def lut_bootstrap(b, new_L):
global L, _lut, M, s, M_L, m
M = b.size-1
if L is None:
fn = lambda a: util.shiftin(remainder1(a, b)[::-1], M)[0]
else:
fn = lambda a: remainder5(a, True)
lut = np.empty(1<<new_L, int)
for i in xrange(lut.size):
lut[i] = fn(np.r_[util.shiftout(np.r_[i], new_L)[::-1], np.zeros(M, int)])
_lut = lut
L = new_L
s = M-L
M_L = M/L
m = (1<<M)-1
def remainder5(a, no_shift_out=False):
if a.size % L:
a = np.r_[a[::-1], np.zeros(-a.size%L, int)]
else:
a = a[::-1]
a = util.shiftin(a, L)[::-1]
A = a.size
rf = np.zeros(1, np.uint32)
code = """
uint32_t r = 0;
for (int i=0; i<A; i++)
r = ((r << L) & m) ^ a(i) ^ _lut(r >> s);
rf(0) = r;
"""
weave.inline(code, ['A', 'rf', 'L', 'm', 'a', '_lut', 's'], type_converters=converters.blitz)
if no_shift_out:
return rf[0]
else:
return (rf[0] >> np.arange(M)[::-1]) & 1
def decode(self, input, visualize=False, deferVisualization=False):
results = []
drawingCalls = None if not visualize else []
endIndex = 0
working_buffer = np.empty_like(input)
minSize = ofdm.format.preambleLength + ofdm.format.ncp + ofdm.format.nfft
for startIndex in self.synchronize(input):
if startIndex < endIndex:
# we already successfully decoded this packet
continue
synchronized_input = input[startIndex:]
working_buffer[:synchronized_input.size] = synchronized_input
working_buffer = working_buffer[:synchronized_input.size]
if working_buffer.size <= minSize:
continue
training_results = self.train(working_buffer)
if training_results is None:
continue
training_data, used_samples_training, lsnr = training_results
llr, length_bits, used_samples_data = self.demodulate(
working_buffer[used_samples_training:], training_data,
drawingCalls)
if llr is None:
continue
output_bits = self.decodeFromLLR(llr, length_bits)
if not crc.checkFCS(output_bits[16:]):
continue
payload = util.shiftin(output_bits[16:-32], 8)
endIndex = startIndex + used_samples_training + used_samples_data
result = payload, startIndex, endIndex, lsnr
results.append(result)
drawFunc = None
if visualize:
def drawFunc():
for fn in drawingCalls:
fn()
if not deferVisualization:
drawFunc()
drawFunc = None
return results, drawFunc
def decode(input, visualize=False, deferVisualization=False):
results = []
drawingCalls = None if not visualize else []
endIndex = 0
working_buffer = np.empty_like(input)
minSize = ofdm.format.preambleLength + ofdm.format.ncp + ofdm.format.nfft
for startIndex in synchronize(input):
if startIndex < endIndex:
# we already successfully decoded this packet
continue
synchronized_input = input[startIndex:]
working_buffer[:synchronized_input.size] = synchronized_input
working_buffer = working_buffer[:synchronized_input.size]
if working_buffer.size <= minSize:
continue
training_results = train(working_buffer)
if training_results is None:
continue
training_data, used_samples_training, lsnr = training_results
llr, length_bits, used_samples_data = demodulate(working_buffer[used_samples_training:], training_data, drawingCalls)
if llr is None:
continue
output_bits = decodeFromLLR(llr, length_bits)
if not crc.checkFCS(output_bits[16:]):
continue
payload = util.shiftin(output_bits[16:-32], 8)
endIndex = startIndex + used_samples_training + used_samples_data
result = payload, startIndex, endIndex, lsnr
results.append(result)
drawFunc = None
if visualize:
def drawFunc():
for fn in drawingCalls:
fn()
if not deferVisualization:
drawFunc()
drawFunc = None
return results, drawFunc
def encode(interleaved_bits, rate):
return rate.constellation[util.shiftin(interleaved_bits, rate.Nbpsc)]
while input.size-j > nfft and i <= length_symbols:
sym = np.fft.fft(input[j:j+nfft])*G
data = sym[ofdm.format.dataSubcarriers]
pilots = sym[ofdm.format.pilotSubcarriers] * next(pilotPolarity) * ofdm.format.pilotTemplate
kalman_u = kalman_state.update(np.sum(pilots))
data *= kalman_u
pilots *= kalman_u
if i==0: # signal
signal_bits = data.real>0
signal_bits = interleaver.interleave(signal_bits, ofdm.format.Nsc, 1, reverse=True)
scrambled_plcp_estimate = code.decode(signal_bits*2-1, 18)
plcp_estimate = scrambler.scramble(scrambled_plcp_estimate, int(ofdm.format.Nsc*.5), scramblerState=0)
parity = (np.sum(plcp_estimate) & 1) == 0
if not parity:
return None, None, 0
plcp_estimate = util.shiftin(plcp_estimate[:18], 18)[0]
try:
encoding_estimate = util.rev(plcp_estimate & 0xF, 4)
rate_estimate = [r.encoding == encoding_estimate for r in wifi_802_11_rates].index(True)
except ValueError:
return None, None, 0
r_est = wifi_802_11_rates[rate_estimate]
Nbpsc, constellation_estimate = r_est.Nbpsc, r_est.constellation
Ncbps, Nbps = r_est.Ncbps, r_est.Nbps
length_octets = (plcp_estimate >> 5) & 0xFFF
length_bits = length_octets * 8
length_coded_bits = (length_bits+16+6)*2
length_symbols = (length_coded_bits+Ncbps-1) // Ncbps
signal_bits = code.encode(scrambled_plcp_estimate)
dispersion = data - qam.bpsk.symbols[interleaver.interleave(signal_bits, ofdm.format.Nsc, 1)]
dispersion = np.var(dispersion)
