The advent of next-generation Internet of Things (IoT) networks necessitates communication capabilities characterized by ultra-reliability and low latency (URLLC) and energy efficiency requirements that traditional wireless designs frequently struggle to satisfy under practical constraints. In this context, realizing symbiotic IoT networks using mutualism backscattering technologies with short-packet transmissions has emerged as a viable solution to achieve the goals of net zero for sustainable IoT network deployment while satisfying URLLC conditions. Following that, this paper first develops theoretical frameworks for evaluating the performance of short packet transmissions in uplink symbiotic systems by deriving formulas for the block error rate (BLER) and total symbiotic ergodic rate under two diversity techniques, namely selection combining with maximal-ratio combining (SC-MRC) and full maximal-ratio combining (Full-MRC). Then, we scale up this considered system for large-scale IoT networks, where we propose an energy-aware resource allocation method using successive convex approximation (SCA) techniques for multi-user scenarios while adhering to URLLC conditions. Finally, simulation results are provided to validate the developed theoretical analyses as well as demonstrate how our proposed optimization solution achieves substantial improvements in energy efficiency performance. These findings lay a robust groundwork for developing scalable and dependable communication systems in future energy-efficient IoT eras.

In this paper, we investigate the performance of simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-enabled short-packet communication (SPC) systems that employ covert rate-splitting (RS) to facilitate applications of Internet-of-Things (IoT). Under the generalized model of the α-η-κ-μ fading, we analyze covertness by first deriving a closed-form expression for the warden’s detection error probability (DEP) and then deducing the optimal detection threshold at which the DEP is minimized. From this optimal DEP, we guide the choice of the feasible power-allocation (PA) region at which the warden’s produced DEP is always beyond the minimal acceptable covertness. On the other hand, we develop mathematical frameworks for evaluating the system’s block-error rate (BLER) and the ergodic rate (ER), as well as providing guidelines on how to access their performance limits at high signal-to-noise ratio, especially the diversity orders and ergodic slopes of the users. Furthermore, we also propose to enhance the system performance by jointly optimizing the PA and RS coefficients in order to: (1) minimize the maximum BLER across private users subject to a minimum covertness requirement and (2) maximize the minimum ER across users subject to covertness and decoding constraints. Numerical results confirm the analytical expressions and show that the proposed optimization efficiently tunes the PA and RS coefficients to achieve the BLER and ER fairness objectives.

In this article, we describe a novel active reconfigurable repeater-aided nonorthogonal multiple access networks within the context of the Internet of Things. The study focuses on a scenario, where a source simultaneously transmits public information to an untrusted user and a covert signal to a legitimate user in the surveillance of an external warden or eavesdropper. We develop comprehensive analytical and optimization frameworks to evaluate the reliability, security, and covertness of the proposed system’s performance, measuring three respective key metrics: 1) outage probability (OP); 2) secrecy OP (SOP); and 3) detection error probability (DEP). First, we derive exact closed-form and asymptotic expressions for OP, SOP in internal and external eavesdropping scenarios, and DEP in external monitoring situations. Based on an asymptotic analysis of the OP, we propose two optimization methods for power allocation (PA) to achieve fairness in outage among users: 1) a convex approximation method and 2) an approximate closed-form solution. We then introduce an alternative method for optimizing PA to improve SOP in both eavesdropping scenarios while maintaining minimal OP requirements. In addition, we propose an effective approach for determining the warden’s detection threshold to minimize the DEP, with low complexity and fast convergence, thereby improving communications covertness. Finally, we validate the theoretical and optimization frameworks through extensive Monte Carlo simulations, exploring the impact of key system parameters on each performance metric.

This work investigates the covertness and security performance of Internet-of-Things (IoTs) networks under Rayleigh fading environments. Specifically, a cellular source transmits covert information to cell-edge users with the assistance of an IoT master node, employing a coordinated direct and relay transmission strategy combined with non-orthogonal multiple access (NOMA). This approach not only enhances spectrum utilization but also generates friendly interference to complicate a warden’s surveillance or an eavesdropper’s decoding efforts. From a covertness perspective, we derive exact closed-form expressions for the detection error probability (DEP) under arbitrary judgment thresholds. We then identify the optimal judgment threshold for the worst-case scenario, at which the warden minimizes its DEP performance. Accordingly, we determine the effective region for user power allocation (PA) in NOMA transmission that satisfies the DEP constraint. From a security perspective, we derive analytical expressions for the secrecy outage probability under two eavesdropping strategies using selection combining and maximal ratio combining. Based on this analysis, we propose an adaptive PA scheme that maximizes covert rate while ensuring the quality-of-service (QoS) requirements of legitimate users, the system’s minimum covertness requirements, and supporting successive interference cancellation (SIC) procedures. Furthermore, we design an adaptive PA scheme that maximizes the secrecy rate while ensuring the QoS requirements of legitimate users and SIC conditions. Numerical results demonstrate the accuracy of the analytical framework, while the proposed optimization strategies effectively adjust PA coefficients to maximize either the covert rate or the secrecy rate.

This study investigates a two-way relaying non-orthogonal multiple access (TWR-NOMA) enabled Internet-of-Things (IoT) network, in which two NOMA users communicate via an IoT access point (IAP) relay using a decode-and-forward (DF) protocol. A power beacon (PB) is used to power the IAP to address the IAP's limited lifetime due to energy constraints. Since co-channel interference (CCI) is inevitable in IoT systems, this effect is also studied in the proposed system to improve practicality. Based on the proposed system model, the closed-form equations for the exact and asymptotic outage probability (OP) and ergodic data (ED) of the NOMA users' signals are first derived to describe the performance of TWR-NOMA systems. The system's diversity order and throughput are then evaluated according to the derived results. To further improve the system's performance, a low-complexity strategy 2D golden section search (GSS) is performed, subject to power allocation (PA) and time-switching (TS) factors, to optimize the outage performance. Finally, a deep learning design with minimal computing complexity and precision OP prediction is established for a real-time IoT network configuration. The numerical results are discussed and analyzed in terms of the effects of the CCI, the TS ratio, the PA factor, the fading parameter on the OP, system throughput, and ED.

