def __init__(self, options):
ofdm = ofdm_rxtx.TX(options)
qam = raw.qam_tx(options.bitrate, ofdm.params.data_tones, ofdm.size, log=options.log)
framebytes = qam.framebytes
if options.crc:
framebytes = 188
gr.hier_block2.__init__(self, "TX",
gr.io_signature(1,1, gr.sizeof_char * framebytes),
gr.io_signature(1,1, gr.sizeof_gr_complex))
qam_in = gr.vector_to_stream(gr.sizeof_char, qam.framebytes)
if options.crc:
self.connect(self,
raw.crc_enc(framebytes),
gr.vector_to_stream(gr.sizeof_char, framebytes + 4),
qam)
else:
self.connect(self,
gr.vector_to_stream(gr.sizeof_char, qam.framebytes),
qam)
self.connect(qam,
gr.stream_to_vector(gr.sizeof_gr_complex, ofdm.params.data_tones),
ofdm,
self)
self.ofdm = ofdm
self.qam = qam
self.framebytes = framebytes
def setup_flowgraph(self):
options = self.options
# Attempt to enable realtime scheduling
if options.realtime:
r = gr.enable_realtime_scheduling()
if r == gr.RT_OK:
options.realtime = True
print >> sys.stderr, "Realtime scheduling ENABLED"
else:
options.realtime = False
print >> sys.stderr, "Realtime scheduling FAILED"
self.setup_timing()
# Setup our input source
if options.inputfile:
self.using_usrp = False
print >> sys.stderr, "Reading data from: " + options.inputfile
self.source = gr.file_source(gr.sizeof_gr_complex,
options.inputfile, options.fileloop)
else:
self.using_usrp = True
self.setup_usrp()
self.setup_filter()
#create a tuner callback
self.mean_offset = 0.0 #this is set by tuner callback
self.burst_cb = burst_callback(self)
# Setup flow based on decoder selection
# if options.decoder.count("c"):
self.setup_c_flowgraph()
# elif options.decoder.count("f"):
# self.setup_f_flowgraph()
self.configure_burst_decoder()
#Hookup a vector-stream converter if we want burst output
if self.scopes.count("b") or options.outputfile:
self.v2s = gr.vector_to_stream(
gr.sizeof_float, 142) #burst output is 142 (USEFUL_BITS)
self.connect(self.burst, self.v2s)
else:
self.burst_sink = gr.null_sink(gr.sizeof_float)
self.v2s = gr.vector_to_stream(
gr.sizeof_float, 142) #burst output is 142 (USEFUL_BITS)
self.connect(self.burst, self.v2s)
self.connect(self.v2s, self.burst_sink)
#Output file
if options.outputfile:
self.filesink = gr.file_sink(gr.sizeof_float, options.outputfile)
self.connect(self.v2s, self.filesink)
def setup_flowgraph(self):
options = self.options
# Attempt to enable realtime scheduling
if options.realtime:
r = gr.enable_realtime_scheduling()
if r == gr.RT_OK:
options.realtime = True
print >> sys.stderr, "Realtime scheduling ENABLED"
else:
options.realtime = False
print >> sys.stderr, "Realtime scheduling FAILED"
self.setup_timing()
# Setup our input source
if options.inputfile:
self.using_usrp = False
print >> sys.stderr, "Reading data from: " + options.inputfile
self.source = gr.file_source(gr.sizeof_gr_complex, options.inputfile, options.fileloop)
else:
self.using_usrp = True
#self.setup_usrp()
self.setup_filter()
#create a tuner callback
self.mean_offset = 0.0 #this is set by tuner callback
self.burst_cb = burst_callback(self)
# Setup flow based on decoder selection
# if options.decoder.count("c"):
self.setup_c_flowgraph()
# elif options.decoder.count("f"):
# self.setup_f_flowgraph()
self.configure_burst_decoder()
#Hookup a vector-stream converter if we want burst output
if self.scopes.count("b") or options.outputfile:
self.v2s = gr.vector_to_stream(gr.sizeof_float,142) #burst output is 142 (USEFUL_BITS)
self.connect(self.burst, self.v2s)
else:
self.burst_sink = gr.null_sink(gr.sizeof_float)
self.v2s = gr.vector_to_stream(gr.sizeof_float,142) #burst output is 142 (USEFUL_BITS)
self.connect(self.burst, self.v2s)
self.connect(self.v2s, self.burst_sink)
#Output file
if options.outputfile:
self.filesink = gr.file_sink(gr.sizeof_float, options.outputfile)
self.connect(self.v2s, self.filesink)
def test_001(self):
frames = 5
config = station_configuration()
config.subcarriers = 12
config.data_subcarriers = 8
config.training_data = dummy()
config.training_data.shifted_pilot_tones = [1,4,8,11]
data = [1.0] * config.subcarriers
for x in config.training_data.shifted_pilot_tones:
data[x] = 2.0
data = concatenate([data]*frames)
ref = [1.0]*(config.data_subcarriers*frames)
src = gr.vector_source_c(data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex,config.subcarriers)
dst = gr.vector_sink_c()
v2s = gr.vector_to_stream(gr.sizeof_gr_complex,config.data_subcarriers)
uut = preambles.pilot_subcarrier_filter()
self.fg.connect(src,s2v,uut,v2s,dst)
self.fg.run()
self.assertEqual(ref,list(dst.data()))
def setUp (self):
#print os.getpid()
#raw_input("press the any key")
self.tb = gr.top_block ()
offset = 43223 #sample15 = 21839 #sample20 = 43223
fftl = 512
cpl = 144*fftl/2048
cpl0 = 160*fftl/2048
slotl = 7*fftl+6*cpl+cpl0
cell_id = 124
N_rb_dl = 6
mod=scipy.io.loadmat('/home/demel/exchange/matlab_test_first_freq.mat')
mat_u1=tuple(mod['test'].flatten())
mat_d=range(len(mat_u1))
for idx, val in enumerate(mat_u1):
mat_d[idx]=val
intu=tuple(mat_d[0:slotl*60])
self.src = gr.vector_source_c(intu,False,1)
self.tag = lte.tag_symbol_cc(offset,fftl)
#self.head = gr.head(gr.sizeof_gr_complex,70000)
self.sel = lte.sss_selector_cvc(fftl)
self.vtos = gr.vector_to_stream(gr.sizeof_gr_complex,512)
self.snk = gr.vector_sink_c(1)
self.tb.connect(self.src,self.tag,self.sel,self.vtos,self.snk)#,self.head
def test_014_bonder_vbb(self):
#################################
src_data_0 = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
################################
expected_result_0 = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
#################################
# Objekte erzeugen
src_0 = gr.vector_source_f(src_data_0)
throttle_0 = gr.throttle(gr.sizeof_float * 1, 320000)
s2v_0 = gr.stream_to_vector(gr.sizeof_float, 2)
bonder = howto_swig.bonder_vff(2, 6)
v2s_0 = gr.vector_to_stream(gr.sizeof_float, 6)
dst_0 = gr.vector_sink_f()
# Objekte verbinden
self.tb.connect(src_0, throttle_0, s2v_0, bonder, v2s_0, dst_0)
# Simulationsstart
self.tb.run()
# Ergebnis auswerten
result_data0 = dst_0.data()
self.assertEqual(expected_result_0, result_data0)
def test_003(self):
# Need to add padding
padding = tuple([0 for i in range(29)])
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2,) + padding + \
(3.2, 4.2, 5.5,) + padding + \
(-1.1, -2.2, -3.2,) + padding
expected_result = [0, 2, 4]
expected_result.extend(padding)
expected_result.extend([6, 8, 11])
expected_result.extend(padding)
expected_result.extend([-2, -4, -6])
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_char(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_char, vlen)
