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https://github.com/hb9fxq/gr-digitalhf
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data-aided frequency offset estimation
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@ -39,19 +39,9 @@ class PhysicalLayer(object):
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print('-------------------- get_doppler --------------------',self._counter)
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doppler = 0
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if self._counter == 0: ## preamble
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corr = s*np.conj(self._preamble[0]['symb'])
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self._preamble_phases.extend([np.angle(np.sum(corr))])
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if len(self._preamble_phases) == 2 and False:
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doppler = 2*(self._preamble_phases[1] - self._preamble_phases[0])/256
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print('preamble_phases', self._preamble_phases, 'doppler', doppler)
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self._preamble_phases = self._preamble_phases[1:]
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else:
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phases = np.unwrap(np.angle(corr))
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doppler = 2*(np.median(phases[-20:]) - np.median(phases[:20]))/80
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print('doppler', doppler,self._preamble_phases)
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doppler = PhysicalLayer.data_aided_frequency_estimation(s, self._preamble[0]['symb'])
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self._counter = (self._counter+1)&1
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return [True, doppler]
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return [True, 2*doppler]
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@staticmethod
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def get_preamble():
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@ -94,3 +84,20 @@ class PhysicalLayer(object):
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c['points'] = np.exp(2*np.pi*1j*np.array(range(n))/n)
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c['symbols'] = gray_code
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return c
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@staticmethod
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def data_aided_frequency_estimation(x,c):
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"""Data-Aided Frequency Estimation for Burst Digital Transmission,
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Umberto Mengali and M. Morelli, IEEE TRANSACTIONS ON COMMUNICATIONS,
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VOL. 45, NO. 1, JANUARY 1997"""
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z = x*np.conj(c) ## eq (2)
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L0 = len(z)
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N = L0//2
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R = np.zeros(N, dtype=np.complex64)
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for i in range(N):
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R[i] = 1.0/(L0-i)*np.sum(z[i:]*np.conj(z[0:L0-i])) ## eq (3)
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m = np.array(range(N), dtype=np.float)
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w = 3*((L0-m)*(L0-m+1)-N*(L0-N))/(N*(4*N*N - 6*N*L0 + 3*L0*L0-1)) ## eq (9)
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mod_2pi = lambda x : np.mod(x-np.pi, 2*np.pi) - np.pi
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fd = np.sum(w[1:] * mod_2pi(np.diff(np.angle(R)))) ## eq (8)
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return fd
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