If you consider a particular type of channel model, the spatial correlation might be determined by a parameter. In particular, the “angular spread” is a common measure for spatial correlation in physical propagation models (such as the one used in Figure 2.6). A smaller angular spread corresponds to stronger spatial correlation.

]]>Sections 3 and 4 explain these things in more detail.

]]>I’m interested to know more about what you said:

“On the average, it appears that spatial channel correlation improves the spectral efficiency.”

Can you please suggest the chapter of your book and any other paper, where explains this a little bit…?

]]>But if you want to generate more realistic channels that have some correlation, you can use the following Matlab implementation of 3GPP channel models:

http://quadriga-channel-model.de

It is often more analytically tractable to deal with i.i.d. fading channels, which is why many research advances are first made for i.i.d. channels and then generalized to correlated fading.

]]>I have a question.

Question: Can we use “AMP Algorithm” in “Correlated Rayleigh Fading Model” for Activity Detection of active user?

Actually I am working on massive connectivity but I have seen many researchers follow i.i.d fading channel instead of Correlated fading channel.

]]>This is discussed in depth in my new book, so I suggest that you read it before conducting research on the topic:

Emil Björnson, Jakob Hoydis and Luca Sanguinetti (2017), “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency”, Foundations and Trends® in Signal Processing: Vol. 11, No. 3-4, pp 154–655. DOI: 10.1561/2000000093.

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