Fixed Viterbi decoder.

As it was using the wrong utility function for euclidean distance
calculation due to the recent migration from Cython based
implementation to pure Python implementation.

Author: veeresht

commpy/channelcoding/convcode.py

@@ -23,7 +23,7 @@
 from matplotlib.collections import PatchCollection
 import matplotlib.patches as mpatches
 
-from commpy.utilities import dec2bitarray, bitarray2dec, hamming_dist
+from commpy.utilities import dec2bitarray, bitarray2dec, hamming_dist, euclid_dist
 #from commpy.channelcoding.acstb import acs_traceback
 
 __all__ = ['Trellis', 'conv_encode', 'viterbi_decode']
@@ -445,7 +445,7 @@ def _acs_traceback(r_codeword, trellis, decoding_type,
                 pass
             elif decoding_type == 'unquantized':
                 i_codeword_array = 2*i_codeword_array - 1
-                branch_metric = euclid_dist_c(r_codeword, i_codeword_array, n)
+                branch_metric = euclid_dist(r_codeword, i_codeword_array)
             else:
                 pass
 
@@ -474,7 +474,6 @@ def _acs_traceback(r_codeword, trellis, decoding_type,
 
             dec_symbol = decoded_symbols[current_state, j]
             previous_state = paths[current_state, j]
-            #dec2bitarray_c(dec_symbol, k, decoded_bitarray)
             decoded_bitarray = dec2bitarray(dec_symbol, k)
             decoded_bits[(t-tb_depth-1)+(j+1)*k+count:(t-tb_depth-1)+(j+2)*k+count] =  \
                     decoded_bitarray
@@ -504,8 +503,10 @@ def viterbi_decode(coded_bits, trellis, tb_depth=None, decoding_type='hard'):
     tb_length : int
         Traceback depth (Typically set to 5*(M+1)).
 
-    decoding_type : str {'hard', 'soft', 'unquantized'}
+    decoding_type : str {'hard', 'unquantized'}
         The type of decoding to be used.
+        'hard' option is used for hard inputs (bits) to the decoder, e.g., BSC channel.
+        'unquantized' option is used for soft inputs (real numbers) to the decoder, e.g., BAWGN channel.
 
     Returns
     -------
@@ -536,15 +537,15 @@ def viterbi_decode(coded_bits, trellis, tb_depth=None, decoding_type='hard'):
     L = int(len(coded_bits)*rate)
 
     path_metrics = np.empty([number_states, 2])
-    path_metrics[:, :] = 10000
+    path_metrics[:, :] = 1000000
     path_metrics[0][0] = 0
     paths = np.empty([number_states, tb_depth], 'int')
-    paths[:, :] = 10000
+    paths[:, :] = 1000000
     paths[0][0] = 0
 
     decoded_symbols = np.zeros([number_states, tb_depth], 'int')
-    decoded_bits = np.empty(L+tb_depth+k, 'int')
-    r_codeword = np.empty(n, 'int')
+    decoded_bits = np.zeros(L+tb_depth+k, 'int')
+    r_codeword = np.zeros(n, 'int')
 
     tb_count = 1
     count = 0
@@ -561,7 +562,7 @@ def viterbi_decode(coded_bits, trellis, tb_depth=None, decoding_type='hard'):
                 pass
             elif decoding_type == 'unquantized':
                 r_codeword[:] = 0
-                r_codeword = r_codeword - 1
+                r_codeword = 2*r_codeword - 1
             else:
                 pass
 
@@ -583,4 +584,3 @@ def viterbi_decode(coded_bits, trellis, tb_depth=None, decoding_type='hard'):
             current_number_states = 1
 
     return decoded_bits[0:len(decoded_bits)-tb_depth-1]
-    #return decoded_bits[0:len(decoded_bits)-tb_depth-total_memory-total_memory%k-k]

commpy/utilities.py

@@ -1,7 +1,7 @@
 
 #   Copyright 2012 Veeresh Taranalli <[email protected]>
 #
-#   This file is part of CommPy.   
+#   This file is part of CommPy.
 #
 #   CommPy is free software: you can redistribute it and/or modify
 #   it under the terms of the GNU General Public License as published by
@@ -22,29 +22,29 @@
 
 def dec2bitarray(in_number, bit_width):
     """
-    Converts a positive integer to NumPy array of the specified size containing 
+    Converts a positive integer to NumPy array of the specified size containing
     bits (0 and 1).
-    
+
     Parameters
     ----------
     in_number : int
         Positive integer to be converted to a bit array.
-    
+
     bit_width : int
         Size of the output bit array.
-    
+
     Returns
     -------
     bitarray : 1D ndarray of ints
         Array containing the binary representation of the input decimal.
-    
+
     """
 
     binary_string = bin(in_number)
     length = len(binary_string)
     bitarray = np.zeros(bit_width, 'int')
     for i in xrange(length-2):
-        bitarray[bit_width-i-1] = int(binary_string[length-i-1]) 
+        bitarray[bit_width-i-1] = int(binary_string[length-i-1])
 
     return bitarray
 
@@ -62,7 +62,7 @@ def bitarray2dec(in_bitarray):
 
     for i in xrange(len(in_bitarray)):
         number = number + in_bitarray[i]*pow(2, len(in_bitarray)-1-i)
-  
+
     return number
 
 def hamming_dist(in_bitarray_1, in_bitarray_2):
@@ -79,7 +79,7 @@ def hamming_dist(in_bitarray_1, in_bitarray_2):
     """
 
     distance = np.bitwise_xor(in_bitarray_1, in_bitarray_2).sum()
-    
+
     return distance
 
 def euclid_dist(in_array1, in_array2):
@@ -88,20 +88,20 @@ def euclid_dist(in_array1, in_array2):
 
     Parameters
     ----------
-    in_bitarray_1: 1-D ndarray of ints
+    in_array1: 1-D ndarray of floats
         NumPy array of real values.
 
-    in_bitarray_2: 1-D ndarray of ints
+    in_array2: 1-D ndarray of floats
         NumPy array of real values.
     """
     distance = ((in_array1 - in_array2)*(in_array1 - in_array2)).sum()
-        
+
     return distance
-    
+
 def upsample(x, n):
     """
-    Upsample the input array by a factor of n 
-    
+    Upsample the input array by a factor of n
+
     Adds n-1 zeros between consecutive samples of x
 
     Parameters
@@ -119,5 +119,3 @@ def upsample(x, n):
         y[i::n] = zero_array
 
     return y
-    
-