dst = gr.vector_sink_c()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_003(self):
# Need to add padding to keep proper alignment
padding = tuple([0 for i in range(5)])
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2) + padding + (3.3, 4.4, 5.5) + padding + (-1.1, -2.2, -3.3) + padding
expected_result = [0, 2, 4]
expected_result.extend(padding)
expected_result.extend([7, 9, 11])
expected_result.extend(padding)
expected_result.extend([-2, -4, -7])
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_int(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_int, vlen)
dst = gr.vector_sink_i()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_001_diff_phasor_vcc(self): a = [1+2j,2+3.5j,3.5+4j,4+5j,5+6j] b = [1j,1j,1j,1j,1j] c = [-1j+3,1j,-7+0j,2.5j+0.333,3.2j] d = [(0.35979271051026462+0.89414454782483865j), (0.19421665709046287+0.024219594550527801j), (0.12445564785882557+0.40766238899138718j), (0.041869638845043688+0.97860437393366329j), (0.068927762235083234+0.16649764877365247j)] e = [(0.16207552830286298+0.435385030608331j), (0.47195779613669675+0.37824764113272558j), (0.13911998015446148+0.6585095669811617j), (0.093510743358783954+0.98446560079828938j), (0.86036393297704694+0.72043005342024602j)] multconj = lambda x,y: x.conjugate()*y src_data = a+b+c+d+e expected_result = [0j,0j,0j,0j,0j]+map(multconj,a,b)+map(multconj,b,c)+map(multconj,c,d)+map(multconj,d,e) src = gr.vector_source_c(src_data) s2v = gr.stream_to_vector(gr.sizeof_gr_complex, 5) diff_phasor_vcc = dab_swig.diff_phasor_vcc(5) v2s = gr.vector_to_stream(gr.sizeof_gr_complex, 5) dst = gr.vector_sink_c() self.tb.connect(src, s2v, diff_phasor_vcc, v2s, dst) self.tb.run() result_data = dst.data() # print expected_result # print result_data self.assertComplexTuplesAlmostEqual(expected_result, result_data, 6)
def test_001 (self):
vlen = 128
syms = 4
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0/vlen)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
ifft = gr.fft_vcc(vlen, False, [], True)
fft_scale = gr.multiply_const_vcc([1.0/vlen]*vlen)
vec = numpy.array(numpy.zeros(vlen), numpy.complex)
vec[vlen/2-vlen/4] = 1.0
vec = concatenate([vec]*syms)
src = gr.vector_source_c(vec)
dst = gr.vector_sink_c()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, vlen)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f([0.0]*syms)
trig = gr.vector_source_b([1]*syms)
self.fg.connect(src, s2v, ifft, (freq_shift,0))
self.fg.connect(eps, (freq_shift,1))
self.fg.connect(trig, (freq_shift,2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual(vec, numpy.array(dst.data()))
def test_007(self):
vlen = 128
syms = 4
bin1 = vlen / 2 + 2
bin1_val = 1.0
expec = numpy.array(numpy.zeros(vlen), numpy.complex)
expec[bin1] = bin1_val
expec = concatenate([expec] * syms)
epsilon = [0.5]
frame_trigger = numpy.concatenate([[1], [0] * (syms - 1)])
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0 / vlen)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
fft_scale = gr.multiply_const_vcc([1.0 / vlen] * vlen)
src = gr.sig_source_c(vlen, gr.GR_COS_WAVE, 1.5, 1.0, 0.0)
# bin vlen/2 + 1.5
dst = gr.vector_sink_c()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, vlen)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f(epsilon)
trig = gr.vector_source_b(frame_trigger.tolist())
self.fg.connect(src, s2v, (freq_shift, 0))
self.fg.connect(eps, (freq_shift, 1))
self.fg.connect(trig, (freq_shift, 2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual2(expec, dst.data(), 1e-5, 1e-5)
def test_007 (self):
vlen = 128
syms = 4
bin1 = vlen/2 + 2
bin1_val = 1.0
expec = numpy.array(numpy.zeros(vlen), numpy.complex)
expec[bin1] = bin1_val
expec = concatenate([expec]*syms)
epsilon = [0.5]
frame_trigger = numpy.concatenate([[1],[0]*(syms-1)])
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0/vlen)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
fft_scale = gr.multiply_const_vcc([1.0/vlen]*vlen)
src = gr.sig_source_c(vlen, gr.GR_COS_WAVE, 1.5, 1.0, 0.0)
# bin vlen/2 + 1.5
dst = gr.vector_sink_c()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, vlen)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f(epsilon)
trig = gr.vector_source_b(frame_trigger.tolist())
self.fg.connect(src, s2v, (freq_shift,0))
self.fg.connect(eps, (freq_shift,1))
self.fg.connect(trig, (freq_shift,2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual2(expec, dst.data(), 1e-5, 1e-5)
def __init__(self, vlen, channel_block, delay):
gr.hier_block2.__init__(self, 'apply_channel_to_vect',
gr.io_signature(1, 1, gr.sizeof_gr_complex * vlen),
gr.io_signature(1, 1, gr.sizeof_gr_complex * vlen))
self.vlen=vlen
self.channel_block = channel_block
self.delay = delay
pad_len = self.vlen + self.delay*2
if(delay>0):
self.padding = gr.vector_source_c((0,)*(delay*2),True,delay*2)
self.pad_cat = mlse.vector_concat_vv(vlen*gr.sizeof_gr_complex,gr.sizeof_gr_complex*2*delay)
self.connect(self, self.pad_cat)
self.connect(self.padding, (self.pad_cat,1))
else:
self.pad_cat = self
self.tostream = gr.vector_to_stream(gr.sizeof_gr_complex, pad_len)
self.connect(self.pad_cat, self.tostream)
# connect channel
self.connect(self.tostream, self.channel_block)
self.tovector = gr.stream_to_vector(gr.sizeof_gr_complex, pad_len)
self.connect(self.channel_block, self.tovector)
# cut out the proper part
self.trim = mlse.vector_slice_vv(
gr.sizeof_gr_complex,
pad_len,
delay,
vlen)
self.connect(self.tovector, self.trim, self)
def test_004_de_diff_mod_vcc (self):
#################################
# Testsequenz generieren
src_data = (1+0j, 0+2j, 0-0j, 0+1j, 2+0j, 0+0j,-1+0j,2+0j,-0+0j)
#################################
# Ergebnis generieren
expected_result_0 = (0+0j, 0+0j, 0-0j, 0+1j, 0-4j, 0-0j, 0+1j, 4+0j, 0+0j)
expected_result_1 = (0+0j, 0-4j, 4+0j)
#################################
# Objekte erzeugen
src = gr.vector_source_c (src_data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, 3)
diff = howto_swig.de_diff_mod_vcc(3,1)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, 3)
dst0 = gr.vector_sink_c()
dst1 = gr.vector_sink_c()
# Objekte verbinden
self.tb.connect(src, s2v, (diff,0), v2s, dst0)
self.tb.connect((diff,1), dst1)
# Simulationsstart
self.tb.run ()
# Ergebnis auswerten
result_data0 = dst0.data ()
result_data1 = dst1.data ()
self.assertComplexTuplesAlmostEqual (expected_result_0, result_data0, 6)
self.assertComplexTuplesAlmostEqual (expected_result_1, result_data1, 6)
def test_001_cutter_vbb(self):
#################################
# Testsequenz generieren
src_data_0 = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
