mirror of
https://github.com/romanz/amodem.git
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156 lines
4.4 KiB
Python
156 lines
4.4 KiB
Python
import numpy as np
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import pylab
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import logging
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import functools
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import itertools
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logging.basicConfig(level=0, format='%(message)s')
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log = logging.getLogger(__name__)
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import sigproc
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import loop
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import show
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from common import *
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COHERENCE_THRESHOLD = 0.95
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CARRIER_DURATION = 300
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CARRIER_THRESHOLD = int(0.95 * CARRIER_DURATION)
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def detect(x, freq):
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counter = 0
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for offset, buf in iterate(x, Nsym, advance=Nsym):
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coeff = sigproc.coherence(buf, Fc)
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if abs(coeff) > COHERENCE_THRESHOLD:
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counter += 1
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else:
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counter = 0
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if counter == CARRIER_THRESHOLD:
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length = CARRIER_THRESHOLD * Nsym
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return offset - length + Nsym, offset
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def find_start(x, start):
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WINDOW = Nsym * 10
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length = CARRIER_DURATION * Nsym
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begin, end = start - WINDOW, start + length + WINDOW
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x_ = x[begin:end]
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Hc = sigproc.exp_iwt(Fc, len(x_))
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P = np.abs(Hc.conj() * x_) ** 2
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cumsumP = P.cumsum()
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start = begin + np.argmax(cumsumP[length:] - cumsumP[:-length])
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log.info('Carrier starts at {:.3f} ms'.format(start * Tsym * 1e3 / Nsym))
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return start
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def extract_symbols(x, freq, offset=0):
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Hc = sigproc.exp_iwt(-freq, Nsym) / (0.5*Nsym)
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func = lambda y: np.dot(Hc, y)
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for _, symbol in iterate(x, Nsym, advance=Nsym, func=func):
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yield symbol
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def demodulate(x, freq, filt, plot=None):
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S = extract_symbols(x, freq) # samples -> symbols
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S = np.array(list(filt(S))) # apply equalizer
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if plot:
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plot()
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show.constellation(S, title='$F_c = {} kHz$'.format(freq / 1e3))
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for bits in sigproc.modulator.decode(S): # list of bit tuples
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yield bits
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def receive(x, freqs):
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x = iter(x)
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prefix = [1]*300 + [0]*100
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S = itertools.islice(extract_symbols(x, Fc), len(prefix))
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S = np.array(list(S))
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bits = np.round(np.abs(S))
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bits = np.array(bits, dtype=int)
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if all(bits != prefix):
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return None
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log.info('Prefix OK')
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filters = {}
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full_scale = len(freqs)
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training_bits = np.array(([1]*10 + [0]*10)*20 + [0]*100)
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expected = full_scale * training_bits
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for freq in freqs:
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S = list(itertools.islice(extract_symbols(x, freq), len(expected)))
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filt = sigproc.train(S, expected)
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filters[freq] = filt
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S = list(filt(S))
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y = np.array(S).real
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train_result = y > 0.5 * full_scale
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if not all(train_result == training_bits):
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pylab.plot(y, '-', expected, '-')
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return None
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noise = y - expected
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Pnoise = sigproc.power(noise)
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log.debug('{:10.1f}Hz: Noise sigma={:.4f}, SNR={:.1f} dB'.format( freq, Pnoise**0.5, 10*np.log10(1/Pnoise) ))
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sz = int(np.ceil(np.sqrt(len(freqs))))
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streams = []
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xs = itertools.tee(x, len(freqs))
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for i, (x, freq) in enumerate(zip(xs, freqs)):
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stream = demodulate(x, freq=freq, filt=filters[freq],
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plot=functools.partial(pylab.subplot, sz, sz, i+1))
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streams.append(stream)
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bitstream = []
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for block in itertools.izip(*streams):
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for bits in block:
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bitstream.extend(bits)
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return bitstream
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def main(fname):
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_, x = load(open(fname, 'rb'))
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result = detect(x, Fc)
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if result is None:
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log.info('No carrier detected')
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return
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begin, end = result
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x_ = x[begin:end]
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Hc = sigproc.exp_iwt(-Fc, len(x_))
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Zc = np.dot(Hc, x_) / (0.5*len(x_))
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amp = abs(Zc)
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log.info('Carrier detected at ~{:.1f} ms @ {:.1f} kHz: coherence={:.3f}%, amplitude={:.3f}'.format(
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begin * Tsym * 1e3 / Nsym, Fc / 1e3, abs(sigproc.coherence(x_, Fc)) * 100, amp
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))
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start = find_start(x, begin)
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x = x[start:]
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peak = np.max(np.abs(x))
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if peak > SATURATION_THRESHOLD:
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raise ValueError('Saturation detected: {:.3f}'.format(peak))
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data_bits = receive(x / amp, frequencies)
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if data_bits is None:
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log.info('Cannot demodulate symbols!')
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else:
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import ecc
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data = iterate(data_bits, bufsize=8, advance=8, func=to_byte)
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data = ''.join(c for _, c in data)
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data = ecc.decode(data)
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if data is None:
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log.warning('No blocks decoded!')
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return
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with file('data.recv', 'wb') as f:
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f.write(data)
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if __name__ == '__main__':
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main('rx_.int16')
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import os
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if os.environ.get('SHOW') is not None:
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pylab.show()
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