However, it seems that favourable propagation condition might not be met in this case. (h^H)*(h)/M would not go to 0 as M goes to infinity.

So what would be the implications on sum throughput/capacity of such systems where the channel hardening condition is already satisfied but favourable propagation condition is not met?

I read the paper, “No downlink pilots are needed in TDD Massive MIMO” and it explains what would happen in keyhole channels (without favourable propagation and without channel hardening), but I want to know what would happen in systems without favourable propagation but with channels already “hardened”?

I am asking this question in context of low mobility users since for high mobility users, it might be a different story.

]]>If we talk about mm-wave Massive MIMO, where paths are mostly line-of-sight and assume that channel will be estimated by uplink pilots only (TDD mode and reciprocity), will Massive MIMO work in such conditions too? ]]>

When you talk about stationarity, I think what you refer to are users that move around. The hardening only applies to small-scale fading effects and not variations in the large-scale fading effects (path-loss, shadowing).

]]>The better you know the channel vector to a terminal, the better you can direct a beam towards that terminal. This leads to a power gain. The more antennas you have, the more directive the beams is, which also leads to a power gain.

]]>When we talk about channel hardening, we are only considering one user channel and the beamforming selected to communicate over that channel.

The interfering channels will typically not harden.

]]>As you say, it is common that people normalize the noise power to 1 to reduce the amount notation i their papers. This means that you include the noise variance in the transmit power term or pathloss coefficient instead. For example, one can define the SNR as p*c/1=p*c, where c=b/sigma^2 is the normalized pathloss coefficient, and 1 is the normalized noise variance.

]]>Most current works on Massive MIMO I have come across model noise as a complex gaussian random variable with 0 mean and unit variance (in linear scale).

My question is why is noise power considered to be 1 in most works?

]]>* Yes, if you with “transpose” mean the “conjugate transpose” (also known as “Hermitian transpose”). The fact that the diagonal elements converge to deterministic constants proves the channel hardening. The fact that the off-diagonal elements converges to zero proves the favorable propagation.

* The proof is based on that M->infinity and K is constant. A consequence from this is that M>>K (infinity is much larger than any constant…).

]]>* Another question is: with an uncorrelated Rayleigh fading channel matrix H (MxK) (with variance 1): transpose(H)*H/M = Identity matrix (KxK) if M goes to infinity. Does it means this channel is both favorable and hardens?

* I have seen in a lot of massive MIMO paper, they claim that transpose(H)*H/M = Identity matrix (KxK) if M goes to infinity and M>>K. But why do we need M>>K, because I saw in the paper “Energy and spectral efficiency of very large multiuser MIMO system”, they claim that a very large M is enough to get: transpose(H)*H/M = Identity matrix (KxK).

]]>Correlated channels harden more slowly, due to the eigenvalue variations in the covariance matrix. But if the two conditions in Assumption 1 in https://arxiv.org/pdf/1705.00538.pdf hold, we will get asymptotic channel hardening anyway.

In practice, I think you will have a finite-sized area where you can deploy antenna. I would then deploy as many antennas as I can with half-wavelength spacing. Adjacent antennas will have correlated channel coefficients, but it is better to have these antennas than to deploy fewer antennas with a larger antenna spacing.

]]>While reading the piece, I was wondering whether there are any requirements on the spacing of the antenna array elements wrt the carrier wave length? Being too close could mean higher correlation which would then break the assumption behind the probability calculation you made.

]]>If you would instead consider correlated Rayleigh fading, then the MSE per antenna will reduce as you add more antennas.

]]>Does the channel hardening of massive MIMO improves the error mean of MMSE estimator?

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