################################
# Ergebnis generieren
expected_result_0 = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
#################################
# Objekte erzeugen
src_0 = gr.vector_source_b(src_data_0)
throttle_0 = gr.throttle(gr.sizeof_char * 1, 320000)
s2v_0 = gr.stream_to_vector(gr.sizeof_char, 6)
cutter = howto_swig.cutter_vbb(6, 2)
v2s_0 = gr.vector_to_stream(gr.sizeof_char, 2)
dst_0 = gr.vector_sink_b()
self.tb.connect(src_0, throttle_0, s2v_0, cutter, v2s_0, dst_0)
self.tb.run()
result_data0 = dst_0.data()
self.assertEqual(expected_result_0, result_data0)
def helper(self, v0, v1, fft_length, preamble):
tb = self.tb
src0 = gr.vector_source_c(v0)
src1 = gr.vector_source_b(v1)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, fft_length)
# print "len(v) = %d" % (len(v))
op = gr.ofdm_insert_preamble(fft_length, preamble)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, fft_length)
dst0 = gr.vector_sink_c()
dst1 = gr.vector_sink_b()
tb.connect(src0, s2v, (op, 0))
tb.connect(src1, (op, 1))
tb.connect((op, 0), v2s, dst0)
tb.connect((op, 1), dst1)
tb.run()
r0 = dst0.data()
r0v = []
for i in range(len(r0) // fft_length):
r0v.append(r0[i * fft_length:(i + 1) * fft_length])
r1 = dst1.data()
self.assertEqual(len(r0v), len(r1))
return (r1, r0v)
def test_011_viterbi_test (self):
#################################
# Matlab Viterbi Testsequenz
src_data_0 = 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################################
# Ergebnis Matlab Viterbi Testsequenz
expected_result_0 = (0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,0,0,1,1,0,1,1,1,0,0,1,1,0,0,1,0,1,0,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,0,1,1,1,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,1,1,1,1,0,1,0,1,0,1,1,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,1,0,0,1,0,0,0,0,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,0,0,1,0,0,1,0,1,0,1,1,1,1,1,0,1,1,0,1,0,0,1,1,0,0,0,1,0,0,1,1,1,1,0,0,0,0,1,1,0,1,1,0,1,1,1,1,1,0,0,1,1,1,0,0,0,0,1,1,0,0,1,1,0,1,0,0,1,0,1,1,1,1,0,1,1,0,0,1,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,1,1,0,0,1,0,0,0,1,0,1,0,1,0,1,1,0,0,1,1,1,0,1,0,0,1,0,1,0,0,0,1,1,0,1,0,0,1,0,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,0,0,0,1,1,1,0,1,0,1,1,0,0,1,0,1,1,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,0,1,0,0,0,0,0,1,1,0,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,0,0,0,0,1,0,1,1,0,1,0,1,1,1,1,1,0,1,0,1,0,1,0,1,0,0,0,0,0,0,1,0,1,0,0,1,0,1,0,1,1,1,1,0,0,1,0,1,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,0,1,0,0,1,0,0,1,1,1,1,0,1,0,1,1,1,0,1,0,1,0,0,0,1,0,0,1,0,0,0,0,1,1,0,0,1,1,1,0,0,0,0,1,0,1,1,1,1,0,1,1,0,1,1,0,0,1,1,0,1,0,0,0,0,1,1,1,0,1,1,0,1,1,0,1,0,1,1,0,1,0,1,0,1,1,0,1,1,1,1,0,0,0,0,0,1,1,1,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,0,1,0,0,0,0,0,1,0,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,1,1,0,1,1,0,1,0,1,0,1,1,1,0,0,0,1,0,0,1,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,1,0,0,0,0,1,0,0,1,1,1,0,0,1,0,1,0,1,0,1,1,0,0,0,0,1,1,0,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,1,0,0,0,1,0,1,0,0,0,0,1,0,1,0,1,1,0,1,0,0,1,1,1,1,1,1,0,1,1,0,0,1,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,1,1,0,0,1,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,)
#################################
# Objekte erzeugen
src_0 = gr.vector_source_f (src_data_0)
throttle_0 = gr.throttle(gr.sizeof_float*1, 32000)
s2v = gr.stream_to_vector(gr.sizeof_float, 3096)
Viterbi = howto_swig.viterbi_vfb(3096)
v2s = gr.vector_to_stream(gr.sizeof_char, 3096/4)
dst_0 = gr.vector_sink_b()
# Objekte verbinden
self.tb.connect(src_0, throttle_0)
self.tb.connect(throttle_0, s2v)
self.tb.connect(s2v, Viterbi)
self.tb.connect(Viterbi, v2s)
self.tb.connect(v2s, dst_0)
# Simulationsstart
self.tb.run ()
# Ergebnis auswerten
result_data0 = dst_0.data ()
result_data0 = result_data0
expected_result_0 = expected_result_0
self.assertEqual(expected_result_0, result_data0)
def __init__(self):
gr.top_block.__init__(self)
length = 101
data_r = range(length)
data_i = range(length,2*length)
src_r = gr.vector_source_s(data_r, False)
src_i = gr.vector_source_s(data_i, False)
s2f_r = gr.short_to_float()
s2f_i = gr.short_to_float()
f2c = gr.float_to_complex()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, length)
shift = True
ifft = gr.fft_vcc(length, False, [], shift)
fft = gr.fft_vcc(length, True, [], shift)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, length)
snk_in = gr.file_sink(gr.sizeof_gr_complex, "fftshift.in")
snk_out = gr.file_sink(gr.sizeof_gr_complex, "fftshift.out")
self.connect(src_r, s2f_r, (f2c,0))
self.connect(src_i, s2f_i, (f2c,1))
self.connect(f2c, snk_in)
self.connect(f2c, s2v, ifft, fft, v2s, snk_out)
def test_004_de_diff_mod_vcc(self):
#################################
# Testsequenz generieren
src_data = (1 + 0j, 0 + 2j, 0 - 0j, 0 + 1j, 2 + 0j, 0 + 0j, -1 + 0j,
2 + 0j, -0 + 0j)
#################################
# Ergebnis generieren
expected_result_0 = (0 + 0j, 0 + 0j, 0 - 0j, 0 + 1j, 0 - 4j, 0 - 0j,
0 + 1j, 4 + 0j, 0 + 0j)
expected_result_1 = (0 + 0j, 0 - 4j, 4 + 0j)
#################################
# Objekte erzeugen
src = gr.vector_source_c(src_data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, 3)
diff = howto_swig.de_diff_mod_vcc(3, 1)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, 3)
dst0 = gr.vector_sink_c()
dst1 = gr.vector_sink_c()
# Objekte verbinden
self.tb.connect(src, s2v, (diff, 0), v2s, dst0)
self.tb.connect((diff, 1), dst1)
# Simulationsstart
self.tb.run()
# Ergebnis auswerten
result_data0 = dst0.data()
result_data1 = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result_0, result_data0, 6)
self.assertComplexTuplesAlmostEqual(expected_result_1, result_data1, 6)
def test_002_ofdm_remove_first_symbol_vcc(self):
src_data0 = (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7)
src_data1 = (1, 0, 0, 1, 0, 0)
expected_result0 = (3, 4, 5, 6, 7, 8, 2, 3, 4, 5, 6, 7)
expected_result0 = [x + 0j for x in expected_result0]
expected_result1 = (1, 0, 1, 0)
src0 = gr.vector_source_c(src_data0)
src1 = gr.vector_source_b(src_data1)
s2v0 = gr.stream_to_vector(gr.sizeof_gr_complex, 3)
ofdm_remove_first_symbol = dab_swig.ofdm_remove_first_symbol_vcc(3)
v2s0 = gr.vector_to_stream(gr.sizeof_gr_complex, 3)
dst0 = gr.vector_sink_c()
dst1 = gr.vector_sink_b()
self.tb.connect(src0, s2v0, (ofdm_remove_first_symbol, 0))
self.tb.connect(src1, (ofdm_remove_first_symbol, 1))
self.tb.connect((ofdm_remove_first_symbol, 0), v2s0, dst0)
self.tb.connect((ofdm_remove_first_symbol, 1), dst1)
self.tb.run()
