TY - JOUR
T1 - Large intelligent surface-assisted nonorthogonal multiple access for 6G networks
T2 - Performance analysis
AU - Bariah, Lina
AU - Muhaidat, Sami
AU - Sofotasios, Paschalis C.
AU - Bouanani, Faissal El
AU - Dobre, Octavia A.
AU - Hamouda, Walaa
N1 - Funding Information:
Manuscript received August 5, 2020; revised October 18, 2020 and December 1, 2020; accepted January 26, 2021. Date of publication February 5, 2021; date of current version March 24, 2021. This work was supported in part by Khalifa University under Grant EX2020-037-8434000382 and Grant EX2020-038-8434000383. The work of Octavia A. Dobre was supported in part by the Natural Sciences and Engineering Research Council of Canada, through its Discovery program. (Corresponding author: Sami Muhaidat.) Lina Bariah is with the KU Center for Cyber-Physical Systems, Department of Electrical and Computer Engineering, Khalifa University, Abu Dhabi, UAE (e-mail: [email protected]).
Publisher Copyright:
© 2014 IEEE.
PY - 2021/4/1
Y1 - 2021/4/1
N2 - Large intelligent surface (LIS) has recently emerged as a potential enabling technology for 6G networks, offering extended coverage and enhanced energy and spectral efficiency. In this work, motivated by its promising potentials, we investigate the error rate performance of LIS-assisted nonorthogonal multiple access (NOMA) networks. Specifically, we consider a downlink NOMA system, in which data transmission between a base station (BS) and L NOMA users is assisted by an LIS comprising M reflective elements (REs). First, we derive the probability density function (PDF) of the end-to-end wireless fading channels between the BS and NOMA users. Then, by leveraging the obtained results, we derive an approximate expression for the pairwise error probability (PEP) of NOMA users under the assumption of imperfect successive interference cancellation. Furthermore, accurate expressions for the PEP for M = 1 and large M values ( M > 10 ) are presented in closed-form. To gain further insights into the system performance, an asymptotic expression for PEP in high signal-to-noise ratio regime, asymptotic diversity order, and tight union bound on the bit error rate are provided. Finally, numerical and simulation results are presented to validate the derived mathematical results.
AB - Large intelligent surface (LIS) has recently emerged as a potential enabling technology for 6G networks, offering extended coverage and enhanced energy and spectral efficiency. In this work, motivated by its promising potentials, we investigate the error rate performance of LIS-assisted nonorthogonal multiple access (NOMA) networks. Specifically, we consider a downlink NOMA system, in which data transmission between a base station (BS) and L NOMA users is assisted by an LIS comprising M reflective elements (REs). First, we derive the probability density function (PDF) of the end-to-end wireless fading channels between the BS and NOMA users. Then, by leveraging the obtained results, we derive an approximate expression for the pairwise error probability (PEP) of NOMA users under the assumption of imperfect successive interference cancellation. Furthermore, accurate expressions for the PEP for M = 1 and large M values ( M > 10 ) are presented in closed-form. To gain further insights into the system performance, an asymptotic expression for PEP in high signal-to-noise ratio regime, asymptotic diversity order, and tight union bound on the bit error rate are provided. Finally, numerical and simulation results are presented to validate the derived mathematical results.
KW - 6G
KW - asymptotic diversity order
KW - bit error rate (BER)
KW - large intelligent surfaces (LISs)
KW - nonorthogonal multiple access (NOMA)
KW - pairwise error probability (PEP)
KW - union bound
UR - http://www.scopus.com/inward/record.url?scp=85100835822&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2021.3057416
DO - 10.1109/JIOT.2021.3057416
M3 - Article
AN - SCOPUS:85100835822
SN - 2327-4662
VL - 8
SP - 5129
EP - 5140
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 7
M1 - 9348935
ER -