## 1 Introduction
[3] in which the secondary users harvest energy in the first phase and transmit their uplink information with NOMA in the second phase under the presence of the eavesdropper. The authors proposed the secrecy energy efficiency (SEE) maximization problem under the constraints of minimum data rate, maximum interference power to the primary users (PUs) and maximum secrecy outage probability. However, none of the researchers studied SEE maximization in a downlink CR-NOMA system with cooperative relaying and an EH user. The importance of the EH user lies in powering the user terminal expected in 5G applications, such as those in the Internet of Things (IoT) [12]. In this paper, we consider the EH user to be a receiver that stores energy from RF signals. With the above motivations, and because energy efficiency is a crucial factor for future wireless networks, we investigate a downlink CR-NOMA scheme to maximize the SEE with cooperative relaying, subject to quality of service (QoS) requirements. We propose a particle swarm optimization (PSO)-based algorithm to solve the optimization problem, which has advantages over the optimal exhaustive search method, such as low computational complexity and high accuracy. Moreover, in the literature, application of PSO in wireless communications networks has shown high performance in resolving optimization problems [8; 13]. The main contributions of this paper are summarized as follows. * Since we focus on enhancing the PLS (and to enable sustainable 5G networks), we propose maximizing the SEE of the CR-NOMA system with cooperative relaying and an EH user to prevent eavesdropper wiretaps by satisfying the following QoS requirements: minimum required energy at the EH user, a minimum data rate for secondary users, the maximum permissible transmission power at the relay, and a transmitter that avoids interference with the primary user. * To reduce the computation complexity of the solution, we solve the SEE maximization problem with a PSO-based algorithm that provides high-accuracy outcomes and high convergence speed. In addition, we provide the mathematical boundaries for the variables of the proposed optimization problem. The simulation results show that the proposed PSO algorithm achieves outcomes very close to values obtained by the high computational-complexity exhaustive search method. * We solve the SEE maximization problem for a CR orthogonal multiple access (CR-OMA) scheme to compare it with our proposed CR-NOMA scheme. Similar to the CR-NOMA system, we also optimize the power allocation variables of each OMA user. Simulation results show that our proposed scheme based on NOMA outperforms the OMA scheme, where an improvement in the SEE of around 40% to more than 100% is achieved by NOMA compared with OMA. The rest of this paper is organized as follows. The CR-NOMA network model with an EH user is described in Section 2. In Section 3, the SEE maximization problem in the CR-NOMA network is formulated, and the PSO-based power allocation scheme for SEE maximization is described. The comparison approach of SEE maximization in the CR-OMA scheme is studied in Section 4. Simulation results of the cooperative CR-NOMA network with an EH user are presented in Section 5. Finally, the conclusion is presented in Section 6. Table 1 lists the main abbreviations used throughout the paper.