result_data0 = dst0.data()
result_data1 = dst1.data()
# print src_data0
# print expected_result0
# print result_data0
self.assertComplexTuplesAlmostEqual(expected_result0, result_data0, 6)
self.assertEqual(result_data1, expected_result1)
def test_003(self):
# Need to add padding to keep proper alignment
padding = tuple([0 for i in range(5)])
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2,) + padding + \
(3.3, 4.4, 5.5,) + padding + \
(-1.1, -2.2, -3.3,) + padding
expected_result = [0, 2, 4]
expected_result.extend(padding)
expected_result.extend([7, 9, 11])
expected_result.extend(padding)
expected_result.extend([-2, -4, -7])
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_int(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_int, vlen)
dst = gr.vector_sink_i()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def __init__(self):
gr.top_block.__init__(self)
sample_rate = 32000
ampl = 0.1
self._fft_length=96
win = []
#win = [1 for i in range(self._fft_length)]
win2 = [1 for i in range(self._fft_length)]
# Constructing a sine source and the fft blocks
src0 = gr.sig_source_c (sample_rate, gr.GR_SIN_WAVE, 350, ampl)
ss2v = gr.stream_to_vector(gr.sizeof_gr_complex, self._fft_length)
sv2s = gr.vector_to_stream(gr.sizeof_gr_complex, self._fft_length)
fft_demod = gr.fft_vcc(self._fft_length, True, win2, False)
ifft = gr.fft_vcc(self._fft_length, False, win, False)
scale = gr.multiply_const_cc(1.0 / self._fft_length)
# Some output data files
trans_output = gr.file_sink(gr.sizeof_gr_complex, "trans_output.dat")
reg_output = gr.file_sink(gr.sizeof_gr_complex, "reg_output.dat")
# make the connections #
self.connect(src0, ss2v, fft_demod, ifft, sv2s, scale, trans_output)
self.connect(src0, reg_output)
def test_001(self):
vlen = 128
syms = 4
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0 / vlen)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
ifft = gr.fft_vcc(vlen, False, [], True)
fft_scale = gr.multiply_const_vcc([1.0 / vlen] * vlen)
vec = numpy.array(numpy.zeros(vlen), numpy.complex)
vec[vlen / 2 - vlen / 4] = 1.0
vec = concatenate([vec] * syms)
src = gr.vector_source_c(vec)
dst = gr.vector_sink_c()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, vlen)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f([0.0] * syms)
trig = gr.vector_source_b([1] * syms)
self.fg.connect(src, s2v, ifft, (freq_shift, 0))
self.fg.connect(eps, (freq_shift, 1))
self.fg.connect(trig, (freq_shift, 2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual(vec, numpy.array(dst.data()))
def test_001_ofdm_coarse_frequency_correct(self):
src_data0 = [
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 0, 5, 7, 6, 0, 4, 0, 6, 1, 1,
1, 0.8, 0.1, 1.3, 1, 0.7, 1, 1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9
]
expected_result0 = [7, 9, 5, 6, 0.8, 1.3, 3, 5]
expected_result0 = [complex(x) for x in expected_result0]
src_data1 = [1, 1, 1, 0]
expected_result1 = (1, 1, 1, 0)
src0 = gr.vector_source_c(src_data0)
src1 = gr.vector_source_b(src_data1)
s2v0 = gr.stream_to_vector(gr.sizeof_gr_complex, 10)
ofdm_coarse_frequency_correct = dab_swig.ofdm_coarse_frequency_correct(
10, 2)
v2s0 = gr.vector_to_stream(gr.sizeof_gr_complex, 2)
dst0 = gr.vector_sink_c()
dst1 = gr.vector_sink_b()
self.tb.connect(src0, s2v0, (ofdm_coarse_frequency_correct, 0))
self.tb.connect(src1, (ofdm_coarse_frequency_correct, 1))
self.tb.connect((ofdm_coarse_frequency_correct, 0), v2s0, dst0)
self.tb.connect((ofdm_coarse_frequency_correct, 1), dst1)
self.tb.run()
result_data0 = dst0.data()
result_data1 = dst1.data()
# print expected_result0
# print result_data0
self.assertComplexTuplesAlmostEqual(expected_result0, result_data0, 6)
self.assertEqual(result_data1, expected_result1)
def test_101(self):
vlen = 256
N = int( 5e5 )
soff=1.0
taps = [1.0,0.0,2e-1+0.1j,1e-4-0.04j]
freqoff = 0.0
norm_freq = freqoff / vlen
rms_amplitude = 8000
snr_db = 10
snr = 10.0**(snr_db/10.0)
noise_sigma = sqrt( rms_amplitude**2 / snr)
data = [1 + 1j] * vlen
#data2 = [2] * vlen
src = gr.vector_source_c( data, True, vlen )
v2s = gr.vector_to_stream(gr.sizeof_gr_complex,vlen)
channel = gr.channel_model(noise_sigma,norm_freq,soff,taps)
dst = gr.null_sink( gr.sizeof_gr_complex )
limit = gr.head( gr.sizeof_gr_complex * vlen, N )
self.tb.connect( src, limit, v2s, channel, dst )
r = time_it( self.tb )
print "Rate: %s Samples/second" \
% eng_notation.num_to_str( float(N) * vlen / r )
def helper(self, v0, v1, fft_length, preamble):
tb = self.tb
src0 = gr.vector_source_c(v0)
src1 = gr.vector_source_b(v1)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, fft_length)
# print "len(v) = %d" % (len(v))
op = gr.ofdm_insert_preamble(fft_length, preamble)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, fft_length)
dst0 = gr.vector_sink_c()
dst1 = gr.vector_sink_b()
tb.connect(src0, s2v, (op, 0))
tb.connect(src1, (op, 1))
tb.connect((op, 0), v2s, dst0)
tb.connect((op, 1), dst1)
tb.run()
r0 = dst0.data()
r0v = []
for i in range(len(r0)//fft_length):
r0v.append(r0[i*fft_length:(i+1)*fft_length])
r1 = dst1.data()
self.assertEqual(len(r0v), len(r1))
return (r1, r0v)
def test_007_vector_sampler(self):
data = range(1,577,1) # 1..576
trigger = numpy.concatenate([[0]*575,[1]])
blocks = 10000
expected = data[64:577]
assert(len(expected)==512)
expected = numpy.concatenate([expected*blocks])
assert(len(expected) == 512*blocks)
src = gr.vector_source_c(data,True)
src2 = gr.vector_source_b(trigger.tolist(),True)
dst = gr.vector_sink_c()
sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,512)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex,512)
self.fg.connect(src, (sampler,0))
self.fg.connect(src2,gr.head(gr.sizeof_char,blocks*576), (sampler,1))
self.fg.connect(sampler, v2s, dst)
self.fg.run()
#self.assertEqual(numpy.array(expected,numpy.Complex), numpy.array(dst.data(), numpy.Complex))
if numpy.array(expected).all() != numpy.array(dst.data()).all():
print "up"
print len(expected),len(dst.data())
vec = dst.data()
for i in range(min(len(expected),len(dst.data()))):
if vec[i] != expected[i]:
print "e at ",i
def test_001(self):
frames = 5
config = station_configuration()
config.subcarriers = 12
config.data_subcarriers = 8
config.training_data = dummy()
config.training_data.shifted_pilot_tones = [1, 4, 8, 11]
data = [1.0] * config.subcarriers
for x in config.training_data.shifted_pilot_tones:
data[x] = 2.0
data = concatenate([data] * frames)
ref = [1.0] * (config.data_subcarriers * frames)
src = gr.vector_source_c(data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, config.subcarriers)
dst = gr.vector_sink_c()
