In the paper “Massive MIMO Has Unlimited Capacity”, the authors used three different channel correlation models and I was wondering which one is the closest one to the real-world case and which one, if not the same, is the hardest to massive MIMO systems in the sense of capacity.
We didn't select the spatial correlation models in that paper based on real-world modeling, but in order to cover different properties:
1. Spatially uncorrelated
2. Spatially correlated but all eigenvalues are non-zero
3. Spatially correlated and some eigenvalues are zero or close to zero (spatial sparsity).
The reason was to demonstrate that category 2 is sufficient to prove the unlimited capacity (i.e., linearly independent correlation matrices), while some previous works have required category 3 to show somewhat similar results (i.e., spatially orthogonal matrices). Our main claim is that our result turns the unlimited capacity result from being a special case, to actually being the normal case.
Since you ask about real-world models, let me say that 3GPP is normally considering models that resemble the "local scattering model" from Chapter 2 of my book Massive MIMO networks, but with six clusters instead of one. We use such a model in the paper "Massive MIMO with Spatially Correlated Rician Fading Channels" (https://arxiv.org/pdf/1805.07972.pdf)
How can I enrich knowledge about basic MIMO and 5G with matlab Code@ Emil Bjornson Sir
@parjoy: For basic MIMO, the following book is good
https://books.google.de/books/about/MIMO_OFDM_Wireless_Communications_with_M.html?id=6HwAoeuMr3kC&source=kp_book_description&redir_esc=y
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