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fsk_lecim_demod.py
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fsk_lecim_demod.py
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import numpy as np
import fsk_lecim_constants
import fsk_lecim_phy
import commpy.channelcoding.convcode as cc # I use that library, so i don't need to implement the viterbi algorithm
from math import ceil, floor, cos
from cmath import exp, pi, phase
from scipy import signal
class fsk_lecim_demodulator(fsk_lecim_phy.physical_layer):
def demodulate(self, data_in, phyPacketSize):
if self.pfsk:
PPDU = self.demodulator_pfsk(data_in)
else:
PPDU = self.demodulator_fsk(data_in)
PPDU = self.PPDU_analyser(PPDU)
PPDU[0] = self.despreading(PPDU[0])
PPDU[0] = self.deinterleaver(PPDU[0], True)
PPDU[0] = self.deinterleaver(PPDU[0], True)
PHR = self.fec_decoder(PPDU[0])
self.PHR = PHR
self.PHR_analyser()
if self.phyPacketSize != phyPacketSize:
print 'good PDU length'
self.phyPacketSize = phyPacketSize
self.nBlock = int(ceil((8*self.phyPacketSize+6)/(self.nPsdu/2.0)))
PPDU[1] = self.despreading(PPDU[1])
PPDU[1] = self.deinterleaver(PPDU[1])
PPDU[1] = self.data_dewhitening(PPDU[1])
PPDU[1] = self.deinterleaver(PPDU[1])
PDU = self.fec_decoder(PPDU[1])
PDU = self.zero_padding_remover(PDU)
return [PHR, PDU]
def demodulate_coherent(self, data_in, phyPacketSize):
if self.pfsk:
PPDU = self.demodulator_pfsk_coherent(data_in)
else:
PPDU = self.demodulator_fsk_coherent(data_in)
PPDU = self.PPDU_analyser(PPDU)
PPDU[0] = self.despreading(PPDU[0])
PPDU[0] = self.deinterleaver(PPDU[0], True)
PPDU[0] = self.deinterleaver(PPDU[0], True)
PHR = self.fec_decoder(PPDU[0])
self.PHR = PHR
self.PHR_analyser()
if self.phyPacketSize != phyPacketSize:
print 'good PDU length'
self.phyPacketSize = phyPacketSize
self.nBlock = int(ceil((8*self.phyPacketSize+6)/(self.nPsdu/2.0)))
PPDU[1] = self.despreading(PPDU[1])
PPDU[1] = self.deinterleaver(PPDU[1])
PPDU[1] = self.data_dewhitening(PPDU[1])
PPDU[1] = self.deinterleaver(PPDU[1])
PDU = self.fec_decoder(PPDU[1])
PDU = self.zero_padding_remover(PDU)
return [PHR, PDU]
#Detect signal and give a first estimation of delay
def signal_detector(self,a):
delay = -1
for k in range(len(a)-self.sps):
sum0 = [0, 0]
for p in range(self.sps):
sum0[0] += a[k+p][0]
sum0[1] += a[k+p][1]
if (abs(sum0[0]) >= self.sps/2.0 and abs(sum0[0]) >= abs(sum0[1])) or (abs(sum0[1]) >= self.sps/2.0 and abs(sum0[1]) > abs(sum0[0])):
print 'signal detected '
delay = k
print delay
break
delay = self.early_late(a, delay)
if self.pfsk:
if delay - self.sps < 0:
return 0
else:
return delay - self.sps
else:
return delay
#Compute a precise estimation of delay, with noisy channel the estimation the estimation error is acceptable
def early_late(self, a, delay):
if delay == -1:
return -1
else:
delta = int(self.sps/4.0)+1
a = np.concatenate([np.zeros((delta,2)), a])
init = delay-self.sps
if init - delta < 0:
init = delta
for k in range(init, delay+self.sps):
sum0 = [0, 0]
sum1 = [0, 0]
sum2 = [0, 0]
for p in range(self.sps):
sum0[0] += a[k+p-delta][0]
