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https://github.com/hb9fxq/gr-digitalhf
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almost complete description of 188-110 App C
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cmayer
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39a8426822
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9298637d69
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@ -97,11 +97,36 @@ REINSERTED_PREAMBLE=n_psk(8, np.array(
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6,
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4,4,4,4,4,6,0,2,4,0,4,0,4,2,0,6,4,4,4,4,4,6,0,2,4,0,4,0,4,2,0])) ## MP-
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## length 31
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MINI_PROBE_PLUS=n_psk(8, np.array(
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[0,0,0,0,0,2,4,6,0,4,0,4,0,6,4,2,0,0,0,0,0,2,4,6,0,4,0,4,0,6,4]))
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## length 31
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MINI_PROBE_MINUS=n_psk(8, np.array(
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[4,4,4,4,4,6,0,2,4,0,4,0,4,2,0,6,4,4,4,4,4,6,0,2,4,0,4,0,4,2,0]))
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MINI_PROBE=[n_psk(8, np.array([0,0,0,0,0,2,4,6,0,4,0,4,0,6,4,2,0,0,0,0,0,2,4,6,0,4,0,4,0,6,4])), ## sign = + (0)
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n_psk(8, np.array([4,4,4,4,4,6,0,2,4,0,4,0,4,2,0,6,4,4,4,4,4,6,0,2,4,0,4,0,4,2,0]))] ## sign = - (1)
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## ---- di-bits ----------------------------------------------------------------
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TO_DIBIT=[(0,0),(0,1),(1,1),(1,0)]
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## ---- rate -------------------------------------------------------------------
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TO_RATE={(0,0,0): {'baud': 0, 'bits_per_symbol': 0}, ## reserved
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(0,0,1): {'baud': 3200, 'bits_per_symbol': 2, 'ci': MODE_QPSK},
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(0,1,0): {'baud': 4800, 'bits_per_symbol': 3, 'ci': MODE_8PSK},
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(0,1,1): {'baud': 6400, 'bits_per_symbol': 4, 'ci': MODE_16QAM},
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(1,0,0): {'baud': 8000, 'bits_per_symbol': 5, 'ci': MODE_32QAM},
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(1,0,1): {'baud': 9600, 'bits_per_symbol': 6, 'ci': MODE_64QAM},
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(1,1,0): {'baud':12800, 'bits_per_symbol': 6, 'ci': MODE_64QAM},
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(1,1,1): {'baud': 0, 'bits_per_symbol': 0}} ## reserved
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## ---- interleaver ------------------------------------------------------------
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TO_INTERLEAVER={(0,0,0): {'frames': -1, 'name': 'illegal'},
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(0,0,1): {'frames': 1, 'name': 'Ultra Short (US)'},
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(0,1,0): {'frames': 3, 'name': 'Very Short (VS)'},
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(0,1,1): {'frames': 9, 'name': 'Short (S)'},
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(1,0,0): {'frames': 18, 'name': 'Medium (M)'},
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(1,0,1): {'frames': 36, 'name': 'Long (L)'},
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(1,1,0): {'frames': 72, 'name': 'very Long (VL)'},
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(1,1,1): {'frames': -1, 'name': 'illegal'}}
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MP_COUNTER=[(0,0,1),
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(0,1,0),
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(0,1,1),
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(1,0,0)]
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## ---- physcal layer class -----------------------------------------------------
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class PhysicalLayer(object):
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@ -113,7 +138,6 @@ class PhysicalLayer(object):
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self._frame_counter = -1
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self._constellations = [BPSK, QPSK, PSK8, QAM16, QAM32, QAM64]
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self._preamble = self.get_preamble()
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self._scr_data = ScrambleData()
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def get_constellations(self):
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return self._constellations
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@ -129,14 +153,15 @@ class PhysicalLayer(object):
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self._frame_counter)
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## --- preamble frame ----
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if self._frame_counter == -1:
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self._preamble_offset = 0
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return [self._preamble,MODE_BPSK,True,False]
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## ----- (re)inserted preamble ------
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if self._frame_counter == 0:
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self.a = self.make_reinserted_preamble()
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self.a = self.make_reinserted_preamble(self._preamble_offset)
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return [self.a, MODE_QPSK,False,False]
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if self._frame_counter >= 1:
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self.a = self.make_data_frame()
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return [self.a, MODE_64QAM,False,True]
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return [self.a, self._constellation_index,False,True]
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def get_doppler(self, symbols, iq_samples):
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"""returns a tuple
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@ -153,12 +178,38 @@ class PhysicalLayer(object):
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for s in symbols:
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print(s)
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self._frame_counter = 0
