mirror of
https://github.com/hb9fxq/gr-digitalhf
synced 2024-12-22 23:19:59 +00:00
209 lines
7.9 KiB
Python
209 lines
7.9 KiB
Python
## -*- python -*-
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import numpy as np
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import common
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from digitalhf.digitalhf_swig import viterbi27
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class Deinterleaver(object):
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"S4285 deinterleaver"
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def __init__(self, incr):
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self._dtype = np.float32
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## incr = 12 -> L
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## incr = 1 -> S
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self._buf = [np.zeros(incr*(31-i) + 1, dtype=self._dtype)
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for i in range(32)]
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def push(self, a):
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assert(len(a) == 32)
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for i in range(32):
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self._buf[i][0] = a[i]
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self._buf[i] = np.roll(self._buf[i],1)
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return self.fetch()
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def fetch(self):
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return np.array([self._buf[(9*i)%32][0] for i in range(32)],
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dtype=self._dtype)
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## ---- constellatios -----------------------------------------------------------
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BPSK=np.array(zip(np.exp(2j*np.pi*np.arange(2)/2), [0,1]), common.CONST_DTYPE)
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QPSK=np.array(zip(np.exp(2j*np.pi*np.arange(4)/4), [0,1,3,2]), common.CONST_DTYPE)
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PSK8=np.array(zip(np.exp(2j*np.pi*np.arange(8)/8), [0,1,3,2,6,7,5,4]), common.CONST_DTYPE)
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## ---- constellation indices ---------------------------------------------------
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MODE_BPSK=0
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MODE_QPSK=1
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MODE_8PSK=2
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MODES = { ## [BPS]['const'] [BPS]['punct'] [BPS]['repeat']
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'2400': {'const': MODE_8PSK, 'repeat': 1, 'deintl_multiple': 4},
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'1200': {'const': MODE_QPSK, 'repeat': 1, 'deintl_multiple': 2},
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'600': {'const': MODE_BPSK, 'repeat': 1, 'deintl_multiple': 1},
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'300': {'const': MODE_BPSK, 'repeat': 2, 'deintl_multiple': 1},
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'150': {'const': MODE_BPSK, 'repeat': 4, 'deintl_multiple': 1},
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'75': {'const': MODE_BPSK, 'repeat': 8, 'deintl_multiple': 1}
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}
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DEINTERLEAVER_INCR = { 'S': 1, 'L': 12 }
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class PhysicalLayer(object):
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"""Physical layer description for STANAG 4285"""
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def __init__(self, sps):
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"""intialization"""
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self._sps = sps
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self._frame_counter = 0
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self._is_first_frame = True
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self._constellations = [BPSK,QPSK,PSK8]
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self._preamble = self.get_preamble()
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self._data = self.get_data()
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self._viterbi_decoder = viterbi27(0x6d, 0x4f)
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self._mode_description = None
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self._frame_counter = -1
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self._fault_counter = 0
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def set_mode(self, mode):
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"""set modulation and interleaver: 'BPS/S' or 'BPS/L'"""
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self._mode_description = mode
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bps,intl = mode.split('/')
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self._mode = MODES[bps]['const']
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self._deinterleaver = Deinterleaver(DEINTERLEAVER_INCR[intl] * MODES[bps]['deintl_multiple'])
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self._depuncturer = common.Depuncturer(repeat = MODES[bps]['repeat'])
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self._repeat = MODES[bps]['repeat']
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self._fault_counter = 0
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def get_mode(self):
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return self._mode_description
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def get_constellations(self):
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return self._constellations
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def get_next_frame(self, symbols):
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"""returns a tuple describing the frame:
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[0] ... known+unknown symbols and scrambling
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[1] ... modulation type after descrambling
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[2] ... a boolean indicating if the processing should continue
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[3] ... a boolean indicating if the soft decision for the unknown symbols are saved"""
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if len(symbols) == 0: ## 1st preamble
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self._frame_counter = 0
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success,frame_description = True,[]
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if (self._frame_counter%2) == 0: ## current frame is a data frame
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frame_description = [self._preamble,MODE_BPSK,success,False]
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else: ## current frame is a preamble frame
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idx = range(30,80)
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idx = range(50)
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z = symbols[idx]*np.conj(self._preamble['symb'][idx])
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mean_z = np.mean(z)
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if np.sum(np.real(z)<0) < 30 and np.real(mean_z) > np.abs(np.imag(mean_z)) and np.real(mean_z) > 0.3:
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self._fault_counter -= 1
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else:
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self._fault_counter += 1
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self._fault_counter = min(11, max(0, self._fault_counter))
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success = self._fault_counter < 10
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if not success:
