def plot_all_pb(Nsamples, SNRmax, show_plot):
modulations = {}
modulations["QAM"] = QAM(16, 1)
modulations["PAM"] = PAM(16, 1)
modulations["PSK"] = PSK(16, 1)
modulations["FSK"] = FSK(16, 1)
for modulation_name in modulations:
SNRs_estimacion, pe_estimada = modulations[
modulation_name].montecarlo_pb_vs_snr(SNRmax, Nsamples)
SNRs_teoricas, pe_teorica = modulations[
modulation_name].theorical_pb_vs_snr(SNRmax)
plt.plot(SNRs_teoricas,
pe_teorica,
label=f"{modulation_name} teórica",
zorder=1)
plt.scatter(SNRs_estimacion,
pe_estimada,
label=f"{modulation_name} estimada",
zorder=2)
plt.title('Probabilidades de error de bit para M=16')
plt.yscale('log')
plt.xlabel('SNR [dB]')
plt.ylabel('log(Probabilidad de error)')
plt.legend()
plt.grid()
plt.savefig(f'results/all_modulations.png')
if show_plot:
plt.show()
plt.close()
plt.clf()
def main():
test_string = raw_input('Please enter in a binary string:\n')
signal = validate_input_string(test_string)
fsk = FSK(signal)
display_carrier_signal()
display_digital_signal(signal, 'Original Signal')
fsk.encode_wave()
original_signal = fsk.decode_wave()
display_digital_signal(original_signal, 'De-Modulated Signal')
plt.show()
def main():
psk = PSK(signal)
fsk = FSK(signal)
ask = ASK(signal)
psk.graph()
fsk.graph()
ask.graph()
Carrier()
OrginSignal()
plt.show()