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elif self._frame_counter >= 0 and self._frame_counter <5: ## -- reinserted preamble ----
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for s in symbols:
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print(s)
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elif self._frame_counter == 0: ## -- reinserted preamble ----
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## decode D0,D1,D2
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idx = np.arange(13)
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z = np.array([np.mean(symbols[32+13*i+idx]) for i in range(3)])
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d0d1d2 = map(np.uint8, np.mod(np.round(np.angle(z)/np.pi*2),4))
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dibits = [TO_DIBIT[idx] for idx in d0d1d2]
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self._mode = {'rate': tuple([x[0] for x in dibits]),
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'interleaver': tuple([x[1] for x in dibits])}
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print('======== rate,interleaver:',
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TO_RATE[self._mode['rate']],
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TO_INTERLEAVER[self._mode['interleaver']])
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rate_info = TO_RATE[self._mode['rate']]
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self._constellation_index = rate_info['ci']
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print('constellation index', self._constellation_index)
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scr = ScrambleData()
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iscr = [scr.next(rate_info['bits_per_symbol']) for _ in range(256)]
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if rate_info['ci'] > MODE_8PSK:
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self._data_scramble = np.ones(256, dtype=np.complex64)
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else:
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constell = self._constellations[rate_info['ci']]
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self._data_scramble = constell[iscr]
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self._frame_counter += 1
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success = True
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else: ## ------------------------ data frame ----
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elif self._frame_counter <=72: ## -- data -------------------
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print(np.abs(symbols[:16]), symbols[-31:], np.mean(symbols[-31:]))
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success = np.abs(np.mean(symbols[-31:])) > 0.5
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if success:
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self._frame_counter += 1
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else:
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self._frame_counter = -1
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else: ## ------------------------ re-inserted preamble -------
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## TODO
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for s in symbols:
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print(s)
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success = False
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@ -188,19 +239,28 @@ class PhysicalLayer(object):
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print('success=', success, 'doppler=', doppler)
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return success,doppler
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def make_reinserted_preamble(self):
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a=np.array(zip(REINSERTED_PREAMBLE,
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REINSERTED_PREAMBLE),
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def make_reinserted_preamble(self, offset):
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""" offset= 0 -> 1st reinserted preamble
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offset=-72 -> all following reinserted preambles"""
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a=np.array(zip(REINSERTED_PREAMBLE[offset:],
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REINSERTED_PREAMBLE[offset:]),
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dtype=[('symb', np.complex64),
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('scramble', np.complex64)])
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a['symb'][32:32+3*13] = 0 ## D0,D1,D2
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a['symb'][-72:-72+3*13] = 0 ## D0,D1,D2
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return a
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def make_data_frame(self):
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a=np.zeros(256+31, dtype=[('symb', np.complex64),
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('scramble', np.complex64)])
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a['scramble'] = 1
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a['symb'][256:] = MINI_PROBE_MINUS
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a['scramble'][256:] = MINI_PROBE_MINUS
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self._preamble_offset = -72 ## all following reinserted preambles start at index -72
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a=np.zeros(256+31, dtype=[('symb', np.complex64),
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('scramble', np.complex64)])
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a['scramble'][:256] = self._data_scramble
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n = self._frame_counter -1
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m = n%18
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if m == 0:
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cnt = n//18
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self._mp = (1,1,1,1,1,1,1,0)+self._mode['rate']+self._mode['interleaver']+MP_COUNTER[cnt]+(0,)
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print('new mini-probe signs n=',n,'m=',m,self._mp)
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a['symb'][256:] = MINI_PROBE[self._mp[m]]
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a['scramble'][256:] = MINI_PROBE[self._mp[m]]
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return a
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@staticmethod
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