## 1 Introduction
### Motivation and Contribution  
Due to the benefit of sharing SE and achieving EE through the combination of NOMA and RF-EH, evaluating the performance of integrated systems of IoT networks has become more difficult and has garnered attention in several recent studies. In [44], the authors investigated the optimal sum throughput (STP) of SWIPT IoT relay NOMA systems in relation to the TS factor. The maximum throughput for the PB-assisted EH NOMA multiuser relaying systems across Nakagami-m channels was examined in [45] in order to enhance the NOMA IoT-based system performance. In the meanwhile, with faulty CSI and hardware impairment, the throughput and OP of cooperative PB-assisted EH were studied in [46]. In a recent study, ref. [47] looked into the cooperative multiple PBs' OP for uplink NOMA systems in wirelessly powered IoT applications. However, these works do not consider DNN methods to be able to predict with a low latency and high accuracy, towards practical real-time configurations of C-NOMA IoT networks.  
Based on these advantages, we propose a wireless sensor-powered NOMA IoT network under imperfect channel state information (CSI). Furthermore, the PB transmits energy to both the BS and relay to transmit the information. Subsequently, the exact OP is derived to evaluate the outage performance of the proposed network. In particular, we employ the DNN model to predict the performance of the considered system to reduce the complexity of the simulation and calculation. The key differences between our study and previous research are summarized in Table 1. The main contribution of our paper can be summarized as follows:  
* We investigate a novel wireless sensor-powered NOMA IoT network, where a PB adopts the TS protocol to transmit the energy to both BS and relaying to transmit information. In particular, the imperfect CSI is considered in the information transmission phase to estimate the complex channel intricacies.
* We analyze the performance in terms of outage probability (OP). To obtain more insight into the considered network, the asymptotic expression OP and diversity order are given. Based on the asymptotic expression OP, we show the main parameters that affect the considered network in high SNR.
* We design the DNN frame to reduce the complexity of the Monte Carlo simulation and the traditional analysis towards practical real-time configurations. The DNN models are demonstrated to be efficient in predicting performance in complicated network scenarios using a low-latency inference technique.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Our Work** & [44] & [45] & [46] & [47] & [48] & [49] \\ \hline NOMA & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline Energy harvesting & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline Imperfect CSI & ✓ & & & ✓ & & & \\ \hline Outage probability analysis & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline Diversity order & ✓ & & & ✓ & & & \\ \hline DNN method & ✓ & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of this work with the reference works The remainder of this work is organized as follows. Section 2 describes the proposed system model. The performance of the proposed system is given in Section 3. The numerical findings of our suggested system are presented in Section 5. Finally, the conclusion is summarized in Section 6.