diff options
Diffstat (limited to 'gr-trellis/python/trellis/fsm_utils.py')
| -rw-r--r-- | gr-trellis/python/trellis/fsm_utils.py | 119 |
1 files changed, 54 insertions, 65 deletions
diff --git a/gr-trellis/python/trellis/fsm_utils.py b/gr-trellis/python/trellis/fsm_utils.py index efc526c0e7..25c552a226 100644 --- a/gr-trellis/python/trellis/fsm_utils.py +++ b/gr-trellis/python/trellis/fsm_utils.py @@ -29,8 +29,6 @@ import sys import numpy -#from gnuradio import trellis - try: import scipy.linalg except ImportError: @@ -38,15 +36,14 @@ except ImportError: sys.exit(1) - -###################################################################### -# Decimal to any base conversion. -# Convert 'num' to a list of 'l' numbers representing 'num' -# to base 'base' (most significant symbol first). -###################################################################### -def dec2base(num,base,l): - s=list(range(l)) - n=num +def dec2base(num, base, l): + """ + Decimal to any base conversion. + Convert 'num' to a list of 'l' numbers representing 'num' + to base 'base' (most significant symbol first). + """ + s = list(range(l)) + n = num for i in range(l): s[l-i-1]=n%base n=int(n / base) @@ -55,30 +52,28 @@ def dec2base(num,base,l): return s -###################################################################### -# Conversion from any base to decimal. -# Convert a list 's' of symbols to a decimal number -# (most significant symbol first) -###################################################################### -def base2dec(s,base): - num=0 +def base2dec(s, base): + """ + Conversion from any base to decimal. + Convert a list 's' of symbols to a decimal number + (most significant symbol first) + """ + num = 0 for i in range(len(s)): - num=num*base+s[i] + num = num * base + s[i] return num - - -###################################################################### -# Automatically generate the lookup table that maps the FSM outputs -# to channel inputs corresponding to a channel 'channel' and a modulation -# 'mod'. Optional normalization of channel to unit energy. -# This table is used by the 'metrics' block to translate -# channel outputs to metrics for use with the Viterbi algorithm. -# Limitations: currently supports only one-dimensional modulations. -###################################################################### -def make_isi_lookup(mod,channel,normalize): - dim=mod[0] +def make_isi_lookup(mod, channel, normalize): + """ + Automatically generate the lookup table that maps the FSM outputs + to channel inputs corresponding to a channel 'channel' and a modulation + 'mod'. Optional normalization of channel to unit energy. + This table is used by the 'metrics' block to translate + channel outputs to metrics for use with the Viterbi algorithm. + Limitations: currently supports only one-dimensional modulations. + """ + dim = mod[0] constellation = mod[1] if normalize: @@ -90,39 +85,36 @@ def make_isi_lookup(mod,channel,normalize): lookup=list(range(len(constellation)**len(channel))) for o in range(len(constellation)**len(channel)): - ss=dec2base(o,len(constellation),len(channel)) - ll=0 + ss = dec2base(o, len(constellation), len(channel)) + ll = 0 for i in range(len(channel)): ll=ll+constellation[ss[i]]*channel[i] lookup[o]=ll return (1,lookup) - - - - -###################################################################### -# Automatically generate the signals appropriate for CPM -# decomposition. -# This decomposition is based on the paper by B. Rimoldi -# "A decomposition approach to CPM", IEEE Trans. Info Theory, March 1988 -# See also my own notes at http://www.eecs.umich.edu/~anastas/docs/cpm.pdf -###################################################################### -def make_cpm_signals(K,P,M,L,q,frac): - - Q=numpy.size(q) / L - h=(1.0*K) / P - f0=-h*(M-1)/2 - dt=0.0; # maybe start at t=0.5 - t=(dt+numpy.arange(0 / Q),Q) - qq=numpy.zeros(Q) +def make_cpm_signals(K, P, M, L, q, frac): + """ + Automatically generate the signals appropriate for CPM + decomposition. + This decomposition is based on the paper by B. Rimoldi + "A decomposition approach to CPM", IEEE Trans. Info Theory, March 1988 + See also my own notes at http://www.eecs.umich.edu/~anastas/docs/cpm.pdf + """ + Q = numpy.size(q) / L + h = (1.0 * K) / P + f0 = -h * (M - 1) / 2 + dt = 0.0 + # maybe start at t=0.5 + t = (dt + numpy.arange(0, Q)) / Q + qq = numpy.zeros(Q) for m in range(L): - qq=qq + q[m*Q:m*Q+Q] - w=math.pi*h*(M-1)*t-2*math.pi*h*(M-1)*qq+math.pi*h*(L-1)*(M-1) + qq = qq + q[m * Q:m * Q + Q] + w = math.pi * h * (M - 1) * t - 2 * math.pi * h * ( + M - 1) * qq + math.pi * h * (L - 1) * (M - 1) - X=(M**L)*P - PSI=numpy.empty((X,Q)) + X = (M**L) * P + PSI = numpy.empty((X, Q)) for x in range(X): xv=dec2base(x / P,M,L) xv=numpy.append(xv, x%P) @@ -165,25 +157,23 @@ def make_cpm_signals(K,P,M,L,q,frac): Sf = S[Esi[0:v0+1]] #print(Sf) - - return (f0,SS,S,F,Sf,Ff,N) - #return f0 - + return (f0, SS, S, F, Sf, Ff, N) +#return f0 ###################################################################### # A list of common modulations. # Format: (dimensionality,constellation) ###################################################################### -pam2 = (1,[-1, 1]) -pam4 = (1,[-3, -1, 3, 1]) # includes Gray mapping -pam8 = (1,[-7, -5, -3, -1, 1, 3, 5, 7]) +pam2 = (1, [-1, 1]) +pam4 = (1, [-3, -1, 3, 1]) # includes Gray mapping +pam8 = (1, [-7, -5, -3, -1, 1, 3, 5, 7]) psk4=(2,[1, 0, \ 0, 1, \ 0, -1,\ - -1, 0]) # includes Gray mapping + -1, 0]) # includes Gray mapping psk8=(2,[math.cos(2*math.pi*0/8), math.sin(2*math.pi*0/8), \ math.cos(2*math.pi*1/8), math.sin(2*math.pi*1/8), \ @@ -233,4 +223,3 @@ orth4=(4,[1, 0, 0, 0, \ # C test channel (J. Proakis, Digital Communications, McGraw-Hill Inc., 2001) c_channel = [0.227, 0.460, 0.688, 0.460, 0.227] - |