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Recently, intelligent reflective surface (IRS)-aided systems are becoming a prospective technology in realizing for sixth generation (6G) wireless communication era because of extremely low power transmission, seamless coverage and their superiority. These network systems can allow many users and devices to connect to each other, extending the coverage. To empower IRS-aided systems, non-orthogonal multiple access (NOMA) can be leveraged to work with IRS technique enabling further benefits such as mass connectivity, flexible resource allocation and improved performance. Increasing connected devices and expanding coverage means devices have the potential to interfere with each other. Recent studies focusing on researching and analyzing the performance of the IRS-supported NOMA network have not taken into account or not fully calculated the impact of interference on system performance. In this study, we first analyze the effect of co-channel interference (CCI) at users in downlink IRS-NOMA systems. In particular, the CCIs generated by the terminals deployed randomly in the coverage area affect the signal reception at the user in the downlink. In this network model, the channel conditions that follow the Rayleigh distribution and the CCI statistical model are independent and identically distributed. We analyze and evaluate network performance by extracting closed-form expressions of outage probability, ergodic capacity, total achievable rate then highlighting the adverse effects of CCI on IRS-NOMA. In addition, to improve the performance of the IRS-NOMA downlink, we present a framework of theorical analysis to look more insights of users’ performance, i.e. diversity order. Our analytical derivatives are verified through computer simulations based on Monte-Carlo and intuitive comparisons with the benchmarks.

This paper provides a study of the latest target (object) detection algorithms for underwater wireless sensor networks (UWSNs). To ensure selection of the latest and state-of-the-art algorithms, only algorithms developed in the last seven years are taken into account that are not entirely addressed by the existing surveys. These algorithms are classified based on their architecture and methodologies of operation and their applications are described that are helpful in their selection in a diverse set of applications. The merits and demerits of the algorithms are also addressed that are helpful to improve their performance in future investigation. Moreover, a comparative analysis of the described algorithms is also given that further provides an insight to their selection in various applications and future enhancement. A depiction of the addressed algorithms in various applications based on publication count over the latest decade (2023-2013) is also given using the IEEE database that is helpful in knowing their future application trend. Finally, the challenges associated with the underwater target detection are highlighted and the future research paradigms are identified. The conducted study is helpful in providing a thorough analysis of the underwater target detection algorithms, their feasibility in various applications with future challenges and defined strategies for further investigation.

Since the requirement of secure transmission for massive multiple-input–multiple-output (mIMO) is high, we consider a secure massive MIMO system in presence of multiple digital to analog converters (DACs). We deal with complicated performance analysis of the proposed system including a base station, a legitimate user, and an eavesdropper while these nodes are equipped with multiple antennas. In particular, we intend to present the closed-form expression for the ergodic secrecy rate of the system and also calculate the optimal power allocation for better performance gain. The simulation analysis shows that quantization bits, transmit signal to noise ratio at the base station, and power allocation plays a major role in enhancing the performance of the system.

In today’s world, the importance of the Green Internet of Things (GIoT) in the transformed sustainable smart cities cannot be overstated. For a variety of applications, the GIoT may make use of advanced machine learning (ML) methodologies. However, owing to high processing costs and privacy issues, centralized ML-based models are not a feasible option for the large data kept at a single cloud server and created by multiple devices. In such circumstances, edge-based computing may be used to increase the privacy of GIoT networks by bringing them closer to users and decentralizing them without requiring a central authority. Nonetheless, enormous amounts of data are stored in a distribution mechanism, and managing them for application purposes remains a difficulty. Hence, federated learning (FL) is one of the most promising solutions for bringing learning to end devices through edge computing without sharing private data with a central server. Therefore, the paper proposes a federated learning-enabled edge-based GIoT system, which seeks to improve the communication strategy while lowering liability in terms of energy management and data security for data transmission. The proposed model uses FL to produce feature values for data routing, which could aid in sensor training for identifying the best routes to edge servers. Furthermore, combining FL-enabled edge-based techniques simplifies security solutions while also allowing for a more efficient computing system. The experimental results show an improved performance against existing models in terms of network overhead, route interruption, energy consumption, and end-to-end delay, route interruption.

This study proposes an innovative integration of the Car-to-Car Network-Hierarchical deep neural network (CtCNET-HDRNN) model with Fifth generation (5G) and Dedicated Short-Range Communications (DSRC) systems, streamlining computational efficiency in edge computing. CtCNET-HDRNN is a specialized deep learning model designed for vehicular communication, allowing vehicles to exchange information seamlessly in a connected environment. It harnesses an adaptive learning rate and regularization within the model’s advanced training methodology, ensuring optimal data fit, superior generalization, and efficient convergence. A key novelty lies in the introduction of a Sparse Deep Recurrent Neural Network (SDRNN), which significantly reduces computational complexity by pruning insignificant connections, making it suitable for deployment on resource-constrained edge devices. SDRNN is a variant of recurrent neural networks designed to minimize computational burden while maintaining high performance in time-series data analysis. Furthermore, this research presents an original integration model, adeptly merging the CtCNET-HDRNN model with the Millimeter wave (mmWave) of 5G and Monte Carlo for DSRC systems for seamless data transmission. The mmWave technology offers high-speed communication capabilities, while Monte Carlo enables adaptive collision avoidance and efficient channel access control for vehicular networks. Beyond immediate computational gains, this integrated model also contributes significantly to edge computing research and practical applications, promising enhanced system performance and improved user experience in vehicular communication scenarios. The proposed approach opens new possibilities for efficient and reliable communication in connected vehicles, laying the foundation for safer and smarter transportation systems.

The intelligent reflecting surface (IRS) has emerged as a promising solution to enhance the quality of radio transmission by allowing flexible control over the direction of reflection and phase shift of electromagnetic waves. In this study, we present a downlink wireless network considering non-orthogonal multiple access (NOMA) and two IRSs to improve performance for a group of user equipment (UE) at the cell edge, when the UEs cannot reach out direct links from the base station (BS). We start by discussing the framework to design a wireless system relying on both IRS and NOMA, and then calculate the link channel statistics between the BS, IRS, and UEs with Rayleigh fading distributions using the probability density function (PDF) and cumulative distribution function (CDF). Based on these distributions, we derive closed form expressions for the outage probability (OP) for evaluating the performance of the user pair. Additionally, we compute the bit error rate (BER), the ergodic rates (ER) of the UE as functions of the signal-to-interference-plus-noise ratio (SINR) using the Chebyshev-Gauss quadrature method, and hence the complete the overall evaluation of the system’s performance can be achieved. Finally, we verify the mathematical analysis through comparing with Monte-Carlo simulations and indicate that the number of IRS meta-surfaces elements as the main limiting factor to achieve better OP, ER and BER performance.