v2s = gr.vector_to_stream(gr.sizeof_gr_complex,
config.data_subcarriers)
uut = preambles.pilot_subcarrier_filter()
self.fg.connect(src, s2v, uut, v2s, dst)
self.fg.run()
self.assertEqual(ref, list(dst.data()))
def test_003(self):
# Need to add padding
padding = tuple([0 for i in range(29)])
scale = 2
vlen = 3
src_data = (0.0, 1.1, 2.2,) + padding + \
(3.2, 4.2, 5.5,) + padding + \
(-1.1, -2.2, -3.2,) + padding
expected_result = [0, 2, 4]
expected_result.extend(padding)
expected_result.extend([6, 8, 11])
expected_result.extend(padding)
expected_result.extend([-2, -4, -6])
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_char(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_char, vlen)
dst = gr.vector_sink_c()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def test_002_energy_disp_vbb (self):
#################################
src_data_0 = []
for number in range(22):
src_data_0.append(0)
for number in range(22):
src_data_0.append(1)
################################
expected_result_0 = (0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,
1,1,1,1,1,0,0,0,0,1,0,0,0,0,0,1)
#################################
# Objekte erzeugen
src_0 = gr.vector_source_b (src_data_0)
s2v_0 = gr.stream_to_vector(gr.sizeof_char, 22)
Energy_disp = howto_swig.energy_disp_vbb(22)
v2s_0 = gr.vector_to_stream(gr.sizeof_char, 16)
dst_0 = gr.vector_sink_b()
# Objekte verbinden
self.tb.connect(src_0, s2v_0,Energy_disp,v2s_0,dst_0)
# Simulationsstart
self.tb.run ()
# Ergebnis auswerten
result_data0 = dst_0.data ()
self.assertEqual(expected_result_0, result_data0)
def test_101(self):
vlen = 256
N = int(5e5)
soff = 1.0
taps = [1.0, 0.0, 2e-1 + 0.1j, 1e-4 - 0.04j]
freqoff = 0.0
norm_freq = freqoff / vlen
rms_amplitude = 8000
snr_db = 10
snr = 10.0**(snr_db / 10.0)
noise_sigma = sqrt(rms_amplitude**2 / snr)
data = [1 + 1j] * vlen
#data2 = [2] * vlen
src = gr.vector_source_c(data, True, vlen)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
channel = gr.channel_model(noise_sigma, norm_freq, soff, taps)
dst = gr.null_sink(gr.sizeof_gr_complex)
limit = gr.head(gr.sizeof_gr_complex * vlen, N)
self.tb.connect(src, limit, v2s, channel, dst)
r = time_it(self.tb)
print "Rate: %s Samples/second" \
% eng_notation.num_to_str( float(N) * vlen / r )
def test_001_ofdm_coarse_frequency_correct(self): fft_length = 10 num_carriers = 2 cp_length = 3 src_data0 = [0,1,2,3,4,5,6,7,8,9,1,2,0,5,7,6,0,4,0,6,1,1,1,0.8,0.1,1.3,1,0.7,1,1,0,1,2,3,4,5,6,7,8,9] expected_result0 = [7,9,5,6,0.8,1.3,3,5] offset = [3,3,-1,-1,-1,-1,-1,-1] frame_index = [0,0, 0, 0, 0, 0, 1, 1] expected_result0 = [complex(expected_result0[i])*cmath.exp(-2j*cmath.pi*offset[i]*cp_length/float(fft_length)*frame_index[i]) for i in range(0,8)] src_data1 = [1,1,1,0] expected_result1 = (1,1,1,0) src0 = gr.vector_source_c(src_data0) src1 = gr.vector_source_b(src_data1) s2v0 = gr.stream_to_vector(gr.sizeof_gr_complex, fft_length) ofdm_coarse_frequency_correct = dab_swig.ofdm_coarse_frequency_correct(fft_length,num_carriers,cp_length) v2s0 = gr.vector_to_stream(gr.sizeof_gr_complex, num_carriers) dst0 = gr.vector_sink_c() dst1 = gr.vector_sink_b() self.tb.connect(src0, s2v0, (ofdm_coarse_frequency_correct,0)) self.tb.connect(src1, (ofdm_coarse_frequency_correct,1)) self.tb.connect((ofdm_coarse_frequency_correct,0), v2s0, dst0) self.tb.connect((ofdm_coarse_frequency_correct,1), dst1) self.tb.run() result_data0 = dst0.data() result_data1 = dst1.data() # print expected_result0 # print result_data0 self.assertComplexTuplesAlmostEqual(expected_result0, result_data0, 4) self.assertEqual(result_data1, expected_result1)
def __init__(self, vlen, channel_block, delay):
gr.hier_block2.__init__(
self, 'apply_channel_to_vect',
gr.io_signature(1, 1, gr.sizeof_gr_complex * vlen),
gr.io_signature(1, 1, gr.sizeof_gr_complex * vlen))
self.vlen = vlen
self.channel_block = channel_block
self.delay = delay
pad_len = self.vlen + self.delay * 2
if (delay > 0):
self.padding = gr.vector_source_c((0, ) * (delay * 2), True,
delay * 2)
self.pad_cat = mlse.vector_concat_vv(
vlen * gr.sizeof_gr_complex, gr.sizeof_gr_complex * 2 * delay)
self.connect(self, self.pad_cat)
self.connect(self.padding, (self.pad_cat, 1))
else:
self.pad_cat = self
self.tostream = gr.vector_to_stream(gr.sizeof_gr_complex, pad_len)
self.connect(self.pad_cat, self.tostream)
# connect channel
self.connect(self.tostream, self.channel_block)
self.tovector = gr.stream_to_vector(gr.sizeof_gr_complex, pad_len)
self.connect(self.channel_block, self.tovector)
# cut out the proper part
self.trim = mlse.vector_slice_vv(gr.sizeof_gr_complex, pad_len, delay,
vlen)
self.connect(self.tovector, self.trim, self)
def test_001(self):
fft_length = 260
carriers = 100
shift = 20
# select maximum estimation range
estim_range = (fft_length - carriers) / 2
l = estim_range + shift
r = estim_range - shift
# create preambles
pn1 = pn_preamble(carriers)
pn2 = pn_preamble(carriers)
diff_pn = concatenate(
[[conjugate(math.sqrt(2) * pn2[2 * i] / pn1[2 * i]), 0.0j]
for i in range(carriers / 2)])
pn1_sym = extend_symbol(pn1, l, r)
pn2_sym = extend_symbol(pn2, l, r)
# block under tests
cfo_estimator = ofdm.schmidl_cfo_estimator(fft_length, carriers,
estim_range, diff_pn)
# source, conversion, sink
src_1 = gr.vector_source_c(pn1_sym)
src_2 = gr.vector_source_c(pn2_sym)
s2v_1 = gr.stream_to_vector(gr.sizeof_gr_complex, fft_length)
s2v_2 = gr.stream_to_vector(gr.sizeof_gr_complex, fft_length)
v2s = gr.vector_to_stream(gr.sizeof_float, 2 * estim_range + 1)
dst = gr.vector_sink_f()
self.fg.connect(src_1, s2v_1, (cfo_estimator, 0))
self.fg.connect(src_2, s2v_2, (cfo_estimator, 1))
self.fg.connect(cfo_estimator, v2s, dst)
# file output
filesink = gr.file_sink(gr.sizeof_float, "test_cfo.float")
vec_equ = vector_equalizer(2 * estim_range + 1)
self.fg.connect(
v2s, gr.float_to_complex(),
gr.stream_to_vector(gr.sizeof_gr_complex, 2 * estim_range + 1),
vec_equ,
gr.vector_to_stream(gr.sizeof_gr_complex, 2 * estim_range + 1),
gr.complex_to_float(), filesink)
runtime = self.fg
runtime.run()
