TY - JOUR
T1 - Accelerated Randomized Methods for Receiver Design in Extra-Large Scale MIMO Arrays
AU - Rodrigues, Victor Croisfelt
AU - Amiri, Abolfazl
AU - Abrão, Taufik
AU - De Carvalho, Elisabeth
AU - Popovski, Petar
N1 - This work was supported in part by the National Council for Scientific
and Technological Development (CNPq) of Brazil, Grant 310681/2019-7, in
part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior,
Brazil (CAPES), Financial Code 001 (88887.461434/2019-00), in part by the
CONFAP-ERC Agreement H2020, Brazil, and in part by the Danish Council
for Independent Research DFF-701700271.
PY - 2021
Y1 - 2021
N2 - 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 article, 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.
AB - 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 article, 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.
KW - Antenna arrays
KW - Approximation algorithms
KW - Complexity theory
KW - MIMO communication
KW - Mathematical model
KW - Receivers
KW - Signal processing algorithms
KW - massive MIMO; extra-large scale massive MIMO; randomized Kaczmarz algorithm; receiver design
UR - http://www.scopus.com/inward/record.url?scp=85107173736&partnerID=8YFLogxK
U2 - 10.1109/TVT.2021.3082520
DO - 10.1109/TVT.2021.3082520
M3 - Journal article
SN - 0018-9545
VL - 70
SP - 6788
EP - 6799
JO - I E E E Transactions on Vehicular Technology
JF - I E E E Transactions on Vehicular Technology
IS - 7
M1 - 9437708
ER -