  This paper focuses on new communication paradigms arising in massive
multiple-input-multiple-output systems where the antenna array at the base
station is of extremely large dimension (xMaMIMO). Due to the extreme dimension
of the array, xMaMIMO is characterized by spatial non-stationary field
properties along the array; this calls for a multi-antenna transceiver design
that is adapted to the array dimension but also its non-stationary properties.
We address implementation aspects of xMaMIMO, with computational efficiency as
our primary objective. To reduce the computational burden of centralized
schemes, we distribute the processing into smaller, disjoint subarrays. Then,
we consider several low-complexity data detection algorithms as candidates for
uplink communication in crowded xMaMIMO systems. Drawing inspiration from coded
random access, one of the main contributions of the paper is the design of low
complexity scheme that exploits the non-stationary nature of xMaMIMO systems
and where the data processing is decentralized. We evaluate the bit-error-rate
performance of the transceivers in crowded xMaMIMO scenarios. The results
confirm their practical potential.