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self._frame_counter = -2
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self._fault_counter = 0
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frame_description = [self._data,self._mode,success,True]
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self._frame_counter += 1
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return frame_description
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def get_doppler(self, iq_samples):
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r = {'success': False, ## -- quality flag
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'use_amp_est': self._frame_counter < 0,
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'doppler': 0} ## -- doppler estimate (rad/symb)
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if len(iq_samples) == 0:
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return r
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sps = self._sps
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zp = np.array([x for x in self._preamble['symb'][9:40]
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for _ in range(sps)], dtype=np.complex64)
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cc = np.correlate(iq_samples, zp)
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imax = np.argmax(np.abs(cc[0:18*sps]))
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pks = cc[(imax,imax+31*sps),]
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tpks = cc[imax+15*sps:imax+16*sps]
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r['success'] = bool(np.mean(np.abs(pks)) > 5*np.mean(np.abs(tpks)))
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r['doppler'] = np.diff(np.unwrap(np.angle(pks)))[0]/31/self._sps if r['success'] else 0
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return r
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def get_preamble_z(self):
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"""preamble symbols for preamble correlation"""
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a = PhysicalLayer.get_preamble()
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return 2,np.array([z for z in a['symb'][0:31] for _ in range(self._sps)])
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def decode_soft_dec(self, soft_dec):
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n = len(soft_dec)
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quality_correction = 4.0/3.5 if n==384 else 1.0
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deintl = lambda x: np.concatenate([self._deinterleaver.push(x[i:i+32]) for i in range(0,len(x),32)])
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rd = self._derepeat(deintl(self._depuncture(soft_dec)))
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decoded_bits = self._viterbi_decoder.udpate(rd.tolist())
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quality = 100.0*self._viterbi_decoder.quality()/(2*len(decoded_bits))*quality_correction
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return decoded_bits,quality
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def _derepeat(self, soft_dec):
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if self._repeat == 1:
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return soft_dec
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n = len(soft_dec)
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m = n//(2*self._repeat)
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u = soft_dec.reshape(m, 2*self._repeat)
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for i in range(1,self._repeat):
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u[:,0] += u[:,2*i]
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u[:,1] += u[:,2*i+1]
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return np.reshape(u[:,0:2], 2*m)
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def _depuncture(self, soft_dec):
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if len(soft_dec) != 384:
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return soft_dec
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else:
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u = np.zeros(512, dtype=soft_dec.dtype)
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u[0::4] = soft_dec[0::3]
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u[1::4] = soft_dec[1::3]
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u[2::4] = soft_dec[2::3]
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u[3::4] = 0.0 ## puncture
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return u
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@staticmethod
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def get_preamble():
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"""preamble symbols + scrambler(=1)"""
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state = np.array([1,1,0,1,0], dtype=np.bool)
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taps = np.array([0,0,1,0,1], dtype=np.bool)
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p = np.zeros(80, dtype=np.uint8)
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for i in range(80):
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p[i] = state[-1]
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state = np.concatenate(([np.sum(state&taps)&1], state[0:-1]))
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a = np.zeros(80, common.SYMB_SCRAMBLE_DTYPE)
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## BPSK modulation
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constellation = PhysicalLayer.make_psk(2,range(2))['points']
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a['symb'] = constellation[p,]
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a['scramble'] = 1
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return a
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@staticmethod
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def get_data():
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"""data symbols + scrambler; for unknown symbols 'symb'=0"""
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state = np.array([1,1,1,1,1,1,1,1,1], dtype=np.bool)
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taps = np.array([0,0,0,0,1,0,0,0,1], dtype=np.bool)
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p = np.zeros(176, dtype=np.uint8)
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for i in range(176):
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p[i] = np.sum(state[-3:]*[4,2,1])
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for _ in range(3):
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state = np.concatenate(([np.sum(state&taps)&1], state[0:-1]))
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a = np.zeros(176, common.SYMB_SCRAMBLE_DTYPE)
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## 8PSK modulation
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constellation = PhysicalLayer.make_psk(8,range(8))['points']
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a['scramble'] = constellation[p,]
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known_symbols = np.mod(range(176),48)>=32
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a['symb'][known_symbols] = a['scramble'][known_symbols]
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return a
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@staticmethod
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def make_psk(n, gray_code):
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"""generates n-PSK constellation data"""
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c = np.zeros(n, common.CONST_DTYPE)
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c['points'] = np.exp(2*np.pi*1j*np.arange(n)/n)
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c['symbols'] = gray_code
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return c
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