  Signal detection in large multiple-input multiple-output (large-MIMO) systems
presents greater challenges compared to conventional massive-MIMO for two
primary reasons. First, large-MIMO systems lack favorable propagation
conditions as they do not require a substantially greater number of service
antennas relative to user antennas. Second, the wireless channel may exhibit
spatial non-stationarity when an extremely large aperture array (ELAA) is
deployed in a large-MIMO system. In this paper, we propose a scalable iterative
large-MIMO detector named ANPID, which simultaneously delivers 1) close to
maximum-likelihood detection performance, 2) low computational-complexity
(i.e., square-order of transmit antennas), 3) fast convergence, and 4)
robustness to the spatial non-stationarity in ELAA channels. ANPID incorporates
a damping demodulation step into stationary iterative (SI) methods and
alternates between two distinct demodulated SI methods. Simulation results
demonstrate that ANPID fulfills all the four features concurrently and
outperforms existing low-complexity MIMO detectors, especially in highly-loaded
large MIMO systems.
