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Signal Processing

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  • $\begingroup$ Thanks! I am clear now. Is there any models capture the temporal characteristics of the channel gain then? $\endgroup$ Commented Jan 7 at 7:08
  • $\begingroup$ Yes, see the bottom of the Wikipedia link summarizing the common approaches to doing this: Jakes's model, and filtered white noise. I like the filter approach due to its simplicity. What I essentially do in that case is generate a magnitude and phase from a Rayleigh distribution (which is the mag and phase of a complex white noise) for each received sample, but then filter those values first with a response consistent with the expected bathtub PSD (which you can generate most easily using the approach described in the last paragraph in this post: dsp.stackexchange.com/a/93746/21048 ). $\endgroup$ Commented Jan 7 at 13:48
  • $\begingroup$ the filtered stream of channel gain and phase values is then multiplied with the received signal. This is all done at complex baseband to be simplest. The frequency response you want for the resulting filter is given by the $S(v)$ in the wikipedia link under "Doppler power spectral density". (if using the FFT approach, the FFT values would be the square root of the PSD) $\endgroup$ Commented Jan 7 at 13:55