This paper surveys the short-term road traffic forecast algorithms based on the long-short term memory (LSTM) model of deep learning. The algorithms developed in the last three years are studied and analyzed. This provides an in-depth and thorough description of the algorithms rather than their marginal description as performed in the existing surveys that focus on general deep learning algorithms. The chosen algorithms are classified depending upon the use of LSTM in combination with other techniques for processing input data features towards a final traffic forecast. The operational strategies of the algorithms are described with merits and limitations. Moreover, a comparative analysis of the compared classes of algorithms is also provided. These strategies are helpful in selection of the right algorithms and their classes for the diverse traffic conditions and their future investigation for improvement. Besides, the applications of these classes of algorithms to traffic forecast in various networks for the latest decade is graphically depicted. Moreover, the applications of the LSTM in other fields involving a forecast are provided. Finally, the challenges associated with the short-term traffic forecast using the LSTM are described and strategies are highlighted for their future investigation.

The need to ensure the longevity of Wireless Sensor Networks (WSNs) and secure their communication has spurred various researchers to come up with various WSN models. Prime among the methods for extending the life span of WSNs is the clustering of Wireless Sensors (WS), which reduces the workload of WS and thereby reduces its power consumption. However, a drastic reduction in the power consumption of the sensors when multicore sensors are used in combination with sensors clustering has not been well explored. Therefore, this work proposes a WSN model that employs clustering of multicore WS. The existing Elliptic Curve Cryptographic (ECC) algorithm is optimized for parallel execution of the encryption/decryption processes and security against primitive attacks. The Elliptic Curve Diffie-Helman (ECDH) was used for the key exchange algorithm, and the Elliptic Curve Digital Signature Algorithm (ECDSA) was used to authenticate the communicating nodes. Security analysis of the model and comparative performance analysis with the existing ones were demonstrated. The security analysis results reveal that the proposed model meets the security requirements and resists various security attacks. Additionally, the projected model is scalable, energy-conservative, and supports data freshness. The results of comparative performance analysis show that the proposed WSN model can efficiently leverage multiprocessors and/or many cores for quicker execution and conserves power usage.

The research of Non-Orthogonal Multiple Access (NOMA) is extensively used to improve the capacity of networks beyond the fifth-generation. The recent merger of NOMA with ambient Backscatter Communication (BackCom), though opening new possibilities for massive connectivity, poses several challenges in dense wireless networks. One such challenge is the performance degradation of ambient BackCom in multi-cell NOMA networks under the effect of inter-cell interference. Driven by providing an efficient solution to the issue, this article proposes a new resource allocation framework that uses a duality theory approach. Specifically, the sum rate of the multi-cell network with backscatter tags and NOMA user equipment is maximized by formulating a joint optimization problem. To find the efficient base station transmit power and backscatter reflection coefficient in each cell, the original problem is first divided into two subproblems, and then the closed form solution is derived. A comparison with the Orthogonal Multiple Access (OMA) ambient BackCom and pure NOMA transmission has been provided. Simulation results of the proposed NOMA ambient BackCom indicate a significant improvement over the OMA ambient BackCom and pure NOMA in terms of sum-rate gains.

Abstract The evolution of non-orthogonal multiple access (NOMA) has raised many opportunities for massive connectivity with less latency in signal transmissions at great distances. We aim to integrate NOMA with a satellite communications network to evaluate system performance under the impacts of imperfect channel state information and co-channel interference from nearby systems. In our considered system, two users perform downlink communications under power-domain NOMA. We analyzed the performance of this system with two modes of shadowing effect: heavy shadowing and average shadowing. The detailed performance was analyzed in terms of the outage probability and ergodic capacity of the system. We derive closed-form expressions and performed a numerical analysis. We discover that the performance of two destinations depends on the strength of the transmit power at the satellite. However, floor outage occurs because the system depends on other parameters, such as satellite link modes, noise levels, and the number of interference sources. To verify the authenticity of the derived closed-form expressions, we also perform Monte-Carlo simulations.

To develop emerging transmission techniques for potential applications of Internet of Things (IoT), the system performance analysis of a cognitive radio (CR)-enabled ambient backscatter (AmBC) system will be studied in this paper with functionality of non-orthogonal multiple access (NOMA). In the proposed scheme, a base station communicates with two destinations via a designated backscatter device. It is assumed that the relay node is fitted with two different interfaces and can simultaneously collect/decode and backscatter the received source signals. Such transmission mechanism benefits to design various applications in IoT as well as wireless systems with improved performance. To exhibit system performance metrics, the outage probability and the ergodic capacity of the recipient nodes are derived analytically. Furthermore, it is shown that employing AmBC NOMA together with CR for secondary communication can significantly improve overall network performance in terms of the achievable throughput in delay-limited and delay-tolerant modes and outage probability. Numerical results show that: 1) The proposed system can improve the spectrum efficiency by employing both CR and NOMA techniques; 2) Compared with the orthogonal multiple access (OMA)-aided AmBC systems, the considered CR AmBC system relying on NOMA can obtain better reliability in the whole range of SNR; 3) There are error floors for the outage probability in the high SNR regime due to required target rates; 4) There exists a trade-off between system performance of IoT devices and power allocation coefficients associated with NOMA; 5) We find energy efficiency factor as evident of further improvement in such system.

Reconfigurable intelligent surfaces (RIS), a device made of low-cost meta-surfaces that can reflect or refract the signals in the desired manner, have the immense ability to enhance the data transmission from the sender to the receiver. The concept of RIS is inspired by a smart radio environment or programmable radio environment. The introduction of this device in wireless communications aids in reducing the hardware requirements, energy consumption, and signal processing complexity. The integration of this device with various emerging technologies such as multiple-input multiple-output (MIMO) systems, non-orthogonal multiple access (NOMA) technique, physical layer security, etc., has increased its potentiality in terms of performance enhancement. One such integration could be studied, i.e. RIS-assisted unmanned aerial vehicles (UAVs). The UAVs exhibit aiding capability in various services to our society such as real-time data collection, traffic monitoring, military operations & surveillance, medical assistance, and goods delivery. Despite the positive appeal, the UAV has its limitations such as fuel efficacy, environment disturbances, limited network capability, etc. Considering these scenarios, the RIS can provide assistance to UAVs to enhance their performance when integrated. There is a limited number of articles and researches that consider UAV-assisted RIS systems. This article provides a detailed survey on RIS-assisted UAV systems considering multiple contexts such as optimization, communication techniques, deep reinforcement learning, secrecy performance, efficiency enhancement, and the internet of things. Finally, we draw attention to the open challenges and possible future directions of UAV-assisted RIS systems in phase shifting, channel modeling, energy efficacy, and federated learning.

