238 research outputs found
Large System Analysis of Power Normalization Techniques in Massive MIMO
Linear precoding has been widely studied in the context of Massive
multiple-input-multiple-output (MIMO) together with two common power
normalization techniques, namely, matrix normalization (MN) and vector
normalization (VN). Despite this, their effect on the performance of Massive
MIMO systems has not been thoroughly studied yet. The aim of this paper is to
fulfill this gap by using large system analysis. Considering a system model
that accounts for channel estimation, pilot contamination, arbitrary pathloss,
and per-user channel correlation, we compute tight approximations for the
signal-to-interference-plus-noise ratio and the rate of each user equipment in
the system while employing maximum ratio transmission (MRT), zero forcing (ZF),
and regularized ZF precoding under both MN and VN techniques. Such
approximations are used to analytically reveal how the choice of power
normalization affects the performance of MRT and ZF under uncorrelated fading
channels. It turns out that ZF with VN resembles a sum rate maximizer while it
provides a notion of fairness under MN. Numerical results are used to validate
the accuracy of the asymptotic analysis and to show that in Massive MIMO,
non-coherent interference and noise, rather than pilot contamination, are often
the major limiting factors of the considered precoding schemes.Comment: 12 pages, 3 figures, Accepted for publication in the IEEE
Transactions on Vehicular Technolog
Asymptotic Analysis of Multicell Massive MIMO over Rician Fading Channels
This work considers the downlink of a multicell massive MIMO system in which
base stations (BSs) of antennas each communicate with
single-antenna user equipments randomly positioned in the coverage area. Within
this setting, we are interested in evaluating the sum rate of the system when
MRT and RZF are employed under the assumption that each intracell link forms a
MIMO Rician fading channel. The analysis is conducted assuming that and
grow large with a non-trivial ratio under the assumption that the data
transmission in each cell is affected by channel estimation errors, pilot
contamination, and an arbitrary large scale attenuation. Numerical results are
used to validate the asymptotic analysis in the finite system regime and to
evaluate the network performance under different settings. The asymptotic
results are also instrumental to get insights into the interplay among system
parameters.Comment: 7 pages, 2 figures, submitted to GLOBECOM16, Washington, DC USA.
arXiv admin note: text overlap with arXiv:1601.0702
Jamming Resistant Receivers for Massive MIMO
We design jamming resistant receivers to enhance the robustness of a massive
MIMO uplink channel against jamming. In the pilot phase, we estimate not only
the desired channel, but also the jamming channel by exploiting purposely
unused pilot sequences. The jamming channel estimate is used to construct the
linear receive filter to reduce impact that jamming has on the achievable
rates. The performance of the proposed scheme is analytically and numerically
evaluated. These results show that the proposed scheme greatly improves the
rates, as compared to conventional receivers. Moreover, the proposed schemes
still work well with stronger jamming power.Comment: Accepted in the 42nd IEEE Int. Conf. Acoust., Speech, and Signal
Process. (ICASSP2017
Massive MIMO has Unlimited Capacity
The capacity of cellular networks can be improved by the unprecedented array
gain and spatial multiplexing offered by Massive MIMO. Since its inception, the
coherent interference caused by pilot contamination has been believed to create
a finite capacity limit, as the number of antennas goes to infinity. In this
paper, we prove that this is incorrect and an artifact from using simplistic
channel models and suboptimal precoding/combining schemes. We show that with
multicell MMSE precoding/combining and a tiny amount of spatial channel
correlation or large-scale fading variations over the array, the capacity
increases without bound as the number of antennas increases, even under pilot
contamination. More precisely, the result holds when the channel covariance
matrices of the contaminating users are asymptotically linearly independent,
which is generally the case. If also the diagonals of the covariance matrices
are linearly independent, it is sufficient to know these diagonals (and not the
full covariance matrices) to achieve an unlimited asymptotic capacity.Comment: To appear in IEEE Transactions on Wireless Communications, 17 pages,
7 figure
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