
RIS-Assisted NOMA Systems: Performance Analysis under HWI and Channel Estimation Error
Author(s) -
Merve Ucar-Gul,
Mustafa Namdar,
Ozgur Ergul
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3590655
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper inspects a reconfigurable intelligent surface (RIS)-aided non-orthogonal multiple access (NOMA) wireless network where users convey to the base station (BS) through the support of RIS. The study investigates the impact of channel estimation error (CEE) and hardware impairment (HWI) at BS and end users in this RIS-enabled NOMA scheme. Additionally, phase errors in the RIS and the influence of imperfect successive interference cancellation (SIC) on NOMA users are incorporated into the analysis. Exact closed-form analytical expressions for the outage probability (OP) and ergodic rate (ER) of theNOMA users are derived to evaluate system performance. Furthermore, the asymptotic OP was also examined. The theoretical findings are validated through simulations, which demonstrate that I) HWI and CEE significantly affect the OP of the NOMA near user (NU) more than far user (FU); II) CEE impacts the OP of FU more than HWI; III) the effect of phase noise at the RIS on OP is substantially less significant than that of transceiver HWI and imperfect SIC; IV) the number of RIS reflecting elements plays a crucial role in enhancing the system performance of the RIS-assisted NOMA system; V) varying power allocation coefficient between users can improve user fairness.
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