By leveraging massive low-cost reconfigurable reflect array elements, intelligent reflecting surface (IRS) is recently proposed to exhibit the favorable wireless propagation environment of Internet of Things (IoT) systems. In this article, we provide a spectrum-efficiency approach by exploiting non-orthogonal multiple access (NOMA) as well as cognitive radio (CR) to form NOMA IRS-assisted CR system. In this IRS-based IoT, the active access point in secondary network transmits beamforming and the passive IRS elements are jointly operated to achieve different performance relying on demands of IoT devices, while maintaining the normal operation of primary network. Then, the exact closed-form formulas are introduced to evaluate outage probability at each IoT device. Moreover, to provide more insights of the system, a diversity order is considered aiming to look at limitation of outage performance when the system tries to increase average signal to noise ratio (SNR) at the secondary transmitter. Finally, we conduct numerical simulations to verify the superior performance of IoT systems with higher meta-surface elements at IRS over the necessary comparisons in practical scenarios.

With the introduction of wireless communications in a diverse range of security-sensitive scenarios such as healthcare, Smart Cities, internet-of-things (IoT) infrastructure, nuclear power plants, so forth, it has become necessary to protect the wireless network against malicious eavesdroppers via physical layer security (PLS). We analyze and study the impact of an eavesdropper located in an underlay cooperative cognitive radio network (CRN). A reconfigurable intelligent surface is used to improve the secrecy outage probability of the proposed system. CRs resolve spectrum scarcity by enabling spectrum sharing. On the other hand, RIS is a planar surface device equipped with signal enhancing reflecting elements that enhance signals at desired users and suppress signal power at undesired eavesdroppers in PLS networks. Therefore, the integration of RIS in cooperative underlay CR networks can enable secure wireless communications. To this end, we derive closed-form secrecy outage probability (SOP) expressions for a network that consists of a primary destination, secondary source, secondary user and a passive eavesdropper. The obtained equations are verified via simulation.

Fading is considered to be one of the major issues in wireless communications. The non-Orthogonal Multiple Access (NOMA) technique proved to be efficient enough to overcome the fading issues if utilized efficiently. Since the signals transmitted in NOMA are superimposed, with the help of Channel State Information (CSI), the Successive Interference Cancellation (SIC) technique is applied to separate each user's signal. A lot of researches have been going on to study the performance of the NOMA system in various fading channels such as Nakagami-m channel distribution, Rayleigh channel distribution, Rician fading channel distribution, etc. Very few studies were conducted on Weibull-channel distribution applied in the NOMA network. This letter studies performance of the Weibull-channel fading distribution applied in the NOMA network in presence of two users and the presence of a bi-directional communication link between the devices. The analytical expressions were obtained to study the performance efficiency of the system and extensive simulations were generated comparing the performance in various parameters.

Since Internet of Things (IoT) is suggested as the fundamental platform to adapt massive connections and secure transmission, we study physical-layer authentication in the point-to-point wireless systems relying on reconfigurable intelligent surfaces (RIS) technique. Due to lack of direct link from IoT devices (both legal and illegal devices) to the access point, we benefit from RIS by considering two main secure performance metrics. As main goal, we examine the secrecy performance of a RIS-aided wireless communication systems which show secure performance in the presence of an eavesdropping IoT devices. In this circumstance, RIS is placed between the access point and the legitimate devices and is designed to enhance the link security. To specify secure system performance metrics, we firstly present analytical results for the secrecy outage probability. Then, secrecy rate is further examined. Interestingly, we are to control both the average signal-to-noise ratio at the source and the number of metasurface elements of the RIS to achieve improved system performance. We verify derived expressions by matching Monte-Carlo simulation and analytical results.

There are high demands on both massive connections and high spectrum efficiency, and the cognitive radio‐based nonorthogonal multiple access (CR‐NOMA) system is developed to satisfy such demand. The unreal situation of CR‐NOMA is considering the perfect channel state information (CSI) in receivers. This paper indicates impacts of imperfect CSI on outage and throughput performance. In particular, we focus on performance of the secondary network related to the imperfect CSI, and we derive closed‐form expressions of outage probability and throughput for the downlink in such a CR‐NOMA system. Particularly, a general form of Nakagami‐m fading channel is adopted to examine the impact of fading on the performance of the CR‐NOMA system. As the main achievement, we conduct extensive simulations and provide analyses to demonstrate the outage performance of the CR‐NOMA system with CSI imperfections.

In this paper, we investigate improved spectrum concern by employing non-orthogonal multiple access (NOMA) scheme in cognitive radio (CR) network to form CR-NOMA and to serve many destination users. In secondary network of our proposed system, device-to-device (D2D) strategy is designed to support further transmission for NOMA users under impacts from interference from the primary network. Outage performance gap exists among these NOMA users since different power allocation factors assigned to the destinations. Unlike existing NOMA schemes as considering power allocation factors, which are not optimal in terms of outage performance, our proposed paradigm exhibits optimal outage in scenario of D2D transmission. In particular, the outage probability is first derived and approximate outage performance can be further achieved. Simulation results confirm exactness of the analytical expressions and show advantages of the proposed CR-NOMA system in terms of outage performance and throughput.