Large-Scale-Fading Decoding in Cellular Massive MIMO Systems with Spatially Correlated Channels

Massive multiple-input–multiple-output (MIMO)
systems can suffer from coherent intercell interference due to
the phenomenon of pilot contamination. This paper investigates
a two-layer decoding method that mitigates both coherent and
non-coherent interference in multi-cell Massive MIMO. To this
end, each base station (BS) first estimates the channels to intracell
users using either minimum mean-squared error (MMSE) or
element-wise MMSE (EW-MMSE) estimation based on uplink
pilots. The estimates are used for local decoding on each BS
followed by a second decoding layer where the BSs cooperate
to mitigate inter-cell interference. An uplink achievable spectral
efficiency (SE) expression is computed for arbitrary two-layer
decoding schemes. A closed-form expression is then obtained
for correlated Rayleigh fading, maximum-ratio combining, and
the proposed large-scale fading decoding (LSFD) in the second
layer. We also formulate a sum SE maximization problem with
both the data power and LSFD vectors as optimization variables.
Since this is an NP-hard problem, we develop a low-complexity
algorithm based on the weighted MMSE approach to obtain a
local optimum. The numerical results show that both data power
control and LSFD improve the sum SE performance over singlelayer
decoding multi-cell Massive MIMO systems