  Future cellular systems will likely employ massive bi-dimensional arrays to
improve performance by large array gain and more accurate spatial filtering,
motivating the design of low-complexity signal processing methods. We propose
optimising a Kronecker-separable beamforming filter that takes advantage of the
bi-dimensional array geometry to reduce computational costs. The Kronecker
factors are obtained using two strategies: alternating optimisation, and
sub-array minimum mean square error beamforming with Tikhonov regularization.
According to the simulation results, the proposed methods are computationally
efficient but come with source recovery degradation, which becomes negligible
when the sources are sufficiently separated in space.