def __init__(self, decim=16, N_id_1=134, N_id_2=0): grc_wxgui.top_block_gui.__init__(self, title="Sss Corr Gui") _icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png" self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY)) ################################################## # Parameters ################################################## self.decim = decim self.N_id_1 = N_id_1 self.N_id_2 = N_id_2 ################################################## # Variables ################################################## self.sss_start_ts = sss_start_ts = 10608 - 2048 - 144 self.samp_rate = samp_rate = 30720e3/decim ################################################## # Blocks ################################################## self.wxgui_scopesink2_0 = scopesink2.scope_sink_f( self.GetWin(), title="Scope Plot", sample_rate=200, v_scale=0, v_offset=0, t_scale=0, ac_couple=False, xy_mode=False, num_inputs=1, trig_mode=gr.gr_TRIG_MODE_AUTO, y_axis_label="Counts", ) self.Add(self.wxgui_scopesink2_0.win) self.gr_vector_to_stream_0 = gr.vector_to_stream(gr.sizeof_gr_complex*1, 2048/decim) self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex*1, samp_rate*decim) self.gr_stream_to_vector_0 = gr.stream_to_vector(gr.sizeof_gr_complex*1, 2048/decim) self.gr_skiphead_0 = gr.skiphead(gr.sizeof_gr_complex*1, sss_start_ts) self.gr_multiply_const_vxx_0 = gr.multiply_const_vcc((gen_sss_fd(N_id_1, N_id_2, 2048/decim).get_sss_conj_rev())) self.gr_integrate_xx_0 = gr.integrate_cc(2048/decim) self.gr_file_source_0 = gr.file_source(gr.sizeof_gr_complex*1, "/home/user/git/gr-lte/gr-lte/test/traces/lte_02_796m_30720k_frame.cfile", True) self.gr_fft_vxx_0 = gr.fft_vcc(2048/decim, True, (window.blackmanharris(1024)), True, 1) self.gr_complex_to_mag_0 = gr.complex_to_mag(1) self.fir_filter_xxx_0 = filter.fir_filter_ccc(decim, (firdes.low_pass(1, decim*samp_rate, 550e3, 100e3))) ################################################## # Connections ################################################## self.connect((self.gr_file_source_0, 0), (self.gr_throttle_0, 0)) self.connect((self.gr_stream_to_vector_0, 0), (self.gr_fft_vxx_0, 0)) self.connect((self.gr_fft_vxx_0, 0), (self.gr_multiply_const_vxx_0, 0)) self.connect((self.gr_multiply_const_vxx_0, 0), (self.gr_vector_to_stream_0, 0)) self.connect((self.gr_vector_to_stream_0, 0), (self.gr_integrate_xx_0, 0)) self.connect((self.gr_integrate_xx_0, 0), (self.gr_complex_to_mag_0, 0)) self.connect((self.gr_complex_to_mag_0, 0), (self.wxgui_scopesink2_0, 0)) self.connect((self.gr_throttle_0, 0), (self.gr_skiphead_0, 0)) self.connect((self.gr_skiphead_0, 0), (self.fir_filter_xxx_0, 0)) self.connect((self.fir_filter_xxx_0, 0), (self.gr_stream_to_vector_0, 0))
def test_30( self ):
gamma = 0.001
beta = -0.1
vlen = 208
N = 20
M = 5
pcount = 8
pdist = vlen / pcount
assert( ( pdist % 2 ) == 0 )
nondata_blocks = [0, 1]
pilot_subc = numpy.arange(pcount) * pdist + pdist/2 - vlen/2
assert( pilot_subc[0] == - pilot_subc[len(pilot_subc)-1] )
data = [1.+0.j] * vlen
frame_start = [0] * N
frame_start[0] = 1
sub_dc = vlen/2
ind_range = numpy.arange( vlen ) - vlen/2
assert( ind_range[0] == -vlen/2 )
phase_offset = ind_range * gamma + numpy.ones(vlen) * beta
assert( phase_offset[sub_dc] == beta )
phase = phase_offset
phase_offset = exp( 1j * phase_offset )
data = data * phase_offset
data = concatenate( [data] * N )
src = gr.vector_source_c( data, True, vlen )
src2 = gr.vector_source_b( frame_start, True )
dst = gr.vector_sink_c()
limit2 = gr.head( gr.sizeof_char, N * M )
uut = ofdm.LMS_phase_tracking2( vlen, pilot_subc.tolist(), nondata_blocks )
self.tb.connect( src, uut,
gr.vector_to_stream( gr.sizeof_gr_complex, vlen ), dst )
self.tb.connect( src2, limit2, ( uut, 1 ) )
self.tb.run()
d = numpy.array( dst.data() )
for i in range( M ):
xx = i * N * vlen
ad = numpy.angle( d[ (xx+len(nondata_blocks)*vlen):(xx+N*vlen) ] )
ad2 = numpy.angle( d[ xx : (xx+len(nondata_blocks)*vlen) ] )
self.assertFloatTuplesAlmostEqual(
concatenate( [phase]*len(nondata_blocks) ), ad2, 3 )
self.assertFloatTuplesAlmostEqual( numpy.zeros(len(ad)), ad, 3 )
def __init__(self, fg):
"""
@param fg: flow graph
"""
v2s = gr.vector_to_stream(gr.sizeof_char, atsc.sizeof_atsc_mpeg_packet)
self.sink = gr.vector_sink_b()
fg.connect(v2s, self.sink)
gr.hier_block.__init__(self, fg, v2s, None)
def help_const_cc(self, src_data, exp_data, op):
src = gr.vector_source_c(src_data)
srcv = gr.stream_to_vector(gr.sizeof_gr_complex, len(src_data))
rhs = gr.vector_to_stream(gr.sizeof_gr_complex, len(src_data))
dst = gr.vector_sink_c()
self.fg.connect(src, srcv, op, rhs, dst)
self.fg.run()
result_data = dst.data()
self.assertEqual(exp_data, result_data)
def __init__(self):
"""
"""
v2s = gr.vector_to_stream(gr.sizeof_char, atsc.sizeof_atsc_mpeg_packet)
self.sink = gr.vector_sink_b()
gr.hier_block2.__init__(self, "vector_sink_ts", v2s.input_signature(),
gr.io_signature(0, 0, 0))
self.connect(self, v2s, self.sink)
def test_fc32_to_f32_2(self):
tb = gr.top_block()
src = gr.vector_source_c([1+2j, 3+4j, 5+6j, 7+8j, 9+10j], False)
convert = fc32_to_f32_2()
v2s = gr.vector_to_stream(gr.sizeof_float, 2)
sink = gr.vector_sink_f()
tb.connect(src, convert, v2s, sink)
tb.run()
self.assertEqual(sink.data(), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
def help_const_ii(self, src_data, exp_data, op):
src = gr.vector_source_i(src_data)
srcv = gr.stream_to_vector(gr.sizeof_int, len(src_data))
rhs = gr.vector_to_stream(gr.sizeof_int, len(src_data))
dst = gr.vector_sink_i()
self.tb.connect(src, srcv, op, rhs, dst)
self.tb.run()
result_data = dst.data()
self.assertEqual(exp_data, result_data)
def help_const_ii(self, src_data, exp_data, op):
src = gr.vector_source_i(src_data)
srcv = gr.stream_to_vector(gr.sizeof_int, len(src_data))
rhs = gr.vector_to_stream(gr.sizeof_int, len(src_data))
dst = gr.vector_sink_i()
self.tb.connect(src, srcv, op, rhs, dst)
self.tb.run()
result_data = dst.data()
self.assertEqual(exp_data, result_data)
def test_fc32_to_f32_2(self):
tb = gr.top_block()
src = gr.vector_source_c([1+2j, 3+4j, 5+6j, 7+8j, 9+10j], False)
convert = fc32_to_f32_2()
v2s = gr.vector_to_stream(gr.sizeof_float, 2)
sink = gr.vector_sink_f()
tb.connect(src, convert, v2s, sink)
tb.run()
self.assertEqual(sink.data(), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
def __init__(self, decim=16):
grc_wxgui.top_block_gui.__init__(self, title="File Fft")
_icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png"
self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY))
##################################################
# Parameters
##################################################
self.decim = decim
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 32000
self.fft_size = fft_size = 2048 / decim
self.N_re = N_re = 62
##################################################
# Blocks
##################################################
self.wxgui_scopesink2_0 = scopesink2.scope_sink_c(
self.GetWin(),
title="Scope Plot",
sample_rate=samp_rate,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=1,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Counts",
)
