Influence of single BER pulses¶
In this example, we consider a BPSK receiver and transmitter system with single interference in the data. The system itself is shown in the figure below.
At the top level we see the random dataset generator, BPSK and pulse generator, which is shown in the figure below.
There are 3 pulse generators in this subsystem. By using delays and adders we increase the number of these pulses.
Next, let's set the auxiliary function to start the model.
# Подключение вспомогательной функции запуска модели.
function run_model( name_model)
Path = (@__DIR__) * "/" * name_model * ".engee"
if name_model in [m.name for m in engee.get_all_models()] # Проверка условия загрузки модели в ядро
model = engee.open( name_model ) # Открыть модель
model_output = engee.run( model, verbose=true ); # Запустить модель
else
model = engee.load( Path, force=true ) # Загрузить модель
model_output = engee.run( model, verbose=true ); # Запустить модель
engee.close( name_model, force=true ); # Закрыть модель
end
sleep(5)
return model_output
end
Let's run the model with interference switched off and on.
EnableImpulse = 0;
run_model("BPSK_and_Impulse") # Запуск модели.
BER = collect(BER)
println("BER: " * string(BER.value[end]))
EnableImpulse = 1;
run_model("BPSK_and_Impulse") # Запуск модели.
BER = collect(BER)
print("BER: " * string(BER.value[end]))
Conclusion¶
As we can see from the results, in our case several values were identified incorrectly after adding interference. This is most likely due to the fact that there were points that were identified as 1 instead of 0. To avoid this situation, use interpolation and averaging.