Non-Orthogonal Multiple Access (NOMA) has been proposed recently as an emerging radio access technology for the Fifth Generation (5G) to achieve high spectral efficiency (SE). In addition, simultaneous wireless information and power transfer (SWIPT) has been receiving exceptional attention because of its role in increasing energy efficiency (EE). In this paper, the performance of the downlink SWIPT-NOMA system has been evaluated. In this paper, signal to interference and noise ratio (SINR) is derived for near and far users with outage probability for each user, where the near user acts as an energy harvesting (EH) node. The Genetic algorithm (GA) is used as an optimization technique for the power splitting ratio and power allocation coefficients to maximize the EE under eligible SE. The outage probability for the near and far user is taken into consideration for the optimization process. In this work, the results from the SE–EE metric show that the maximum EE reached 0.325 Mbits/J at SE of 9 bits/sec/Hz.

One of the most notable challenges in wireless communications is energy scarcity, which has attracted considerable attention in Fifth Generation (5G) wireless network research. This paper investigates the performance of energy harvesting (EH) relays under the best relay selection (BRS) scheme. The results show degradation of spectral efficiency (SE) due to EH relaying compared with conventional cooperative relaying (CR). Conversely, EH relaying provides a positive gain compared with conventional CR, increasing the lifetime of the network and decreasing energy consumption (EC) and operational cost. Moreover, the EH relaying network has better energy efficiency (EE) compared with conventional relaying networks. Results show that when EH relaying is applied, EE is improved through an increased number of relays. Finally, the SE-EE metric is presented for both conventional and EH relays. Results show that the performance of the proposed technique was able to achieve a maximum SE of 1.4 bits/s/Hz and maximum EE at 0.6 bits/s/Hz, and for the case of conventional relays, a maximum SE of 2 bits/s/Hz and EE at 1.1 bits/s/Hz. This result implies that the proposed EH scheme provides an optimum solution for energy-constrained wireless CR systems.

In the Industrial Internet of Things (IIoT), non-orthogonal multiple access (NOMA) has emerged as a viable multiple access method due to its superior efficiency. In this paper, a new power allocation technique for NOMA-enabled IIoT devices is presented with trade-offs between increasing energy efficiency and decreasing power consumption. We present a joint optimization of transmission rate and energy harvesting in simultaneous wireless information and power transfer (SWIPT) NOMA-enabled IIoT devices. With the power splitting (PS) approach, we examine how to improve overall transmission rate and harvested energy, simultaneously, while fulfilling the minimum rate and harvested energy needs of each IIoT device in a SWIPT-enabled NOMA system. An objective function is established by adding transmission rates obtained from information decoding and the transformed throughput from energy harvesting. The combination of management approaches with Industry 4.0 technology provides a viable strategy to decrease industrial production’s energy use. Several performance metrics may be utilized to study manufacturing process optimization. The efficiency of production equipment may be measured by looking at the overall effectiveness (OE) of the equipment in use. We divide the non-convex optimization problem into two sub-problems, based on the Lagrangian duality method, and solve them to find the optimal solution for the non-convex problem. The approach is validated based on physical layer parameter settings that represent potential factory of the future scenarios. Simulation results confirm the effectiveness of the presented method in a SWIPT-enabled NOMA system, provide considerable performance gains over the classic rate maximization strategy, and demonstrate the energy efficiency of the presented method compared with the conventional system. The results show huge potential of our solutions to reduce the future huge energy demand related to factory automation.

The development of mobile edge computing (MEC) is expected to offer better performance in mobile communications than the current cloud computing architecture. MEC involves offering the closest access to the data source or physical mobile network environment. The network services are able to respond faster, thus satisfying the demands of the mobile network industry when deploying various potential business applications in real-time. Since the harvested mobile data are transferred to the edge server to make calculations, data transfers and faults in the mobile network can be swiftly pinpointed and removed accurately. Nevertheless, there are still problems in the practical application of the systems, specifically in reducing delays and lessening energy consumption. Because of non-orthogonal multiple access (NOMA) superior spectrum efficiencies, it is best to combine NOMA with MEC for simultaneous support of multiple access for end users, thus reducing transmission latencies and lowering energy consumption. Combining MEC and NOMA would offer many advantages, including superior energy savings, reductions in latency, massive connectivity, and the potential of combining with additional transmission technologies, such as millimetre-wave (mmWave) and M-MIMO. In this paper, designing wireless resource allocation is crucial for an economically viable low-latency wireless network, which can be realised using the Karush–Kuhn–Tucker (KKT) approach to obtain the optimal solution for partial and full offloading network traffic scenarios to minimize the total latency of the MEC network. The convergence and performance for orthogonal multiple access (OMA), pure-NOMA (P-NOMA), and hybrid-NOMA (H-NOMA) are also compared under different network traffic offloading scenarios. The significant results from this study showed the convergence of the optimal resource allocation in the case of full and partial offloading. The results demonstrated that the P-NOMA reduces the total offloading delay by about 11%.