self.Add(self.wxgui_scopesink2_0.win)
self.gr_vector_to_stream_0 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_stream_to_vector_0 = gr.stream_to_vector(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_keep_m_in_n_0 = gr.keep_m_in_n(gr.sizeof_gr_complex, N_re,
fft_size, (fft_size - N_re) / 2)
self.gr_file_source_0 = gr.file_source(
gr.sizeof_gr_complex * 1,
"/home/user/git/gr-lte/gr-lte/test/foo_pss0_sss_in.cfile", True)
self.gr_fft_vxx_0 = gr.fft_vcc(fft_size, True,
(window.blackmanharris(1024)), True, 1)
##################################################
# Connections
##################################################
self.connect((self.gr_stream_to_vector_0, 0), (self.gr_fft_vxx_0, 0))
self.connect((self.gr_file_source_0, 0),
(self.gr_stream_to_vector_0, 0))
self.connect((self.gr_vector_to_stream_0, 0),
(self.gr_keep_m_in_n_0, 0))
self.connect((self.gr_fft_vxx_0, 0), (self.gr_vector_to_stream_0, 0))
self.connect((self.gr_keep_m_in_n_0, 0), (self.wxgui_scopesink2_0, 0))
def __init__(self):
"""
"""
v2s = gr.vector_to_stream(gr.sizeof_char, atsc.sizeof_atsc_mpeg_packet)
self.sink = gr.vector_sink_b()
gr.hier_block2.__init__(self, "vector_sink_ts",
v2s.input_signature(),
gr.io_signature(0, 0, 0))
self.connect(self, v2s, self.sink)
def __init__(self, ):
# """
# docstring
# """
gr.hier_block2.__init__(self, "viterbi_vfvb",
gr.io_signature(1,1, gr.sizeof_float*120), # sizeof (<+float+>)), # Input signature
gr.io_signature(1,1, gr.sizeof_char*40 )) #sizeof (<+float+>))) # Output signature
#print "\nlte_viterbi_vfvb START"
#tpp=gr.tag_propagation_policy()
#################################
# Define blocks
# Repeat input vector one time to get viterbi decoder state right (tail-biting stuff)
self.rpt = gr.repeat(gr.sizeof_float*120,2)
# viterbi decoder requires stream as input
self.vtos = gr.vector_to_stream(1*gr.sizeof_float,120)
# Correct FSM instantiation: k=num_input_bits, n=num_output_bits, Tuple[dim(k*n)] (decimal notation)
self.fsm = trellis.fsm(1,3,[91,121,117])
# Values for viterbi decoder
K = 80 # steps for one coding block
SO = 0 # initial state
SK = -1 # final state (in this case unknown, therefore -1)
D = 3 # dimensionality
# D = 3 follows from the fact that 1 {0,1} input symbol of the encoder produces 3 {0,1} output symbols.
# (packed into one byte {0,1,...,7} )
# with NRZ coding follows:
# 0 --> 1
# 1 --> -1
# This leads to the following constellation input
# | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
constellation = [1,1,1,1,1,-1,1,-1,1,1,-1,-1,-1,1,1,-1,1,-1,-1,-1,1,-1,-1,-1]
# print "len(constellation)/D = " + str(len(constellation)/D) + "\tfsm.O = " + str(self.fsm.O())
# Viterbi_combined input: FSM, K, SO, SK, D, TABLE, TYPE
# FSM = Finite State Machine
# K = number of output symbols produced by the FSM
# SO = initial state of the FSM
# SK = final state of the FSM (unknown in this example)
# D = dimensionality
# TABLE = constellation of the input symbols
self.vit = trellis.viterbi_combined_fb(self.fsm,K,SO,SK,D,constellation,200)
# stream output of viterbi decoder to vector
self.stov2 = gr.stream_to_vector(1*gr.sizeof_char,80)
# second half of the viterbi output carries desired information. (tail-biting stuff)
my_map=range(40)
for i in my_map:
my_map[i]=i+40
self.map = lte.vector_resize_vbvb(my_map,80,40)
self.connect(self,self.rpt,self.vtos,self.vit,self.stov2,self.map,self)
def test_001(self):
fft_length = 260
carriers = 100
shift = 20
# select maximum estimation range
estim_range = (fft_length-carriers)/2
l = estim_range+shift
r = estim_range-shift
# create preambles
pn1 = pn_preamble(carriers)
pn2 = pn_preamble(carriers)
diff_pn = concatenate([[conjugate(math.sqrt(2)*pn2[2*i]/pn1[2*i]),0.0j] for i in range(carriers/2)])
pn1_sym = extend_symbol(pn1,l,r)
pn2_sym = extend_symbol(pn2,l,r)
# block under tests
cfo_estimator = ofdm.schmidl_cfo_estimator(fft_length,carriers,estim_range,diff_pn)
# source, conversion, sink
src_1 = gr.vector_source_c(pn1_sym)
src_2 = gr.vector_source_c(pn2_sym)
s2v_1 = gr.stream_to_vector(gr.sizeof_gr_complex,fft_length)
s2v_2 = gr.stream_to_vector(gr.sizeof_gr_complex,fft_length)
v2s = gr.vector_to_stream(gr.sizeof_float,2*estim_range+1)
dst = gr.vector_sink_f()
self.fg.connect(src_1, s2v_1, (cfo_estimator,0))
self.fg.connect(src_2, s2v_2, (cfo_estimator,1))
self.fg.connect(cfo_estimator,v2s,dst)
# file output
filesink = gr.file_sink(gr.sizeof_float,"test_cfo.float")
vec_equ = vector_equalizer(2*estim_range+1)
self.fg.connect(v2s,gr.float_to_complex(),
gr.stream_to_vector(gr.sizeof_gr_complex,2*estim_range+1),
vec_equ,gr.vector_to_stream(gr.sizeof_gr_complex,2*estim_range+1),
gr.complex_to_float(),filesink)
runtime=self.fg
runtime.run()
def test_003(self):
# Same test as above, only use 2 threads
tb = gr.top_block()
fft_size = 32
tmp_data = ((4377+4516j),
(-1706.1268310546875+1638.4256591796875j),
(-915.2083740234375+660.69427490234375j),
(-660.370361328125+381.59600830078125j),
(-499.96044921875+238.41630554199219j),
(-462.26748657226562+152.88948059082031j),
(-377.98440551757812+77.5928955078125j),
(-346.85821533203125+47.152004241943359j),
(-295+20j),
(-286.33609008789062-22.257017135620117j),
(-271.52999877929688-33.081821441650391j),
(-224.6358642578125-67.019538879394531j),
(-244.24473571777344-91.524826049804688j),
(-203.09068298339844-108.54627227783203j),
(-198.45195007324219-115.90768432617188j),
(-182.97744750976562-128.12318420410156j),
(-167-180j),
(-130.33688354492188-173.83778381347656j),
(-141.19784545898438-190.28807067871094j),
(-111.09677124023438-214.48896789550781j),
(-70.039543151855469-242.41630554199219j),
(-68.960540771484375-228.30015563964844j),
(-53.049201965332031-291.47097778320312j),
(-28.695289611816406-317.64553833007812j),
(57-300j),
(45.301143646240234-335.69509887695312j),
(91.936195373535156-373.32437133789062j),
(172.09465026855469-439.275146484375j),
(242.24473571777344-504.47515869140625j),
(387.81732177734375-666.6788330078125j),
(689.48553466796875-918.2142333984375j),
(1646.539306640625-1694.1956787109375j))
src_data = tuple([x/fft_size for x in tmp_data])
expected_result = tuple([complex(primes[2*i], primes[2*i+1]) for i in range(fft_size)])
nthreads = 2
src = gr.vector_source_c(src_data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, fft_size)
fft = gr.fft_vcc(fft_size, False, [], False, nthreads)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, fft_size)
dst = gr.vector_sink_c()
tb.connect(src, s2v, fft, v2s, dst)
tb.run()
result_data = dst.data()
self.assert_fft_ok2(expected_result, result_data)
def test_003(self):
