  Massive multiple-input-multiple-output (M-MIMO) features a capability for
spatial multiplexing of large number of users. This number becomes even more
extreme in extra-large (XL-MIMO), a variant of M-MIMO where the antenna array
is of very large size. Yet, the problem of signal processing complexity in
M-MIMO is further exacerbated by the XL size of the array. The basic processing
problem boils down to a sparse system of linear equations that can be addressed
by the randomized Kaczmarz (RK) algorithm. This algorithm has recently been
applied to devise low-complexity M-MIMO receivers; however, it is limited by
the fact that certain configurations of the linear equations may significantly
deteriorate the performance of the RK algorithm. In this paper, we embrace the
interest in accelerated RK algorithms and introduce three new RK-based
low-complexity receiver designs. In our experiments, our methods are not only
able to overcome the previous scheme, but they are more robust against
inter-user interference (IUI) and sparse channel matrices arising in the
XL-MIMO regime. In addition, we show that the RK-based schemes use a mechanism
similar to that used by successive interference cancellation (SIC) receivers to
approximate the regularized zero-forcing (RZF) scheme.
