Comparison of DSB AM and DSBSC AM modulation in a channel with limited white noise¶
This model demonstrates the differences in stability and transmission efficiency between two-band amplitude modulation with carrier (DSB AM) and with suppressed carrier (DSBSC AM) under band-limited white noise channel conditions. It consists of a signal generator, modulation and demodulation channels, and blocks for error calculation and analysis.
The model itself is shown in the figure below.
The main blocks of the model are described below.
Source signal generation consists of two blocks.
- Sine Wave: generates the initial harmonic signal.
- Zero-Order Hold: provides discretisation by fixing the signal level at each time step.
The first branch is DSB AM.
- DSB AM Modulator Passband modulates the signal while preserving the carrier frequency, which simplifies transmission and demodulation.
- Add Noise: Band-Limited White Noise is added to the signal using the Add block to simulate a real noisy communication channel.
- DSB AM Demodulator Passband demodulates the signal, restoring the original information.
- Comparison and error calculation.
- Add finds the difference between the original signal and the signal at the demodulator output.
- Abs calculates the absolute value of the error for each sample.
- Average Filter is a filter with a sliding window of 1000 samples to calculate the average error.
The second branch - DSBSC AM differs only in modulation blocks.
- DSBSC AM Modulator Passband modulates the signal with carrier suppression. The energy is concentrated on the sidebands, which reduces the energy cost.
- DSBSC AM Demodulator Passband demodulates the signal, requiring precise synchronisation to recover the carrier frequency as the carrier is not transmitted.
Let's move on to the modelling¶
Declaring an auxiliary function¶
# 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
Initialising and running the model¶
Noise_power = 0.1;
window = 1000;
run_model("DSB_and_DSBSC") # Запуск модели.
Average_error_DSB = collect(Average_error_DSB);
Average_error_DSBSC = collect(Average_error_DSBSC);
Analysing the result¶
gr()
plot(Average_error_DSB.time,Average_error_DSB.value, title = "Error", label = "DSB_AM")
plot!(Average_error_DSBSC.time,Average_error_DSBSC.value, title = "Error", label = "DSBSC_AM")
As we can see in the graph, the average error value is smaller in case of DSBSC AM. This is due to the differences between these two types of modulation. Let's understand them in more detail.
DSB AM (with carrier).
- modulation characteristic: the signal is transmitted with a carrier, which simplifies demodulation because the carrier frequency can be easily recovered by the receiver.
- Energy consumption: requires more power as some of the energy is spent on the carrier.
- Immunity to noise: more susceptible to the effects of noise as the carrier is also subject to distortion.
- Advantages: easy demodulation, making it suitable for systems with limited processing power or simplified synchronisation.
- Disadvantages: low power efficiency, since a significant amount of power is spent in transmitting the carrier.
DSBSC AM (carrier suppressed).
- Modulation characteristic: the transmission is done by sideband only, making the scheme more energy efficient.
- energy consumption: requires less power because the carrier is not transmitted and energy is concentrated on useful information.
- Immunity to noise: less prone to noise compared to DSB AM, but requires precise synchronisation for demodulation.
- Advantages: high energy efficiency and better noise immunity compared to DSB AM.
- Disadvantages: difficult to demodulate due to the need for precise synchronisation to the reference frequency.
Conclusion¶
The main result of the demonstration is that we saw that the mean error value for DSBSC AM is lower than that for DSB AM.
This difference is due to the modulation methods themselves: in DSBSC AM the signal power is concentrated only in the sidebands, which makes it less sensitive to noise compared to DSB AM, where part of the energy is spent on transmitting the carrier. In DSB AM, this additional carrier is subject to distortion and introduces additional error when the signal is recovered after passing through the noise channel.
Thus, this comparison confirms that DSBSC AM has higher noise immunity and higher energy efficiency, which makes it preferable in systems requiring a high level of interference immunity and minimum energy consumption.