def do(self, nb_tx, nb_rx):
def check_noise(mod, chan, corrected_SNR_lin):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg) # previous test asserted that channel neither add nor remove energy
P_noise = signal_power(chan.noises)
assert_allclose(abs(chan.noises.mean()), 0., atol=0.5,
err_msg='Noise mean is not 0')
if corrected_SNR_lin == inf:
assert_allclose(P_noise, 0, atol=1e-2,
err_msg='There is noise that should not be here')
else:
assert_allclose(chan.nb_tx * P_msg / P_noise, corrected_SNR_lin, atol=0.2,
err_msg='Wrong SNR')
fading_param = zeros((nb_rx, nb_tx), complex), identity(nb_tx), identity(nb_rx)
chan = MIMOFlatChannel(nb_tx, nb_rx, fading_param=fading_param)
for mod in self.all_mods:
chan.noise_std = 0
check_noise(mod, chan, inf)
chan.set_SNR_lin(6, Es=signal_power(mod))
check_noise(mod, chan, 6)
chan.set_SNR_lin(6, .5, signal_power(mod))
check_noise(mod, chan, 3)
chan.set_SNR_dB(0, Es=signal_power(mod))
check_noise(mod, chan, 1)
chan.set_SNR_dB(0, .5, signal_power(mod))
check_noise(mod, chan, .5)
def do(self, nb_tx, nb_rx):
# Set seed
seed(17121996)
def check_noise(mod, chan, corrected_SNR_lin):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg) # previous test asserted that channel neither add nor remove energy
P_noise = signal_power(chan.noises)
assert_allclose(abs(chan.noises.mean()), 0., atol=0.5,
err_msg='Noise mean is not 0')
if corrected_SNR_lin == inf:
assert_allclose(P_noise, 0, atol=1e-2,
err_msg='There is noise that should not be here')
else:
assert_allclose(chan.nb_tx * P_msg / P_noise, corrected_SNR_lin, atol=0.2,
err_msg='Wrong SNR')
fading_param = zeros((nb_rx, nb_tx), complex), identity(nb_tx), identity(nb_rx)
chan = MIMOFlatChannel(nb_tx, nb_rx, fading_param=fading_param)
for mod in self.all_mods:
chan.noise_std = 0
check_noise(mod, chan, inf)
chan.set_SNR_lin(6, Es=signal_power(mod))
check_noise(mod, chan, 6)
chan.set_SNR_lin(6, .5, signal_power(mod))
check_noise(mod, chan, 3)
chan.set_SNR_dB(0, Es=signal_power(mod))
check_noise(mod, chan, 1)
chan.set_SNR_dB(0, .5, signal_power(mod))
check_noise(mod, chan, .5)
def test_noise_generation(self):
def check_noise(mod, chan, corrected_SNR_lin):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg) # previous test asserted that channel neither add nor remove energy
P_noise = signal_power(chan.noises)
assert_allclose(absolute(chan.noises.mean()), 0., atol=5e-2,
err_msg='Noise mean is not 0')
if corrected_SNR_lin == inf:
assert_allclose(P_noise, 0, atol=1e-2,
err_msg='There is noise that should not be here')
else:
assert_allclose(P_msg / P_noise, corrected_SNR_lin, atol=0.2,
err_msg='Wrong SNR')
chan = SISOFlatChannel(fading_param=(1 + 0j, 0))
for mod in self.all_mods:
chan.noise_std = 0
check_noise(mod, chan, inf)
chan.set_SNR_lin(6, Es=signal_power(mod))
check_noise(mod, chan, 6)
chan.set_SNR_lin(6, .5, signal_power(mod))
check_noise(mod, chan, 3)
chan.set_SNR_dB(0, Es=signal_power(mod))
check_noise(mod, chan, 1)
chan.set_SNR_dB(0, .5, signal_power(mod))
check_noise(mod, chan, .5)
def check_chan_gain(mod, chan):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg)
P_unnoisy = signal_power(chan.unnoisy_output)
assert_allclose(P_unnoisy, P_msg, rtol=0.2,
err_msg='Channel add or remove energy')
def check_chan_gain(mod, chan):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg)
P_unnoisy = signal_power(chan.unnoisy_output)
assert_allclose(P_unnoisy, P_msg, rtol=0.2,
err_msg='Channel add or remove energy')
def check_noise(mod, chan, corrected_SNR_lin):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg) # previous test asserted that channel neither add nor remove energy
P_noise = signal_power(chan.noises)