sum0[1] += a[k+p-delta][1]
sum1[0] += a[k+p+delta][0]
sum1[1] += a[k+p+delta][1]
sum2[0] += a[k+p][0]
sum2[1] += a[k+p][1]
if (abs(abs(sum0[0])-abs(sum1[0])) < 2 and abs(sum2[0]) > abs(sum0[0]) and abs(sum2[0]) > abs(sum1[0]) and abs(sum2[0]) >= self.sps/2.0) or (abs(abs(sum0[1])-abs(sum1[1])) < 2 and abs(sum2[1]) > abs(sum0[1]) and abs(sum2[1]) > abs(sum1[1]) and abs(sum2[1]) >= self.sps/2.0):
# print '================='
delay = k - delta
# print k - delta
# print abs(sum0[0]), abs(sum0[1])
# print abs(sum2[0]), abs(sum2[1])
# print abs(sum1[0]), abs(sum1[1])
# print '########################'
print 'delay'
if self.pfsk:
print delay-self.sps
else:
print delay
return delay
#demodulator FSK correlator (non coherent)
def demodulator_fsk(self, data_in):
a = np.zeros((len(data_in),2), dtype=complex)
sum0 = [0, 0]
Z = [0, 0]
for i in range(len(data_in)):
a[i][0] = data_in[i]*exp(1j*2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
a[i][1] = data_in[i]*exp(1j*-2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
delay = self.signal_detector(a)
data_out = np.zeros((int((len(data_in) - delay + (delay % self.sps))/self.sps),), dtype=int)
if delay == -1:
print 'no signal detected, only noise'
return data_out
for k in range(len(data_out)-1):
sum0 = [0, 0]
for p in range(self.sps):
sum0[0] += a[self.sps*k+p+delay][0]
sum0[1] += a[self.sps*k+p+delay][1]
Z[0]= abs(sum0[0])**2 #Z0
Z[1]= abs(sum0[1])**2 #Z1
if Z[0] - Z[1] >= 0: #Z0-Z1 Threshold 0
data_out[k] = 0
d = 0
else:
data_out[k] = 1
d =1
return data_out
#demodulator FSK correlator (coherent)
def demodulator_fsk_coherent(self, data_in):
a = np.zeros((len(data_in),2), dtype = complex)
Z = [0, 0]
d = 0
for i in range(len(data_in)):
a[i][0] = data_in[i]*exp(1j*2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
a[i][1] = data_in[i]*exp(1j*-2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
delay = self.signal_detector(a)
data_out = np.zeros((int((len(data_in) - delay + (delay % self.sps))/self.sps),), dtype = int)
if delay == -1:
print 'no signal detected, only noise'
return data_out
for k in range(len(data_out)-1):
sum0 = [0, 0]
for p in range(self.sps):
sum0[0] += a[self.sps*k+p+delay][0]
sum0[1] += a[self.sps*k+p+delay][1]
phioff0 = phase(sum0[0])
phioff1 = phase(sum0[1])
sum0[0] = sum0[0] * exp(-1j*phioff0)
sum0[1] = sum0[1] * exp(-1j*phioff1)
Z[0]= sum0[0].real #Z0
Z[1]= sum0[1].real #Z1
if Z[0] - Z[1] >= 0: #Z0-Z1 Threshold 0
data_out[k] = 0
else:
data_out[k] = 1
return data_out
#Demodulator P-FSK correlator (non coherent)
def demodulator_pfsk(self, data_in):
a = np.zeros((len(data_in),2), dtype = complex)
sum0 = [0, 0]
Z = [0, 0, 0, 0]
delta = [0, 0]
for i in range(len(data_in)):
a[i][0] = data_in[i]*exp(1j*2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
a[i][1] = data_in[i]*exp(1j*-2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
delay = self.signal_detector(a)
data_out = np.zeros((int((len(data_in) - delay + (delay % self.sps))/self.sps),), dtype=int)
if delay == -1:
print 'no signal detected, only noise'