This paper studies unmanned aerial vehicle (UAV)-aided nonorthogonal multiple access (NOMA)-based mobile-edge computing (MEC) in Internet of Things (IoT) systems in which the uav acts as a relay (UR). Specifically, we consider a scenario with two clusters IoT devices (IDs) (i.e., a high-priority cluster IA and a low-priority cluster IB) with limited resources, so these IDs cannot compute their tasks and must offload them to a base station (BS) through a UR. We propose a protocol named time switching - radio frequency (RF) energy harvesting (EH) UR NOMA (TS-REUN), which is divided into 5 phases. By applying the TS-REUN protocol, the IDs in the two clusters and the UR harvest RF energy from the broadcast signal of the power beacons (PB). Then, the IDs offload their tasks to the MEC server located at the BS. After server processing, the IDs receive the calculation results from the BS via the UR. The effects of both imperfect channel state information (ICSI) and imperfect successive interference cancellation (ISIC) on the REUN-based mec (REUN-MEC) are taken into account. To evaluate the performance of the system, we derive closed-form expressions for the successful computation probability (SCP) and energy consumption probability (ECP) in the Nakagami- $\mathfrak {m}$ fading channel. Moreover, we propose an optimization problem formulation that maximizes the SCP by optimizing the position and the height of the UR and the time switching ratio (TSR). The problem was addressed by employing an algorithm based on particle swarm optimization (PSO). In addition, the Monte Carlo simulation results confirmed the accuracy of our analysis based on system performance simulations with various system parameters, such as the number of antennas at the BS, the number of IDs in each cluster, the TSR, and the position and the height of the UR.

Reconfigurable intelligent surface (RIS)-assisted non-orthogonal multiple access (NOMA) has the ability to overcome the challenges of the wireless environment like random fluctuations, shadowing, and mobility in an energy efficient way when compared to multiple input-multiple output (MIMO)-NOMA systems. The NOMA system can deliver controlled channel gains, improved coverage, increased energy efficiency, and enhanced fairness in resource allocation with the help of RIS. RIS-assisted NOMA will be one of the primary potential components of sixth-generation (6G) networks, due to its appealing advantages. The analytical outage probability expressions for smart RIS-assisted fixed NOMA (FNOMA) are derived in this paper, taking into account the instances of RIS as a smart reflector (SR) and an access point (AP). The analytical and simulation findings are found to be extremely comparable. In order to effectively maximize the sum capacity, the formulas for optimal powers to be assigned for a two-user case are also established. According to simulations, RIS-assisted FNOMA surpasses FNOMA in terms of outage and sum capacity. With the aid of RIS and the optimal power assignment, RIS-AP-FNOMA offers ≈62% improvement in sum capacity over the FNOMA system for a signal-to-noise ratio (SNR) of 10 dB and 32 elements in RIS. A significant improvement is also brought about by the increase in reflective elements.

This paper develops a novel approach for reliable vehicle-to-vehicle (V2V) communication in various environments. A switched beam antenna is deployed at the transmitting and receiving points, with a beam management system that concentrates the power in each beam using a low-computation algorithm and a potential mathematical model. The algorithm is designed to be flexible for various environments faced by vehicles. Additionally, an anti-failure system is proposed in case the intelligent transportation system (ITS) system fails to retrieve real-time Packet Delivery Ratio (PDR) values related to traffic density. Performance metrics include the time to collision in seconds, the bit error rate (BER), the packet error rate (PER), the average throughput (Mbps), the beam selection probability, and computational complexity factors. The proposed system is compared with traditional systems. Extensive experiments, simulations, and comparisons show that the proposed approach is excellent and reliable for vehicular systems. The proposed study demonstrates an average throughput of 1.7 Mbps, surpassing conventional methods’ typical throughput of 1.35 Mbps. Moreover, the bit error rate (BER) of the proposed study is reduced by a factor of 0.1. Additionally, the proposed framework achieves a beam power efficiency of touching to 100% at computational factor of 34. These metrics indicate that the proposed method is both efficient and sufficiently robust.

With less human involvement, the Industrial Internet of Things (IIoT) connects billions of heterogeneous and self-organized smart sensors and devices. Recently, IIoT-based technologies are now widely employed to enhance the user experience across numerous application domains. However, heterogeneity in the node source poses security concerns affecting the IIoT system, and due to device vulnerabilities, IIoT has encountered several attacks. Therefore, security features, such as encryption, authorization control, and verification, have been applied in IIoT networks to secure network nodes and devices. However, the requisite machine learning models require some time to detect assaults because of the diverse IIoT network traffic properties. Therefore, this study proposes ensemble models enabled with a feature selection classifier for Intrusion Detection in the IIoT network. The Chi-Square Statistical method was used for feature selection, and various ensemble classifiers, such as eXtreme gradient boosting (XGBoost), Bagging, extra trees (ET), random forest (RF), and AdaBoost can be used for the detection of intrusion applied to the Telemetry data of the TON_IoT datasets. The performance of these models is appraised based on accuracy, recall, precision, F1-score, and confusion matrix. The results indicate that the XGBoost ensemble showed superior performance with the highest accuracy over other models across the datasets in detecting and classifying IIoT attacks.

As an important partner of fifth generation (5G) communication, the internet of things (IoT) is widely used in many fields with its characteristics of massive terminals, intelligent processing, and remote control. In this paper, we analyze security performance for the cooperative non-orthogonal multiple access (NOMA) networks for IoT, where the multi-relay Wyner model with direct link between the base station and the eavesdropper is considered. In particular, secrecy outage probability (SOP) for two kinds of relay selection (RS) schemes (i.e., single-phase RS (SRS) and two-phase RS (TRS)) is developed in the form of closed solution. As a benchmark for comparison, the SOP for random RS (RRS) is also obtained. To gain more meaningful insights, approximate derivations of SOP under the high signal-to-noise ratio (SNR) region are provided. Results of statistical simulation confirm the theoretical analysis and testify that: i) Compared with RRS scheme, SRS and TRS may improve secure performance because of obtaining smaller SOPs; ii) There exists secrecy performance floor for the SOP in strong SNR regime, which is dominated by NOMA protocol; iii) The security performance can be enhanced by augmenting the quantity of relays for SRS and TRS strategies. The purpose of this work is to provide theoretical basis for the analysis and design of anti-eavesdropping for NOMA systems in IoT.

