Question about setting the reflection coefficient of objects in phased.Sca​tteringMIM​OChannel

In the example "Integrated Sensing and Communication II: Communication-Centric Approach Using MIMO-OFDM", when reducing the number of static scatterers or setting their reflection coefficients to zero, the bit error rate (BER) increases more than 50 times compared to the original example. I would like to understand the reason for this.

I understand that in a multipath environment, the signals reflected from static scatterers can enhance the received signal, thereby reducing the BER. However, when setting the reflection coefficients of static scatterers to zero, I would expect the BER to increase slightly rather than experiencing such a drastic 50-fold increase.

From my understanding, in a scenario where there are no obstacles along the signal path, the BER should either decrease or increase slightly. I am curious why removing reflections from static scatterers results in such a significant increase in BER.

Answer 1

[Jack]

The significant increase in BER occurs because the static scatterers provide beneficial multipath contributions that improve the effective channel gain. In the original example, these static reflections add diversity and can constructively interfere with the direct path, which enhances the overall SNR. When you set their reflection coefficients to zero, you remove these helpful multipath components, leaving only the less favorable dynamic paths. This results in a much weaker effective channel and, consequently, a dramatic increase in the BER.

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[JG]

Thanks for your help.

[JG]

Could you provide any advice on reducing bit errors in a scenario where only one moving object is present without the static scatterers? Besides phased.ScatteringMIMOChannel, are there any other functions you would recommend?

[Jack]

In a scenario with only one moving object and no static scatterers, the channel diversity is severely reduced, which can drastically increase the BER. Besides using phased.ScatteringMIMOChannel, you might consider using comm.MIMOChannel from the Communications Toolbox. This function allows you to simulate different channel conditions such as Rician fading by adjusting the K-factor to emphasize the strong direct path from the moving object while still modeling any residual multipath. Moreover, incorporating diversity techniques or channel coding (for example, space-time block coding via comm.OSTBCEncoder and comm.OSTBCDecoder) can help mitigate the bit errors caused by the lack of beneficial static multipath components. These approaches provide a more robust simulation framework that can help reduce the BER even when the scattering environment is limited to a single moving object.

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[JG]

Thank you so much for your great help. I really appreciate it!

[JG]

I have one last question. In the example above, when the reflection coefficient of the static scatterer was set to 0, the bit error rate (BER) was high. However, the results from the Moving Scatter using the Doppler effect and the range-Doppler response turned out well.

Despite the high BER, the Doppler effect-based results were favorable. Do you have any insights into why this happened?

[Jack]

When the static scatterers are removed, the overall effective SNR decreases because you lose the beneficial multipath contributions that would normally enhance the received signal. This results in a high bit error rate (BER). However, the moving scatterer still introduces a distinct Doppler shift that is captured well by range-Doppler processing. In range-Doppler algorithms, coherent integration over multiple pulses can improve the detectability of the Doppler frequency even when the instantaneous SNR is low. Essentially, while the high BER reflects the degraded performance in terms of data fidelity, the Doppler signature from the moving object remains strong and can be accurately estimated through averaging and integration techniques, leading to favorable range-Doppler results.

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[JG]

Thank you so much. I really appreciate your help.