return data_out
for k in range(len(data_out)-1):
for p in range(self.sps):
sum0[0] += a[self.sps*k+p+delay][0]
sum0[1] += a[self.sps*k+p+delay][1]
if (k%2) == 0:
Z[0]= abs(sum0[0])**2 #Z0(2k)
Z[1]= abs(sum0[1])**2 #Z1(2k)
else:
Z[2]= abs(sum0[0])**2 #Z0(2k+1)
Z[3]= abs(sum0[1])**2 #Z1(2k+1)
delta = [Z[0]+Z[1], Z[2]+Z[3]]
if delta[0] - delta[1] >= 0: #Position bit
data_out[k] = 0
if Z[0]-Z[1]>=0:
data_out[k-1] = 0
else:
data_out[k-1] = 1
else:
data_out[k] = 1
if Z[2]-Z[3]>=0:
data_out[k-1] = 0
else:
data_out[k-1] = 1
sum0 = [0, 0]
return data_out
#Demodulator P-FSK correlator (coherent)
def demodulator_pfsk_coherent(self, data_in):
a = np.zeros((len(data_in),2), dtype = complex)
sum0 = [0, 0]
Z = [0, 0, 0, 0]
d = [0, 0]
delta = [0, 0]
for i in range(len(data_in)):
a[i][0] = data_in[i]*exp(1j*2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
a[i][1] = data_in[i]*exp(1j*-2*pi*self.freq_dev*i/(self.sps*self.symbol_rate))
delay = self.signal_detector(a)
data_out = np.zeros((int((len(data_in) - delay + (delay % self.sps))/self.sps),), dtype=int)
if delay == -1:
print 'no signal detected, only noise'
return data_out
for k in range(len(data_out)-1):
for p in range(self.sps):
sum0[0] += a[self.sps*k+p+delay][0]
sum0[1] += a[self.sps*k+p+delay][1]
phioff0 = phase(sum0[0])
phioff1 = phase(sum0[1])
sum0[0] = sum0[0] * exp(-1j*phioff0)
sum0[1] = sum0[1] * exp(-1j*phioff1)
if (k%2) == 0:
Z[0]= sum0[0].real #Z0(2k)
Z[1]= sum0[1].real #Z1(2k)
else:
Z[2]= sum0[0].real #Z0(2k+1)
Z[3]= sum0[1].real #Z1(2k+1)
delta = [Z[0]+Z[1], Z[2]+Z[3]]
if delta[0] - delta[1] >= 0: #Position bit
data_out[k] = 0
if Z[0]-Z[1]>=0:
data_out[k-1] = 0
else:
data_out[k-1] = 1
else:
data_out[k] = 1
if Z[2]-Z[3]>=0:
data_out[k-1] = 0
else:
data_out[k-1] = 1
sum0 = [0, 0]
return data_out
#deinterleave K
def deinterleave_k(self, k, Ndepth, lambda_):
a = int((Ndepth-1-k)*lambda_-(Ndepth-1)*floor((Ndepth-1-k)*lambda_/float(Ndepth)))
return a
#deinterleaver
def deinterleaver(self, data_in, phr = False):
data_out=np.zeros((len(data_in),),dtype = int)
if(phr):
for i in range(self.nPhr):
data_out[self.deinterleave_k(i,self.nPhr,self.lambdaPhr)] = data_in[i]
else:
for m in range(self.nBlock):
for k in range(self.nPsdu):
data_out[m*self.nPsdu+self.deinterleave_k(k,self.nPsdu,self.lambdaPsdu)] = data_in[m*self.nPsdu+k]
return data_out
#Viterbi/ FEC decoder
def fec_decoder(self, data_in):
memory = np.array([6])
g_matrix = np.array([[91,121]]) # G(D) = [1+D^2+D^3+D^5+D^6, 1+D+D^2+D^3+D^6]
trellis = cc.Trellis(memory, g_matrix)
data_out = cc.viterbi_decode(data_in, trellis, tb_depth = int(len(data_in)/2))
return data_out[:-6]
#PPDU analyser
def PPDU_analyser(self, data_in):
SHRlength = -1
SFDlength = 24
offset = 44
for k in range(len(data_in)-SFDlength):
if np.array_equal(self.SFD, data_in[k:k+SFDlength]):
print 'SFD detected'
print data_in[k:k+SFDlength]
SHRlength = k + SFDlength
if SHRlength == -1:
SHRlength = (int(floor(self.phyLecimFskPreambleLength))+3)*8
if self.phyLecimFskSpreading:
offset = offset * self.phyLecimFskSpreadingFactor