One of the key enablers of future wireless communications is constituted by massive users can access the core network in wireless systems simultaneously, which can improve the spectral efficiency. In existing scheme of massive connections, namely non-orthogonal multiple access (NOMA), is investigated in conventional relaying networks. This method results in excessive power consumption and high hardware costs. Recently, reconfigurable intelligent surface (RIS) has been considered as one of the revolutionary technologies to enable energy-efficient and smart wireless communications, which is a two-dimensional structure with a large number of passive elements. This paper examines the RISs used in emerging communications systems based on NOMA scheme. The two-user system model contains the far user and the near user which employing RIS and NOMA is conducted in this study. In particular, we design two links (backscatter and direct links) to target to improve performance of far user. System performance was characterized through closed-form expressions of outage probability, ergodic capacity and throughput, which are beneficial to evaluate performance of two users. In Monte-Carlo simulations, it was revealed that the probability of the two users experiencing system outage was determined by factors related to power allocation, power transmission at the base station, and the number of reflecting elements in the RISs.

In this paper, a hybrid satellite-terrestrial spectrum sharing system allows terrestrial secondary network to cooperate with a primary satellite network and to further provide higher spectrum efficiency. For massive connections design, we implement non-orthogonal multiple access (NOMA) technique to form cognitive radio based satellite-terrestrial (CR-NSHT) system relying on NOMA and further achieve more benefits compared with traditional schemes. The secondary network only remains its stable operation when the outage probability of such system is guaranteed, and thereby, to explore advantages of spectrum sharing opportunities. Considering Shadowed-Rician fading for satellite links, and Nakagami- $m$ as well as Rician fading for terrestrial links, we derive the closed-form expressions of the outage probability to evaluate the performance of secondary network. We consider further system performance metrics including ergodic capacity, energy efficiency and multi-user scenarios. We also demonstrate the impacts of power allocation factors, transmit signal-to-noise ratio (SNR) at the source, parameters of satellite links, target rates, and fading severity parameters on the system performance. Numerical and simulation results validate our analysis and highlight the performance gains of the proposed schemes for CR-NSHT with relay link serving secondary network and direct link serving the primary network.

This paper considers a two-user downlink transmission in reconfigurable intelligent surface (RIS)-aided network over fading channels. Particularly, by employing user grouping and fixed power allocation scheme to enable non-orthogonal multiple access (NOMA) approach, RIS-aided network can significant benefit from NOMA. To highlight the advantages of RIS, we compare the system performance of NOMA-RIS and traditional orthogonal multiple access (OMA) based RIS. Main practical circumstances are carefully analyzed, such as, RIS with direct link, system without RIS, and imperfect phase shifts. More specifically, we consider a RIS-aided downlink network, where the base station communicates with a group of two users under assistance of RIS, which acts equivalently as relay. As key expectation, the RIS is efficiently designed to improve the performance of users. To evaluate the system performance, two main system performance metrics including outage probability and average capacity are studied by deriving new closed-form expressions. The goal is to find out which system parameters need to be adjusted to achieve the expected performance. The numerical results reveal that: i) the outage probability and average capacity of considered NOMA-RIS aided wireless system outperforms the conventional NOMA network over fading channels; ii) with different power allocation factors assigned to users, the performance gap among two users can be adjusted to guarantee the fairness characteristic; iii) the number of reflecting elements in RIS has significant impact on the system performance of the considered NOMA-RIS system, which shows advantage of both RIS and NOMA compared with conventional OMA system.

We study the secrecy transmission of uplink non-orthogonal multiple access (NOMA) with single antenna and multi-antenna users in presence of an eavesdropper. Two phases are required for communications during each time frame between the users and the base station in cellular networks. We study the case where an eavesdropper overhears the relay and direct links from the users to the base stations. In terms of the secure performance analysis, we focus on two main metrics including secrecy outage probability (SOP) and strictly positive secrecy capacity (SPSC) with the assumption that the eavesdropper is able to detect the signals. Analytical closed-form expressions for the SOP and SPSC are derived to evaluate the system secure performance achieved by the proposed schemes. Furthermore, the asymptotic analysis is presented to gain further insights. The analytical and numerical results indicate that the proposed schemes can realize better secrecy performance once we improve the channel condition and signal-to-noise ratio (SNR) at the base station. Our results confirms that the secrecy performance gaps exist among the two users since different power allocation factors are assigned to these users.

This paper investigates the physical layer security and data transmission for the underlay device-to-device (D2D) networks, and considers a combination of the reconfigurable intelligent surface (RIS) and full-duplex (FD) jamming receiver for the robustness and security enhancements of the system. In the demonstrated spectrum sharing setup, the total power of the D2D networks is conceived to the transmitter and receiver to transmit a private message and emit the artificial noise (AN) signals. To prevent information leakage, a beamforming design is presented for a multi-antenna FD D2D receiver in order to suppress and inject the AN signals in the direction of legitimate users and eavesdropper, respectively. The statistical characterization of end-to-end RIS-assisted wireless channels is presented, and the achievable ergodic secrecy rate of the system is derived in novel approximate expressions. The numerical and simulation results confirm the accuracy and effectiveness of the proposed analytical framework. The results demonstrate an optimal selection of the D2D power allocations for different number of reflecting elements in terms of achievable ergodic secrecy rates of the system.

We investigated the outage performance of non-orthogonal multiple access (NOMA) in satellite-terrestrial systems which contain hardware impairments. An unmanned aerial vehicle (UAV) was implemented to forward signals from a satellite to users on the ground. A two-user model was applied to achieve spectral efficiency. In practical, real-life scenarios, the UAV and ground users encounter issues with imperfect hardware. We examined the performance gap between two users experiencing practical problems such as hardware impairment and imperfect successive interference cancellation (SIC). To implement a practical scenario, Shadow-Rician fading was adopted in the satellite links, and Rician fading was employed in the terrestrial links for ground users. In the main results, we derived the closed-form expression of the outage probability, and to evaluate the system performance of two NOMA users, we obtained the approximate expressions for high signal-to-noise ratios (SNR). Finally, we produced Monte-Carlo simulations to verify the analytical expressions and demonstrate the effect of the main system parameters, such as the number of transmit antennas on the satellite, transmit SNR, and level of hardware impairment on the system performance metric.

