  In this paper, we consider the downlink (DL) of a zero-forcing (ZF) precoded
extra-large scale massive MIMO (XL-MIMO) system. The base-station (BS) operates
with limited number of radio-frequency (RF) transceivers due to high cost,
power consumption and interconnection bandwidth associated to the fully digital
implementation. The BS, which is implemented with a subarray switching
architecture, selects groups of active antennas inside each subarray to
transmit the DL signal. This work proposes efficient resource allocation (RA)
procedures to perform joint antenna selection (AS) and power allocation (PA) to
maximize the DL spectral efficiency (SE) of an XL-MIMO system operating under
different loading settings. Two metaheuristic RA procedures based on the
genetic algorithm (GA) are assessed and compared in terms of performance,
coordination data size and computational complexity. One algorithm is based on
a quasi-distributed methodology while the other is based on the conventional
centralized processing. Numerical results demonstrate that the
quasi-distributed GA-based procedure results in a suitable trade-off between
performance, complexity and exchanged coordination data. At the same time, it
outperforms the centralized procedures with appropriate system operation
settings.
