diff options
Diffstat (limited to 'gr-digital/python/digital/soft_dec_lut_gen.py')
| -rw-r--r-- | gr-digital/python/digital/soft_dec_lut_gen.py | 48 |
1 files changed, 26 insertions, 22 deletions
diff --git a/gr-digital/python/digital/soft_dec_lut_gen.py b/gr-digital/python/digital/soft_dec_lut_gen.py index 898af5320d..13c50251a5 100644 --- a/gr-digital/python/digital/soft_dec_lut_gen.py +++ b/gr-digital/python/digital/soft_dec_lut_gen.py @@ -11,6 +11,7 @@ import numpy + def soft_dec_table_generator(soft_dec_gen, prec, Es=1): ''' | Builds a LUT that is a list of tuples. The tuple represents the @@ -71,7 +72,7 @@ def soft_dec_table_generator(soft_dec_gen, prec, Es=1): ''' npts = int(2.0**prec) - maxd = Es*numpy.sqrt(2.0)/2.0 + maxd = Es * numpy.sqrt(2.0) / 2.0 yrng = numpy.linspace(-maxd, maxd, npts) xrng = numpy.linspace(-maxd, maxd, npts) @@ -83,6 +84,7 @@ def soft_dec_table_generator(soft_dec_gen, prec, Es=1): table.append(decs) return table + def soft_dec_table(constel, symbols, prec, npwr=1): ''' Similar in nature to soft_dec_table_generator above. Instead, this @@ -120,6 +122,7 @@ def soft_dec_table(constel, symbols, prec, npwr=1): table.append(decs) return table + def calc_soft_dec_from_table(sample, table, prec, Es=1.0): ''' Takes in a complex sample and converts it from the coordinates @@ -144,25 +147,26 @@ def calc_soft_dec_from_table(sample, table, prec, Es=1.0): constellation. ''' lut_scale = 2.0**prec - maxd = Es*numpy.sqrt(2.0)/2.0 - scale = (lut_scale) / (2.0*maxd) + maxd = Es * numpy.sqrt(2.0) / 2.0 + scale = (lut_scale) / (2.0 * maxd) - alpha = 0.99 # to keep index within bounds + alpha = 0.99 # to keep index within bounds xre = sample.real xim = sample.imag - xre = ((maxd + min(alpha*maxd, max(-alpha*maxd, xre))) * scale) - xim = ((maxd + min(alpha*maxd, max(-alpha*maxd, xim))) * scale) - index = int(xre) + lut_scale*int(xim) + xre = ((maxd + min(alpha * maxd, max(-alpha * maxd, xre))) * scale) + xim = ((maxd + min(alpha * maxd, max(-alpha * maxd, xim))) * scale) + index = int(xre) + lut_scale * int(xim) max_index = lut_scale**2 while(index >= max_index): - index -= lut_scale; + index -= lut_scale while(index < 0): - index += lut_scale; + index += lut_scale return table[int(index)] + def calc_soft_dec(sample, constel, symbols, npwr=1): ''' This function takes in any consteallation and symbol symbol set @@ -186,8 +190,8 @@ def calc_soft_dec(sample, constel, symbols, npwr=1): M = len(constel) k = int(numpy.log2(M)) - tmp = 2*k*[0] - s = k*[0] + tmp = 2 * k * [0] + s = k * [0] for i in range(M): # Calculate the distance between the sample and the current @@ -200,21 +204,21 @@ def calc_soft_dec(sample, constel, symbols, npwr=1): for j in range(k): # Get the bit at the jth index - mask = 1<<j + mask = 1 << j bit = (symbols[i] & mask) >> j # If the bit is a 0, add to the probability of a zero if(bit == 0): - tmp[2*j+0] += d + tmp[2 * j + 0] += d # else, add to the probability of a one else: - tmp[2*j+1] += d + tmp[2 * j + 1] += d # Calculate the log-likelihood ratio for all bits based on the # probability of ones (tmp[2*i+1]) over the probability of a zero # (tmp[2*i+0]). for i in range(k): - s[k-1-i] = (numpy.log(tmp[2*i+1]) - numpy.log(tmp[2*i+0])) + s[k - 1 - i] = (numpy.log(tmp[2 * i + 1]) - numpy.log(tmp[2 * i + 0])) return s @@ -225,19 +229,19 @@ def show_table(table): pp = "" subi = 1 subj = 0 - for i in reversed(list(range(prec+1))): - if(i == prec//2): - pp += "-----" + prec*((nbits*8)+3)*"-" + "\n" + for i in reversed(list(range(prec + 1))): + if(i == prec // 2): + pp += "-----" + prec * ((nbits * 8) + 3) * "-" + "\n" subi = 0 continue - for j in range(prec+1): - if(j == prec//2): + for j in range(prec + 1): + if(j == prec // 2): pp += "| " subj = 1 else: - item = table[prec*(i-subi) + (j-subj)] + item = table[prec * (i - subi) + (j - subj)] pp += "( " - for t in range(nbits-1, -1, -1): + for t in range(nbits - 1, -1, -1): pp += "{0: .4f} ".format(item[t]) pp += ") " pp += "\n" |