Reconfigurable intelligent surface (RIS)-aided communication is considered as an exciting research topic in academic and industrial communities since it provides an emerging affordable solution to achieve high quality and secure next-generation wireless systems. Especially, the deployment of RIS in multi-user wireless networks promises to reduce system hardware costs, signal processing complexity, as well as energy consumption due to small size, lightweight and ability to actively shape the wireless propagation environment. Further, by realizing a cost-effective radio environment, RIS-aided communication can be implemented to be an appealing technology for future integration with other emerging wireless applications and communication systems. Despite the positive appeal, RISs face new challenges that hinder integrating efficiently into wireless networks, such as network secrecy performance and system sum-rates, as well as achieving efficient deployment design in highly dynamic and time-varying wireless environments. To this end, we overview recent state-of-the-art techniques to address the above issues faced in the integration of RISs with various emerging multi-user communication techniques, such as Unmanned Aerial Vehicles (UAVs), Non-Orthogonal Multiple Access (NOMA), Millimeter Wave (mmWave) and Terahertz (THz) communications, Physical Layer Security (PLS), massive antennas, and Simultaneous Wireless Information and Power Transfer (SWIPT). Finally, we highlight promising future research directions of RIS-aided communication in Cell-Free Massive Multiple-Input-Multiple-Output (MIMO) systems, Rate-Splitting Multiple Access (RSMA), Light Fidelity (LiFi), and Cognitive Radio (CR) systems.

In the paper, we present a study on the performance analysis of a non-orthogonal multiple access (NOMA) underlay cognitive hybrid satellite-terrestrial relaying network (CSTRN) and highlight the performance gaps between multiple users. The satellite source communicates with users by enabling cognitive radio scheme to forward signals to secondary destinations on the ground which belong to dedicated groups following the principle of NOMA. In this scenario, the secondary source acts a relay and employs Amplify and Forward (AF) mode to serve distant NOMA users under a given interference constraint. To characterize the transmission environment, the shadowed-Rician fading and Nakagami- m fading models are widely adopted to the relevant hybrid channels. To provide detailed examination of the system performance metrics, we aim to derive closed-form formulas for the outage probability of the secondary destinations in the presence of the primary interference power constraint imposed by the adjacent primary satellite network. Finally, our simulation results showed that a greater number of antennas, better quality of wireless channels and power allocation factors exhibit the main effects on system performance.

Nanoscale devices, also called nanomachines, form communication networks and cooperate with each other so that they can be used to perform complicated tasks. Such networks of nanodevices, named nanonetworks, envisioned to serve the functionality and performance of today’s Internet. This paper presents a comparative review of the state-of-the-art electromagnetic (EM) nanonetworks highlighting their potentials and challenges in a comprehensive manner. We first introduce the promising areas of applications of nanonetworks; therein, we explain how it can be useful in biomedical fields, environmental domains, consumer products, military systems, and on-chip wireless communications. Then, the survey focuses on the basic principles of fundamental physical layer issues enabling nanonetworks; the discussion includes frequency bands, modulation and demodulation, and EM properties of nanoparticles. Subsequently, the study provides an overview of transmission characteristics including channels, channel coding, and energy constraint nature of nanonetworks. Furthermore, we provide an in-depth discussion on nanoantenna highlighting its variants and their characteristics; give an overview of network layer issues; and discuss the security issues in EM nanonetworks. The study argues that despite the significant recent development of EM communication as one of the most desired modes of nano communications, the limited capabilities of nanomachines introduce a new set of challenges and unique requirements and pose unseen characteristics that need to be deliberately addressed. On that, the review finally provides a critical discussion on the applicability of EM mode for nano communication networks highlighting the future challenges with a set of perspectives of possible solutions.

In a wireless system, dual-hop transmission requires Full-Duplex (FD) to transmit signals from the base station too far users. It is more beneficial if we deploy non-orthogonal multiple access to serve specific users, i.e. normal users (near and far users) and device-to-device users. The fairness and outage performance of these users can be studied. We particularly focus on mathematical analysis of outage performance which is computed based on Signal to Noise Ratio (SNR) of received signals at each kind of user. We derive a closed-form formula of such outage probability along with throughput. To realize both the FD NOMA, this paper performs system performance metrics and considers how self-interference make influences system performance. The simulation results validate the theoretical analysis and show that our scheme can obtain a better outage probability and throughput performance with high transmit SNR at the base station and lower required target rates.

In this work, we design an intelligent reflecting surface (IRS)-assisted Internet of Things (IoT) by enabling non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAV) approaches. We pay attention to studying the achievable rates for the ground users. A practical system model takes into account the presence of hardware impairment when Rayleigh and Rician channels are adopted for the IRS–NOMA–UAV system. Our main findings are presented to showcase the exact expressions for achievable rates, and then we derive their simple approximations for a more insightful performance evaluation. The validity of these approximations is demonstrated using extensive Monte Carlo simulations. We confirm the achievable rate improvement decided by main parameters such as the average signal to noise ratio at source, the position of IRS with respect to the source and destination and the number of IRS elements. As a suggestion for the deployment of a low-cost IoT system, the double-IRS model is a reliable approach to realizing the system as long as the hardware impairment level is controlled. The results show that the proposed scheme can greatly improve achievable rates, obtain optimal performance at one of two devices and exhibit a small performance gap compared with the other benchmark scheme.

Healthcare systems in recent times have witnessed timely diagnoses with a high level of accuracy. Internet of Medical Things (IoMT)-enabled deep learning (DL) models have been used to support medical diagnostics in real time, thus resolving the issue of late-stage diagnosis of various diseases and increasing performance accuracy. The current approach for the diagnosis of leukemia uses traditional procedures, and in most cases, fails in the initial period. Hence, several patients suffering from cancer have died prematurely due to the late discovery of cancerous cells in blood tissue. Therefore, this study proposes an IoMT-enabled convolutional neural network (CNN) model to detect malignant and benign cancer cells in the patient’s blood tissue. In particular, the hyper-parameter optimization through radial basis function and dynamic coordinate search (HORD) optimization algorithm was used to search for optimal values of CNN hyper-parameters. Utilizing the HORD algorithm significantly increased the effectiveness of finding the best solution for the CNN model by searching multidimensional hyper-parameters. This implies that the HORD method successfully found the values of hyper-parameters for precise leukemia features. Additionally, the HORD method increased the performance of the model by optimizing and searching for the best set of hyper-parameters for the CNN model. Leukemia datasets were used to evaluate the performance of the proposed model using standard performance indicators. The proposed model revealed significant classification accuracy compared to other state-of-the-art models.

Wireless Power Transfer (WPT) is a significant technique for Internet of Things (IoT) networks. Recently, more interest has been focused on multiple access technique without orthogonal signals for wireless communication. Non-orthogonal Multiple Access (NOMA) scheme is proposed to allow users the access point in IoT network. In this paper, we propose the power beacon which is able to feed energy to power-constraint relay node to further support transmission from the source to destinations in IoT networks. In this article, a NOMA system is benefited by with WPT and antenna selection technique. The system improvement can be achieved through the exact closed-form expressions of outage probability (OP). The performance gap among two users is evaluated using model of the Rayleigh fading channels. Furthermore, we compare NOMA with traditional scheme to highlight advantage of such IoT system.