# Same test as above, only use 2 threads
tb = gr.top_block()
fft_size = 32
tmp_data = ((4377+4516j),
(-1706.1268310546875+1638.4256591796875j),
(-915.2083740234375+660.69427490234375j),
(-660.370361328125+381.59600830078125j),
(-499.96044921875+238.41630554199219j),
(-462.26748657226562+152.88948059082031j),
(-377.98440551757812+77.5928955078125j),
(-346.85821533203125+47.152004241943359j),
(-295+20j),
(-286.33609008789062-22.257017135620117j),
(-271.52999877929688-33.081821441650391j),
(-224.6358642578125-67.019538879394531j),
(-244.24473571777344-91.524826049804688j),
(-203.09068298339844-108.54627227783203j),
(-198.45195007324219-115.90768432617188j),
(-182.97744750976562-128.12318420410156j),
(-167-180j),
(-130.33688354492188-173.83778381347656j),
(-141.19784545898438-190.28807067871094j),
(-111.09677124023438-214.48896789550781j),
(-70.039543151855469-242.41630554199219j),
(-68.960540771484375-228.30015563964844j),
(-53.049201965332031-291.47097778320312j),
(-28.695289611816406-317.64553833007812j),
(57-300j),
(45.301143646240234-335.69509887695312j),
(91.936195373535156-373.32437133789062j),
(172.09465026855469-439.275146484375j),
(242.24473571777344-504.47515869140625j),
(387.81732177734375-666.6788330078125j),
(689.48553466796875-918.2142333984375j),
(1646.539306640625-1694.1956787109375j))
src_data = tuple([x/fft_size for x in tmp_data])
expected_result = tuple([complex(primes[2*i], primes[2*i+1]) for i in range(fft_size)])
nthreads = 2
src = gr.vector_source_c(src_data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, fft_size)
fft = gr.fft_vcc(fft_size, False, [], False, nthreads)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, fft_size)
dst = gr.vector_sink_c()
tb.connect(src, s2v, fft, v2s, dst)
tb.run()
result_data = dst.data()
self.assert_fft_ok2(expected_result, result_data)
def help_cc(self, size, src_data, exp_data, op):
for s in zip(range(len(src_data)), src_data):
src = gr.vector_source_c(s[1])
srcv = gr.stream_to_vector(gr.sizeof_gr_complex, size)
self.tb.connect(src, srcv)
self.tb.connect(srcv, (op, s[0]))
rhs = gr.vector_to_stream(gr.sizeof_gr_complex, size)
dst = gr.vector_sink_c()
self.tb.connect(op, rhs, dst)
self.tb.run()
result_data = dst.data()
self.assertEqual(exp_data, result_data)
def __init__(self, data_tones, num_symbols, mode=0):
symbol_size = data_tones * gr.sizeof_gr_complex
gr.hier_block2.__init__(self, "SNR",
gr.io_signature2(2,2, symbol_size, symbol_size),
gr.io_signature(1,1, gr.sizeof_float))
sub = gr.sub_cc(data_tones)
self.connect((self,0), (sub,0))
self.connect((self,1), (sub,1))
err = gr.complex_to_mag_squared(data_tones);
self.connect(sub, err);
pow = gr.complex_to_mag_squared(data_tones);
self.connect((self,1), pow);
if mode == 0:
# one snr per symbol (num_symbols is ignored)
snr = gr.divide_ff()
self.connect(pow, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones), (snr,0))
self.connect(err, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones), (snr,1))
out = snr
elif mode == 1:
# one snr per packet
snr = gr.divide_ff()
self.connect(pow, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones*num_symbols), (snr,0))
self.connect(err, gr.vector_to_stream(gr.sizeof_float, data_tones),
gr.integrate_ff(data_tones*num_symbols), (snr,1))
out = snr
elif mode == 2:
# one snr per frequency bin
snr = gr.divide_ff(data_tones)
self.connect(pow, raw.symbol_avg(data_tones, num_symbols), (snr,0))
self.connect(err, raw.symbol_avg(data_tones, num_symbols), (snr,1))
out = gr.vector_to_stream(gr.sizeof_float, data_tones)
self.connect(snr, out)
self.connect(out, gr.nlog10_ff(10), self)
def __init__(self, framebytes, numframes, mode=0):
gr.hier_block2.__init__(self, "BER",
gr.io_signature2(2,2, framebytes, framebytes),
gr.io_signature(1,1, gr.sizeof_float))
xor = gr.xor_bb()
self.connect((self,0), gr.vector_to_stream(gr.sizeof_char, framebytes), (xor,0))
self.connect((self,1), gr.vector_to_stream(gr.sizeof_char, framebytes), (xor,1))
if mode == 0:
# one ber per packet
ber = raw.ber_avg(1, framebytes)
self.connect(xor,
ber)
elif mode == 1:
# one ber per byte in packet
ber = raw.ber_avg(framebytes, numframes)
self.connect(xor,
gr.stream_to_vector(gr.sizeof_char, framebytes),
ber)
self.connect(ber, self)
def simple_test2(self, gamma, beta):
vlen = 208
N = 20
pcount = 8
pdist = vlen / pcount
assert ((pdist % 2) == 0)
nondata_blocks = [0, 1]
pilot_subc = numpy.arange(pcount) * pdist + pdist / 2 - vlen / 2
assert (pilot_subc[0] == -pilot_subc[len(pilot_subc) - 1])
data = [1. + 0.j] * vlen
frame_start = [0] * N
frame_start[0] = 1
sub_dc = vlen / 2
ind_range = numpy.arange(vlen) - vlen / 2
assert (ind_range[0] == -vlen / 2)
phase_offset = ind_range * gamma + numpy.ones(vlen) * beta
assert (phase_offset[sub_dc] == beta)
phase = phase_offset
phase_offset = exp(1j * phase_offset)
data = data * phase_offset
data = concatenate([data] * N)
src = gr.vector_source_c(data, False, vlen)
src2 = gr.vector_source_b(frame_start, False)
dst = gr.vector_sink_c()
uut = ofdm.LMS_phase_tracking2(vlen, pilot_subc.tolist(),
nondata_blocks)
self.tb.connect(src, uut,
gr.vector_to_stream(gr.sizeof_gr_complex, vlen), dst)
self.tb.connect(src2, (uut, 1))
self.tb.run()
d = numpy.array(dst.data())
ad = numpy.angle(d[(len(nondata_blocks) * vlen):len(d)])
ad2 = numpy.angle(d[0:(len(nondata_blocks) * vlen)])
self.assertFloatTuplesAlmostEqual(
concatenate([phase] * len(nondata_blocks)), ad2, 3)
self.assertFloatTuplesAlmostEqual(numpy.zeros(len(ad)), ad, 3)
def test_002_vector_slice_vv(self):
"""tests reversing and cutting off the beginning of the input"""
src = gr.vector_source_f(
(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15))
expected_result = (5, 4, 3, 10, 9, 8, 15, 14, 13)
dst = gr.vector_sink_f()
reor1 = gr.stream_to_vector(gr.sizeof_float, 5)
reor2 = gr.vector_to_stream(gr.sizeof_float, 3)
slicer = mlse_swig.vector_slice_vv(gr.sizeof_float, 5, 2, 3, 1)
self.tb.connect(src, reor1, slicer, reor2, dst)
self.tb.run()
self.tb.run()
result_data = dst.data()
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 6)
def test_001_vector_slice_vv(self):
"""tests negative offsets"""
src = gr.vector_source_f(
(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15))
expected_result = (0, 1, 2, 0, 6, 7, 0, 11, 12)
dst = gr.vector_sink_f()
reor1 = gr.stream_to_vector(gr.sizeof_float, 5)
reor2 = gr.vector_to_stream(gr.sizeof_float, 3)
slicer = mlse_swig.vector_slice_vv(gr.sizeof_float, 5, -1, 3)
self.tb.connect(src, reor1, slicer, reor2, dst)
self.tb.run()
self.tb.run()
result_data = dst.data()
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 6)
