TY - JOUR
T1 - IRS-Assisted Massive MIMO-NOMA Networks:
T2 - Exploiting Wave Polarization
AU - S. de Sena, Arthur
AU - Henrique Juliano Nardelli, Pedro
AU - Costa, Daniella
AU - M. Lima, Rafael
AU - Liang, Yang
AU - Popovski, Petar
AU - Ding, Zhiguo
AU - Papadias, Constantinos
PY - 2021
Y1 - 2021
N2 - A dual-polarized intelligent reflecting surface (IRS) can contribute to a better multiplexing of interfering wireless users. In this paper, we use this feature to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC). By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain. Our novel strategy alleviates the impact of imperfect SIC and enables users to exploit polarization diversity with near-zero inter-subset interference. To this end, the IRSs are optimized to mitigate transmissions originated at the BS from the interfering polarization. The formulated optimization is transformed into quadratically constrained quadratic sub-problems, which makes it possible to obtain the optimal solution via interior-points methods. We also derive analytically a closed-form expression for the users’ ergodic rates by considering large numbers of reflecting elements. This is followed by representative simulation examples and comprehensive discussions. The results show that when the IRSs are large enough, the proposed scheme always outperforms conventional massive MIMO-NOMA and MIMO-OMA systems even if SIC error propagation is present. It is also confirmed that dual-polarized IRSs can make cross-polar transmissions beneficial to the users, allowing them to improve their performance through diversity.
AB - A dual-polarized intelligent reflecting surface (IRS) can contribute to a better multiplexing of interfering wireless users. In this paper, we use this feature to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC). By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain. Our novel strategy alleviates the impact of imperfect SIC and enables users to exploit polarization diversity with near-zero inter-subset interference. To this end, the IRSs are optimized to mitigate transmissions originated at the BS from the interfering polarization. The formulated optimization is transformed into quadratically constrained quadratic sub-problems, which makes it possible to obtain the optimal solution via interior-points methods. We also derive analytically a closed-form expression for the users’ ergodic rates by considering large numbers of reflecting elements. This is followed by representative simulation examples and comprehensive discussions. The results show that when the IRSs are large enough, the proposed scheme always outperforms conventional massive MIMO-NOMA and MIMO-OMA systems even if SIC error propagation is present. It is also confirmed that dual-polarized IRSs can make cross-polar transmissions beneficial to the users, allowing them to improve their performance through diversity.
KW - Antenna arrays
KW - Array signal processing
KW - Interference
KW - Massive MIMO
KW - Multi-polarization
KW - NOMA
KW - Silicon carbide
KW - Transmitting antennas
KW - Wireless communication
KW - intelligent reflecting surfaces
UR - http://www.scopus.com/inward/record.url?scp=85107236455&partnerID=8YFLogxK
U2 - 10.1109/TWC.2021.3081419
DO - 10.1109/TWC.2021.3081419
M3 - Journal article
SN - 1536-1276
VL - 20
SP - 7166
EP - 7183
JO - I E E E Transactions on Wireless Communications
JF - I E E E Transactions on Wireless Communications
IS - 11
M1 - 9440813
ER -