This paper investigates non-orthogonal multiple access (NOMA), cooperative relaying, and energy harvesting to support device-to-device (D2D) transmission. In particular, we deploy multiple relay nodes and a cell-center D2D device which can operate in full-duplex (FD) or half-duplex (HD) mode to communicate with a cell-edge D2D device. In this context, there are two possible signal transmission paths from the base station (BS) to the far D2D user either through multiple decode-and-forward (DF) relay nodes or through a near D2D user. Consequently, we propose three schemes to support D2D-NOMA systems, namely non-energy harvesting relaying (Non-EHR), energy harvesting relaying (EHR) and quantize-map-forward relaying (QMFR) schemes. For each of the proposed schemes, closed-form expressions of the outage probabilities of both D2D users are derived. Extensive Monte-Carlo simulation results are provided to validate the derived analytical expressions. The study results show that the proposed schemes can improve the outage performance compared to conventional orthogonal multiple access (OMA) schemes. Moreover, it is shown that the Non-EHR scheme achieves the best outage performance among the three considered schemes.

In this paper, we investigate the reliability and security of cooperative dual-hop non-orthogonal multiple access (NOMA) for internet-of-thing (IoT) networks, in which the transceivers consider a detrimental factor of in-phase and quadrature-phase imbalance (IQI). The communication between the source and destination is accomplished through a decode-and-forward (DF) relay in the presence of an eavesdropper. In order to characterize the performance of the considered system, exact analytical expressions for the outage probability (OP) and intercept probability (IP) are derived in closed-form. Furthermore, to better understanding the performance of the considered system, we further derive the asymptotic expressions of OP in the high signal-to-noise ratio (SNR) regime and IP at the high main eavesdropping ratio (MER) region. A large number of analysis and Monte Carlo simulation results show that the existence of IQI usually increases the corresponding OP and reduces the IP, which means that reduces the reliability of the system and improves the security. In addition, the provided results provide useful insights into the trade-off between reliability and security of secure cooperative communication systems.

In conventional cognitive radio (CR), the users in secondary network (SN) can only access the idle spectrum when users in primary network (PN) are absent. This novel strategy provides higher spectrum efficiency when detecting the presence of the PN. Hence, spectrum utilization of the traditional scheme can be further improved as exploiting application of non-orthogonal multiple access (NOMA). As combination of CR and NOMA, such CR-NOMA has been proposed to improve spectrum efficiency to adapt to requirements in 5G communications. In this study, the relaying scheme is employed in the SN of the proposed CR-NOMA and the relay is allowed to energy harvesting (EH) from the secondary transmitter to serve signal forwarding to distant secondary users. With this regard, the complex model of EH-assisted CR-NOMA is explored in outage behavior and throughput performance as awareness on imperfect successive interference cancellation (SIC) at the receiver. As most important results, the exact closed-form of the exact outage probability is derived for each NOMA destination by assuming that the channel coefficients among considered links follow Rayleigh distribution. Furthermore, performance gap between two NOMA users can be controlled by various parameters such as transmit power, energy harvesting coefficients and levels of imperfect SIC. Simulation results verify our analytical results.

In this paper, we propose a unified framework for hybrid satellite/unmanned aerial vehicle (HSUAV) terrestrial non-orthogonal multiple access (NOMA) networks, where satellite aims to communicate with ground users with the aid of a decode-forward (DF) UAV relay by using NOMA protocol. All users are randomly deployed to follow a homogeneous Poisson point process (PPP), which is modeled by the stochastic geometry approach. To reap the benefits of satellite and UAV, the links of both satellite-to-UAV and UAV-to-ground user are assumed to experience Rician fading. More practically, we assume that perfect channel state information (CSI) is infeasible at the receiver, as well as the distance-determined path-loss. To characterize the performance of the proposed framework, we derive analytical approximate closed-form expressions of the outage probability (OP) for the far user and the near user under the condition of imperfect CSI. Also, the system throughput under delay-limited transmission mode is evaluated and discussed. In order to obtain more insights, the asymptotic behavior is explored in the high signal-to-noise ratio (SNR) region and the diversity orders are obtained and discussed. To further improve the system performance, based on the derived approximations, we optimize the location of the UAV to maximize the sum rate by minimizing the average distance between the UAV and users. The simulated numerical results show that: i) there are error floors for the far and the near users due to the channel estimation error; ii) the outage probability decreases as the Rician factor K increasing, and iii) the outage performance and system throughput performance can be further improved considerably by carefully selecting the location of the UAV.

As a promising technique, power beacon provides ability of wireless energy transfer to relaying devices in Internet of Things (IoT) to serve far devices with respect to low latency and high spectrum efficiency manner. Mobile edge computing (MEC) enables smart devices to offload parts of their computation-workloads to the cellular base stations associated with edge servers. This paper introduces a promising multiple access technique, namely non-orthogonal multiple access (NOMA) to provide communication service between the base station associated with MEC and far IoT devices. In this paper, we indicate that the multiple power beacons (PBs) benefits to uplink of NOMA-MEC system with the wireless powered IoT. More antennas equipped at smart device and more PBs exhibit reasonable outage performance for the considered system. The simulation results reveal in two folds: (1) our proposed scheme can simultaneously achieve higher spectrum efficiency and ensure prolong lifetime of IoT devices; (2) the mobility of relay leads to select PB appropriately and hence the suitable scheme is realized as comparing two schemes related to ability of energy harvesting and acceptable outage behavior.

This article studies the wireless systems by implementing the full-duplex (FD) unmanned aerial vehicle (UAV) relay to allow two nearby base stations joint communicate to distant users. The non-orthogonal multiple access (NOMA) assisted networks and design of multiple-antenna users are considered in order to improve the users' performance. To overcome obstacles in transmission environment, such a model of the uplink (UL) and the downlink (DL) relying on UAV relay is suitable to forward signals to far users. Moreover, practical scenario of imperfect successive interference cancellation (SIC) at each receiver is considered as main reason of degraded performance. To evaluate specific performance metric, we derive the closed-form expressions of outage probability. In addition, the throughput in delay-limited transmission mode of UAV relay assisted UL/DL NOMA system is also considered thoroughly. The derivations and results showed that the higher number of antennas at users could effectively improve the system throughput and reduce the outage probability. The numerical simulation results further indicate the effectiveness of the proposed system and the correctness of theoretical analysis.

