# Computational-Intelligence-Based Spectrum-Sharing Scheme for NOMA-Based Cognitive Radio Networks
## 1 Introduction
### Contributions  
In this article, owing to the overlay approach of a truly win-win situation for both primary and secondary networks, a NOMA-assisted power-domain cooperative overlay spectrum-sharing framework is developed for downlink transmission in CRNs. In the proposed scheme, the information for the PU in the absence of DL is retransmitted through the SU selected from the secondary network, in addition to the secondary NOMA relay. The main contributions of this work are as follows. * For a dual-hop downlink CRN operating in half-duplex mode, a novel NOMA-assisted spectrum-sharing scheme is proposed in which a secondary NOMA relay (SR) first transmits the information for the PU and multiple SUs to the corresponding destinations. Then, a single best SU retransmits the primary signal in order to enhance QoS using maximal ratio combining (MRC), while the primary base station (PBS) transmits the next frame for the PU to the SR at the same time. The SU selection is based on the best channel condition for the PU. * For the implementation of the proposed scheme, an enhanced version of ABC, referred to here as the enhanced-artificial-bee-colony (EABC)-based power allocation scheme, is proposed to overcome the limitations of classic ABC. * To validate the effectiveness of the proposed EABC-based scheme, its performance is compared with the classic ABC and with the existing competent EA-based techniques in the literature, i.e., GA and PSO. It is clearly observed through simulations that EABC outsmarts the traditional version and other global optimizers in terms of convergence time and in achieving a higher sum rate while consuming minimum transmit power. * The performance of the proposed scheme is validated by varying the transmit power at the NOMA relay, the rate threshold of the PU, and the number of SUs. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref.** & **Year** & **Major Focus** & **Primary DL** & **Performance Analysis** \\ \hline
[24] & 2020 & Coordinate direct and secondary relay transmission to assist weak PU & Yes &
\begin{tabular}{c} OP and ergodic sum capacity analysis \\ through Monte Carlo simulations showed \\ improved performance compared to \\ conventional NOMA networks \\ \end{tabular} \\ \hline
[25] & 2022 & Direct and relay transmission to assist cell-edge users & Yes &
\begin{tabular}{c} Better SIC and more accurate CSI required \\ to enhance OP and system capacity \\ \end{tabular} \\ \hline
[26] & 2018 & Enable primary communication through relay selection and power control & No &
\begin{tabular}{c} Improved secondary transmission rate \\ and total transmit power of the system, \\ but fairness among SRs is ignored \\ \end{tabular} \\ \hline
[27] & 2018 & Utilize NOMA with spatial modulation and antenna selection & Yes &
\begin{tabular}{c} Symbol error probability analysis through \\ Monte Carlo simulations showed \\ improved spectrum utilization efficiency, \\ but more multifaceted \\ \end{tabular} \\ \hline
[28] & 2018 & Exploit spatial diversity to overcome fading impairments & Yes &
\begin{tabular}{c} Improved OP and ergodic capacity \\ provided appropriate allocation of time \\ slots for cooperation \\ \end{tabular} \\ \hline
[29] & 2020 & Exploit spatial diversity through relay selection and combining technologies & Yes & \
\begin{tabular}{c} Improved OP and reduced transmit \\ power with increase in the number of SUs \\ as compared to conventional CR NOMA \\ networks, but performance depends on \\ location of the relay \\ \end{tabular} \\ \hline \multirow{4}{*}{-} & This Article & Enable primary communication under deep shadowing through secondary NOMA relay and single best SU from secondary network to exploit spatial diversity & No &
\begin{tabular}{c} Optimize the sum rate of SUs and total transmit power of the system using \\ different state-of-the-art CI tools (EABC, ABC, GA, and PSO) while guaranteeing \\ QoS at the primary network \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cont.