Abstract
With the given scope for new use cases and the demanding needs of future 6th generation (6G) wireless networks, the development of wireless communications looks exciting. The propagation medium has been viewed as a randomly behaving entity between the transmitter and the receiver since traditional wireless technology, degrading the quality of the received signal due to the unpredictable interactions of the broadcast radio waves with the surrounding objects. On the other hand, network operators could now manipulate electromagnetic radiation to remove the negative impacts of natural wireless propagation due to the recent arrival of reconfigurable intelligent surfaces (RIS) in wireless communications. According to recent findings, the RIS mechanism benefits nonorthogonal multiple access (NOMA), which can effectively deliver effective transmissions. For simple design, of RIS‐NOMA system, fixed power allocation scheme for NOMA is required. The main system performance metric, i.e., outage probability, needs to be considered to look at the efficiency and capability of transmission mode relying on RIS and NOMA schemes, motivated by the potential of these developing technologies. As major performance metrics, we derive analytical representations of outage probability, and throughput and an accurate approximation is obtained for the outage probability. Numerical results are conducted to validate the exactness of the theoretical analysis. It is found that increasing the higher number of reflecting elements in the RIS can significantly boost the outage probability performance, and the scenario with only the RIS link is also beneficial. In addition, it is desirable to deploy the RIS‐NOMA since it is indicated that better performance compared with the traditional multiple access technique.
Highlights
Due to high demands in terms of system capacity and spectrum efficiency, the traditional orthogonal multiple access (OMA) has been unable to meet the user needs to be associated with the rapid growth of Internet of Things (IoT) and mobile communications [1,2,3,4,5,6,7]
Since more complicated computations regarding reconfigurable intelligent surfaces (RIS) which is the form of a reflect-array comprisingNsimple and reconfigurable reflector elements, and more matrix variables in computations, unlike other published work dealing with the calculation of symbol error probability (SEP) [34], our work focuses on main metric, i.e., outage performance evaluation of the RIS-aided nonorthogonal multiple access (NOMA) system [35] to determine which scenario exhibiting better performance
We study two practical situations for deployment of RIS and NOMA in wireless system
Summary
Due to high demands in terms of system capacity and spectrum efficiency, the traditional orthogonal multiple access (OMA) has been unable to meet the user needs to be associated with the rapid growth of Internet of Things (IoT) and mobile communications [1,2,3,4,5,6,7]. The authors in [13] deployed the relaying scheme for the secondary network of the considered CR-NOMA, and the relay can energy harvesting (EH) from the secondary transmitter to serve signal forwarding to distant secondary users They studied the complex model of EH-assisted CR-NOMA in terms of outage behavior and throughput performance when has imperfect successive interference cancellation (SIC). Reference [14] presented relay-aided CR-NOMA networks to improve the performance of far users by enabling partial relay selection architecture They explored system performance in terms of full-duplex (FD). It is demonstrated in this work that the outage probability of the system mainly relying on the number of metasurfaces in RIS (iii) The derivations of asymptotic outage probabilities at high transmit signal-to-noise ratio (SNR) for two users are provided as an important evaluation to design such the RIS-aided NOMA system in practice. Compared with orthogonal multiple access- (OMA-) assisted RIS system, the considered system exhibits more benefits, and it becomes a prominent candidate to implement for forthcoming networks
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