In this article, we introduce a small-cell network operating in the context of heterogeneous cellular networks for both downlink (DL) and uplink (UL) by deploying three techniques of full-duplex transmission mode, energy harvesting, and power domain-based non-orthogonal multiple access (NOMA) schemes. Compared to the conventional half-duplex orthogonal multiple access (OMA) scheme that has been widely implemented in current wireless communication systems, the full-duplex (FD) NOMA relying on energy harvesting scheme has a great potential to further enhance the system performance in terms of connectivity capability, spectral efficiency and outage performance. In the proposed two-user small-cell relying on NOMA scheme, the small-cell base station first transfers an energy-bearing signal to serve the two users in the DL phase. Later, an energy harvesting technique is proceeded to encourage the strong user and the weak user to transmit their messages in the UL phase in a FD manner. However, one major challenge related to the FD strategy is the self-interference signal due to a signal leakage from the terminal's output to the input. Besides that, the interference from macro-cell users is also main reason of degradation of the system performance. In this article, we derive analytical expressions to describe the system's performance in terms of the outage probability and throughput. Moreover, extensive numerical simulations are performed to compare and highlight the performance of the proposed small-cell network with several practical scenarios.

We study a hybrid satellite-terrestrial cognitive network (HSTCN) relying on non-orthogonal multiple access (NOMA) interconnecting a satellite and multiple terrestrial nodes. In this scenario, the long distance communication is achieved by the satellite equipped multiple antennas to send information to a multi-antenna destinations through the base station acting as relay. The secure performance is necessary to study by exploiting the appearance of an eavesdropper attempting to intercept the transmissions from relay to destinations. We explore situation of hardware imperfections in secondary network and deign of multiple antennas need be investigated in term of the physical-layer security by adopting the decode-and-forward (DF) relay strategy. Specifically, we guarantee coverage area by enabling relaying scheme and keep outage probability (OP) performance satisfying required data rates. Moreover, suppose that only the main channels' state information is known while the wiretap channels' state information is unavailable due to the passive eavesdropper, we analyze the secrecy performance in term of intercept probability (IP) of the HSTCN by driving the closed-form expressions of such performance metric. Finally, the presented simulation results show that: 1) The outage behaviors of NOMA-based HSTCN network does not depend on transmit signal to noise ratio (SNR) at source at high SNR; 2) Numerical results show that the such system using higher number of transceiver antennas generally outperform the system with less antennas in terms of OP and IP and reasonable selection of parameters is necessary to remain the secrecy performance of such systems; and 3) By allocating different power levels to tow users, the second user has better secure behavior compared with the first user regardless of other set of satellite links or the number of antennas, which means that the superiority of the second user compared with user the first user in terms of OP and IP are same.

Satellite communication systems need to be integrated with emerging small-cell network to provide seamless connectivity and high-speed broadband access for mobile users in future wireless networks. In this paper, we study a hybrid satellite-terrestrial relay system (HSTRS) employing small cell transmission under interference constraint with macro-cell users. To characterize such HSTRS-assisted small-cell network, Shadowed-Rician fading for satellite links and Nakagami-$m$ fading for terrestrial links are adopted. We further deploy non-orthogonal multiple access (NOMA) to improve spectrum efficiency. To provide performance analysis, we derive exact formulas for outage probability and throughput of the considered HSTRS, and further examine its achievable diversity order. More importantly, we conduct the performance analysis by indicating performance gaps among two users, and such a gap depends on power allocation factors. We evaluate key performance metrics through the derived analytical expressions to provide useful framework of HSTRN and to characterize the impact of interference in different cells, and integer values of the per-hop fading severity parameters. The useful guidelines are introduced in the design of futuristic HSTRS for small-cell communications.

Vehicle-to-everything (V2X) communications are regarded as the key technology in future vehicular networks. V2X features promising benefits in providing efficient and reliable massive connections, improving traffic efficiency and safety, as well as supporting in-vehicle entertainment and other functions. Recently, non-orthogonal multiple access (NOMA) is further known as a promising solution in the fifth-generation (5G) mobile communication systems. Such NOMA has drawn much attention because of its ability to significantly improve the network throughput and lower the accessing and transmission latency to meet the quality-of-service (QoS) requirements of many 5G-enabled applications. In this respect, this paper first considers a full-duplex (FD) transmission mode together with the Roadside Unit (RSU) selection scheme in a NOMA-V2X networks since relay selection based NOMA network is introduced as technique to increase the ergodic capacity. In the considered NOMA-V2X systems, the vehicles enable device-to-device (D2D) transmission mode to permit two nearby vehicles communicate at close distances. To further robust performance, the vehicle requires relaying transmission in group of RSUs which tight connected with a cellular network. Secondly, we compare ergodic rate performance of two vehicles in specific group. Finally, we evaluate the ergodic performance by deriving the exact and closed-form expressions of ergodic rate in various scenarios. The results show that ergodic rate improvement can be achieved by increasing the number of RSUs and limiting impact of self-interference due to the FD mode.

The future of wireless communications looks exciting with the potential new use cases and challenging requirements of future 6th generation (6G) wireless networks. Since the traditional wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. The recent advent of reconfigurable intelligent surfaces (RIS) in wireless communications enables, on the other hand, network operators to control the radio waves (the scattering, reflection, and refraction characteristics) to eliminate the negative effects of natural wireless propagation. Recent results have revealed that non-orthogonal multiple access (NOMA) benefits from RIS mechanism which can effectively provide effective transmissions. Motivated by the potential of these emerging technologies, we study the impact of hardware impairment in RIS-aided NOMA system in term of performance metrics. We then derive analytical expressions of outage probability and throughput as main performance metrics. Simulations are conducted to validate the analytical expressions. We find that the number of meta-surfaces in RIS, transmit power at the base station, power allocation factors play important role to demonstrate improvement in system performance of RIS relying on NOMA compared with orthogonal multiple access (OMA). Numerical results are presented to validate the effectiveness of the proposed RIS-aided NOMA transmission strategies.

In this study, the performance of a secondary network in cognitive radio (CR) is studied in the context of vehicle-to-everything (V2X). The non-orthogonal multiple access (NOMA) is effectively applied in this new system model, namely CR-assisted NOMA-V2X, and it is beneficial to serve group of vehicles. In our proposed system, two schemes related to vehicle-to-vehicle (V2V) transmissions are further considered to enhance performance of the vehicle that needs higher quality of service (QoS). However, the degradation performance can be predicted by evaluating downlink under impacts from interference from the primary network, imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC). The outage performance gap among two vehicles exists since different power allocation factors were assigned to them. To validate the system performance, the outage probability is first derived in exact and approximate forms and then the throughput can be further achieved. The optimal throughput can be obtained by numerical simulations. Simulation results are provided to verify the correctness of the derived expressions and it exhibits advantages of the proposed CR-assisted NOMA-V2X system in terms of outage probability and the throughput.