return [data_in[SHRlength:SHRlength+offset], data_in[SHRlength+offset:]]
#PHR analyser
def PHR_analyser(self):
pdu_len = 0
if self.PHR[12]:
self.FCS = True
else:
self.FCS = False
if self.PHR[11]:
self.dataWhitening = True
else:
self.dataWhitening = False
for i in range(11):
pdu_len = pdu_len + (self.PHR[i]<<i)
parity_bit = self.PHR[0]
for i in range(1,13):
parity_bit = parity_bit^self.PHR[i]
if self.PHR[13]!=parity_bit:
print 'Parity bit error'
self.phyPacketSize = pdu_len
self.nBlock = int(ceil((8*self.phyPacketSize+6)/(self.nPsdu/2.0)))
#Despreading fundtion
def despreading(self, data_in):
if self.phyLecimFskSpreading:
factor = self.phyLecimFskSpreadingFactor
data_out = np.zeros((int(len(data_in)/float(factor)),),dtype = int)
if self.phyLecimFskSpreadingAlternating:
for i in range(len(data_out)):
if np.array_equal(np.tile(fsk_lecim_constants.spreadingAlternating_0,factor/2), data_in[factor*i:factor*(i+1)]):
data_out[i] = 0
if np.array_equal(np.tile(fsk_lecim_constants.spreadingAlternating_1,factor/2), data_in[factor*i:factor*(i+1)]):
data_out[i] = 1
else:
if factor <= 4:
for i in range(len(data_out)):
if np.array_equal(np.tile(fsk_lecim_constants.spreadingAlternating_0,factor/2), data_in[factor*i:factor*(i+1)]):
data_out[i] = 0
if np.array_equal(np.tile(fsk_lecim_constants.spreadingAlternating_1,factor/2), data_in[factor*i:factor*(i+1)]):
data_out[i] = 1
if factor == 8:
for i in range(len(data_out)):
if np.array_equal(fsk_lecim_constants.spreadingNonAlternating8_0,data_in[factor*i:factor*(i+1)]):
data_out[i] = 0
if np.array_equal(fsk_lecim_constants.spreadingNonAlternating8_1,data_in[factor*i:factor*(i+1)]):
data_out[i] = 1
if factor == 16:
for i in range(len(data_in)):
if np.array_equal(fsk_lecim_constants.spreadingNonAlternating16_0,data_in[factor*i:factor*(i+1)]):
data_out[i] = 0
if np.array_equal(fsk_lecim_constants.spreadingNonAlternating16_1,data_in[factor*i:factor*(i+1)]):
data_out[i] = 1
return data_out
else:
return data_in
#Data dewhitening
def data_dewhitening(self, data_in):
if self.dataWhitening:
data_out = np.zeros((len(data_in), ), dtype=int)
PN9 = np.ones((9, ), dtype=int)
for i in range(len(data_in)):
PN9n = PN9[3]^PN9[8]
poly = np.insert(PN9, 0, PN9n)
poly = np.delete(poly, 9)
data_out[i] = data_in[i]^PN9[0]
return data_out
else:
return data_in
#zero padding remover
def zero_padding_remover(self, data_in):
nPad = int((self.nBlock*(self.nPsdu/2.0))-(8*self.phyPacketSize+6))
self.nPad = nPad
return data_in[:-nPad]
#PLL : I don't use this software PLL
def phase_loop(self, data_in):
phi_ = np.zeros((len(data_in),), dtype = complex)
phi = 0
wn = 0.11
zeta = 0.707
K = 1000
t1 = K/(wn*wn)
t2 = 2*zeta/wn
b0 = (4*K/t1)*(1+0.5*t2)
b1 = 8*K/t1
b2 = (4*K/t1)*(1-0.5*t2)
a1 = -2.0
a2 = 1.0
v0 = 0
v1 = 0
v2 = 0
diff = []
for i in range(len(data_in)):
delta = phase(data_in[i]*np.conj(exp(1j*phi)))
diff.append(delta)
#print str(i) +' Phi estimate ' + str(phi) + ' Error ' + str(delta)
v2 = v1
v1 = v0
v0 = delta - v1*a1 - v2*a2
phi = v0*b0 + v1*b1 + v2*b2
phi_[i] = exp(1j*phi)
return [phi_, diff]