= LL; t--) { state = prev_state[t*states + state]; } for (t = LL - 1; t >= 0; t--) { output_u_int[t] = prev_bit[t*states + state]; state = prev_state[t*states + state]; } /* free the dynamically allocated memory */ free(prev_section); free(next_section); free(prev_bit); free(prev_state); free(rec_array); free(metric_c); } #endif