assert_allclose(abs(chan.noises.mean()), 0., atol=0.5,
err_msg='Noise mean is not 0')
if corrected_SNR_lin == inf:
assert_allclose(P_noise, 0, atol=1e-2,
err_msg='There is noise that should not be here')
else:
assert_allclose(chan.nb_tx * P_msg / P_noise, corrected_SNR_lin, atol=0.2,
err_msg='Wrong SNR')
def check_noise(mod, chan, corrected_SNR_lin):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(msg) # previous test asserted that channel neither add nor remove energy
P_noise = signal_power(chan.noises)
assert_allclose(abs(chan.noises.mean()), 0., atol=0.5,
err_msg='Noise mean is not 0')
if corrected_SNR_lin == inf:
assert_allclose(P_noise, 0, atol=1e-2,
err_msg='There is noise that should not be here')
else:
assert_allclose(chan.nb_tx * P_msg / P_noise, corrected_SNR_lin, atol=0.2,
err_msg='Wrong SNR')
def test_noise_generation(self):
def check_noise(mod, chan, corrected_SNR_lin):
msg = choice(mod, self.msg_length)
chan.propagate(msg)
P_msg = signal_power(
msg
) # previous test asserted that channel neither add nor remove energy
P_noise = signal_power(chan.noises)
assert_allclose(absolute(chan.noises.mean()),
0.,
atol=5e-2,
err_msg='Noise mean is not 0')
if corrected_SNR_lin == inf:
assert_allclose(
P_noise,
0,
atol=1e-2,
err_msg='There is noise that should not be here')
else:
assert_allclose(P_msg / P_noise,
corrected_SNR_lin,
atol=0.2,
err_msg='Wrong SNR')
chan = SISOFlatChannel(fading_param=(1 + 0j, 0))
for mod in self.all_mods:
chan.noise_std = 0
check_noise(mod, chan, inf)
chan.set_SNR_lin(6, Es=signal_power(mod))
check_noise(mod, chan, 6)
chan.set_SNR_lin(6, .5, signal_power(mod))
check_noise(mod, chan, 3)
chan.set_SNR_dB(0, Es=signal_power(mod))
check_noise(mod, chan, 1)
chan.set_SNR_dB(0, .5, signal_power(mod))
check_noise(mod, chan, .5)
chan = SISOFlatChannel(fading_param=(1, 0))
for mod in self.real_mods:
chan.noise_std = 0
check_noise(mod, chan, inf)
chan.set_SNR_lin(6, Es=signal_power(mod))
check_noise(mod, chan, 6)
chan.set_SNR_lin(6, .5, signal_power(mod))
check_noise(mod, chan, 3)
chan.set_SNR_dB(0, Es=signal_power(mod))
check_noise(mod, chan, 1)
chan.set_SNR_dB(0, .5, signal_power(mod))
check_noise(mod, chan, .5)
def constellation(self, value):
# Check value input
num_bits_symbol = log2(len(value))
if num_bits_symbol != int(num_bits_symbol):
raise ValueError('Constellation length must be a power of 2.')
# Set constellation as an array
self._constellation = array(value)
# Update other attributes
self.Es = signal_power(self.constellation)
self.m = self._constellation.size
self.num_bits_symbol = int(num_bits_symbol)
decodedCodes[i] = deCompAlgo[i](sourceCodes[i])
timeStop = perf_counter_ns()
timeDe[i] = timeStop - timeStart
'''
#Number of Flops
papi_high.flops()
decodedCodes[i] = deCompAlgo[i](sourceCodes[i])
result = papi_high.flops()
flopsDe[i] = result.mflops
papi_high.stop_counters()
'''
for i in range(0, noOfSources):
M = 16
mod = PSKModem(M)
sigPower[i] = signal_power(np.array(list(sourceCodes[i]), dtype=int))
print("Normally our code would be of size ", len(sourceCodes[0]))
print("")
for i in range(0, noOfSources):
if decodedCodes[i] != decodedCodes[0]:
print('There is an error in', sourceNames[i])
print('Original Code is', decodedCodes[0])
print('Recieved Code is', decodedCodes[i])
print("")
print("Using ", sourceNames[i], " The size is ",
str(len(sourceCodes[i])) + ":")
print("Compression ratio of ",
len(sourceCodes[0]) / len(sourceCodes[i]))
print("The time taken to compress", timeEn[i])
print("The time taken to decompress", timeDe[i])
def do_qam(self, modem):
assert_allclose(signal_power(modem.constellation),
2 * (modem.m - 1) / 3)
