Covert communication and physical layer security (PLS) have emerged as two essential pillars for safeguarding wireless networks against increasingly sophisticated eavesdropping and surveillance threats. This paper investigates a downlink hybrid power–frequency multiple access (HPMA) system aided by a friendly jammer, where a single source communicates with two legitimate users in the presence of a passive eavesdropper. By jointly exploiting the power and frequency domains, the proposed HPMA scheme achieves clear advantages in terms of covertness and secrecy performance compared to conventional orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) schemes. For performance analysis, we derive closed-form and approximated expressions for key metrics, including detection error probability (DEP), secrecy outage probability (SOP), effective secrecy throughput (EST), and average secrecy capacity (ASC), which reveal important trade-offs among resource allocation, jammer power, and secrecy reliability. To further reduce the computational burden of conventional analysis, a regression-based deep neural network (DNN) framework is developed to efficiently predict the secrecy performance of the considered system. Extensive Monte Carlo simulations validate the analytical results and confirm the superiority of the proposed HPMA scheme with friendly jamming. These findings provide useful insights for the design of future secure and covert wireless systems with low-complexity and intelligent physical-layer security requirements.

Ensuring reliable transmission and secure communication remains a critical challenge for next-generation wireless networks, particularly in the context of sixth-generation (6G) and Internet of Things (IoT) systems. This paper investigates the reliability and physical layer security of active reconfigurable intelligent surface (ARIS)-assisted dual-hop relaying in non-orthogonal multiple access (NOMA) networks over Nakagami-mfading channels. We develop a comprehensive system model where a base station communicates with two users via a relay and an ARIS, in the presence of a potential eavesdropper. Closed-form expressions for outage probability (OP) and intercept probability (IP) are derived for both near and far users, capturing the effects of ARIS configuration, power allocation, and channel fading. Extensive Monte Carlo simulations confirm the accuracy of the analytical results and reveal that increasing the number of ARIS elements, optimizing amplification factors, and carefully allocating power can significantly enhance both reliability and secrecy performance. The findings provide valuable insights for the design of robust and secure ARIS-assisted NOMA networks in practical wireless environments.

Mobile-edge computing (MEC) has emerged as a prominent technology to overcome sudden demands on computation-intensive applications of the Internet of Things (IoT) with finite processing capabilities. Nevertheless, the limited energy resources also seriously hinder IoT devices from offloading tasks that consume high power in active RF communications. Despite the development of energy harvesting (EH) techniques, the harvested energy from surrounding environments could be inadequate for power-hungry tasks. Fortunately, backscatter communications (Backcom) is an intriguing technology to narrow the gap between the power needed for communication and harvested power. Motivated by these considerations, this article investigates a backscatter-assisted data offloading in OFDMA-based wireless-powered (WP) MEC for IoT systems. Specifically, we aim at maximizing the sum computation rate by jointly optimizing the transmit power at the gateway (GW), backscatter coefficient, time-splitting (TS) ratio, and binary decision-making matrices. This problem is challenging to solve due to its nonconvexity. To find solutions, we first simplify the problem by determining the optimal values of transmit power of the GW and backscatter coefficient. Then, the original problem is decomposed into two subproblems, namely, TS ratio optimization with given offloading decision matrices and offloading decision optimization with given TS ratio. Especially, a closed-form expression for the TS ratio is obtained which greatly enhances the CPU execution time. Based on the solutions of the two subproblems, an efficient algorithm, termed the fast-efficient algorithm (FEA), is proposed by leveraging the block coordinate descent method. Then, it is compared with exhaustive search (ES), the bisection-based algorithm (BA), edge computing (EC), and local computing (LC) used as reference methods. As a result, the FEA is the best solution which results in a near-globally-optimal solution at a much lower complexity as compared to benchmark schemes. For instance, the CPU execution time of FEA is about 0.029 s in a 50-user network, which is tailored for ultralow latency applications of IoT networks.

In this study, a cooperative non‐orthogonal multiple access (NOMA) scheme is investigated in an underlay cognitive radio network. With this aim, a number of secondary users are concerned in the cooperative NOMA, in which a user with strong channel gains is properly selected (to act as a relay) by a multi‐antenna base station ( ) for assisting another user with poor channel gains in the presence of a primary network. Closed‐form expressions for the outage probability of the secondary network are derived, based on which the asymptotic outage behaviours of each secondary user assuming various realistic cases are discussed. Our analytical results clearly reveal that an outage floor may exist in the outage probability of the secondary users, being determined by the interference constraint and the number of antennas at the . The impact of the multiple antennas and the number of cooperative NOMA users on the system performance is examined, and it shows that the cell‐edge user under poor channel gains can benefit from both the cooperative NOMA and opportunistic relay transmission.

In this study, the performance of energy harvesting systems in the presence of unreliable backhaul links is investigated over independent but not necessarily identically distributed Nakagami‐ m fading channels. In particular, the energy‐constrained relay uses the amount of harvested energy from the best small‐cell transmitter based on time switching‐based relaying protocol to process for the next hop transmission. The authors derived the closed‐form expressions of the outage probability and the effective throughput with two distinct transmission schemes: (i) delay‐limited transmission, and (ii) delay‐tolerance transmission are attained. In order to assess the impacts of unreliable backhaul links, they thus obtain the asymptotic expression of the outage probability in high signal‐to‐noise ratio (SNR) regime. The numerical results are conducted to analyse the effects of energy harvesting fraction time, energy efficiency, backhaul reliability, and the fading parameters on the system performance. The authors' results show that under the unreliable backhaul links the outage probability yields the error‐floor in the high SNR regime which demonstrates the significant impact of the backhaul unreliability.

In this research, the authors investigate the outage probability (OP) of the secondary network in a cognitive wireless powered communication network. Energy‐constrained secondary users harvest energy from a hybrid access‐point (H‐AP) and the primary transmitter in the first phase. In the second phase, they select a secondary user based on two different schemes, namely the best uplink channel selection (UCS) and the minimal interference channel selection (MICS), to transfer information to the H‐AP. The secondary network can share the same spectrum with the primary network ensuring that a desired OP constraint in the primary network is always met. This constraint represents the quality‐of‐service (QoS) of the primary network. The analytical expressions and asymptotic expressions of the OP of the secondary network are derived. The result shows that increasing the number of secondary users can considerably improve system performance. The transmit power of the selected secondary user, energy harvesting time and relaxing the QoS constraint of the primary network have a significant impact on the OP of the secondary network. The results show that UCS outperforms MICS.