Non-orthogonal multiple access (NOMA) is considered as one of the most promising technologies to handle the issue of spectrum scarcity in beyond fifth-generation (5G) networks. Integrating NOMA in cognitive radio (CR) network is expected to usher a new era of reliable, seamless, and massive connectivity. In this regard, this work explores the relay selection problem in CR networks when operating in the spectrum sharing model. Specifically, the secondary users (SUs) in the CR-NOMA network opportunistically access the licensed spectrum resources to boost the number of accessible SUs sharing the limited and dynamic spectrum resources. Moreover, to improve the performance of far users, partial relay selection architecture is exploited at full-duplex (FD) and half duplex (HD) relays for both uplink and downlink communications. For in-depth performance evaluation, we provide closed-form expressions of the outage probabilities of the users in FD and HD relay-aided CR-NOMA networks. In addition to this, the analytical expressions of asymptotic outage probabilities and ergodic capacity are also provided which unveils the critical factors affecting the performance of CR-NOMA networks. To validate the derived expressions, extensive simulations are performed that demonstrate the accuracy of analytical expressions for FD and HD relay-aided CR-NOMA networks.

To improve the utilization of spectrum and system capacity, non-orthogonal multiple access (NOMA) is considered as a promising multiple access method for emerging communication technologies. Its advantageous benefits are implemented in two-way wireless networks. Power allocation factors assigned to multiple users play a key role in the successful deployment of fairness balance in NOMA. This paper considers fixed power allocation, and performance degradation is predicted in worse situation in which non-optimal power scheme and the imperfect channel state information (CSI) happen. More challenging issue happens in this system, and this paper addresses the situation of NOMA supporting multi-pair of users, in which group of users can communicate to other users to achieve acceptable throughout in two kinds of mode, i.e. delay-limited mode and delay-tolerant mode. Two performance metrics have been considered, namely, ergodic rate and outage probability. For both metrics, we derived closed-form analytical expressions as well as asymptotic performance. Numerical results show that the proposed system presents benefits to cellular networks by extending ability to serve more users who have different demands on data communication. Monte Carlo simulations are provided throughout to validate the accuracy of the derived analytical expressions.

In this paper, we design and investigate a novel uplink/downlink (UL/DL) non-orthogonal multiple access (NOMA) network using a common relay. Instead of successive interference cancellation (SIC) for UL/DL NOMA systems with fixed decoding order based on the statistical channel state information (CSI), we adopt the dynamic decoding order according to power level of received signals. Specifically, by exploiting the CSI-based dynamic decoding order, better fairness can be achieved and applicable. This decoding scheme is highly suitable for implementing a NOMA system in practice. The closed-form expressions for the users' outage probabilities are derived, and then an asymptotic analysis is carried out. Insightful discussions with diversity order are provided. Simulations are performed to corroborate the exactness of the theoretical analysis.

A single-tier downlink Non-Orthogonal Multiple Access (NOMA) network is considered in this paper where analytical framework is given for performance evaluation. Particularly, the outage probability at the downlink users is studied under the impact of imperfect Channel State Information (CSI). The inter-cell interference and the intra-cell interference are also taken into consideration to capture practical behaviors of the proposed system. Further, we also adopt the Poisson Point Process (PPP) to model the location of the base stations and the downlink users in this work. For the imperfect CSI scenario, the results point out that the more times the user spends on performing interference cancellation, the more severe the user is affected by channel estimation error and vice versa. The results for the outage probability expressed in the analytical-forms are then confirmed by the Monte Carlo simulations.

In this paper, two energy harvesting policies deploying in cooperative non-orthogonal multiple access (NOMA) systems are considered. After period of wireless power transfer, the NOMA users including cell-edge and cell-center users simultaneously transmit the superposition coded symbols to the base station (BS). In the last time slot, the BS decodes to achieve its signal based on superposition coded symbol with corresponding power allocation factors. This paper provides exact expressions of outage probability in two schemes. Performance gap of two NOMA users can be raised by providing different power allocation factors. It is confirmed by numerical result. Distance and data rate are main factors affecting outage performance. Scheme I exhibit scenario where power beacon transmits energy signal to NOMA user while the BS feeds energy to NOMA user in Scheme II. It is shown that outage performance of Scheme I is better than that of Scheme II.

The evolution of Internet of Things (IoT) networks has been studied owing to the associated benefits in useful applications. Although the evolution is highly helpful, the increasing day-to-day demands of mobile users have led to immense requirements for further performance improvements such as efficient spectrum utilization, massive device connectivity, and high data rates. Fortunately, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) techniques have recently been introduced as two possible current-generation emerging technologies with immense potential of addressing the above-mentioned issues. In this paper, we propose the integration of RIS to the existing techniques (i.e., NOMA and relaying) to further enhance the performance for mobile users. We focus on a performance analysis of two-user group by exploiting two main performance metrics including outage probability and ergodic capacity. We provide closed-form expressions for both performance metrics to highlight how NOMA-aided RIS systems provide more benefits compared with the benchmark based on traditional orthogonal multiple access (OMA). Monte-Carlo simulations are performed to validate the correctness of obtained expressions. The simulations show that power allocation factors assigned to two users play a major role in the formation of a performance gap among two users rather than the setting of RIS. In particular, the strong user achieves optimal outage behavior when it is allocated 35% transmit power.

A novel non-orthogonal multiple access (NOMA) scheme is proposed to improve the throughput and the outage probability of the cognitive radio (CR) inspired system which has been implemented to adapt multiple services in the nextgeneration network (5G). In the proposed scheme, the primary source (PS) had sent a superposition code symbol with a predefined power allocation to relays, it decoded and forwarded (DF) a new superposition coded symbol to the destination with the other power allocation. By using a dual antenna at relays, it will be improved the bandwidth efficiency in such CR NOMA scheme. The performance of the system is evaluated based on the outage probability and the throughput with the assumption of the Rayleigh fading channels. According to the results obtained, it is shown that the outage probability and throughput of the proposed full-duplex (FD) in CR-NOMA with reasonable parameters can be able deploy in practical design as illustration in numerical results section.

In this paper, the impact of the jamming signal on the secrecy performance of Energy Harvesting (EH) enabled dual-hop amplify-and-forward relaying network is investigated. First, the security outage probability analysis is studied for conventional networks under a single passive eavesdropper attack. Then, the outage performance analysis in two cases regarding energy harvesting is investigated. Moreover, the proposed work enhances Physical Layer (PHY) security performance of two-hop relaying model using Cooperative Jamming Dual-Hop Techniques (CJDH). For this purpose, new closed-form expressions are derived for the outage probability of CJDH model in the presence of interference over Rayleigh fading channels. A power allocation optimization problem for energy harvesting protocol is formulated and solved for enhancing the system security. The derived analytical formulas herein are supported by numerical and simulation results to clarify the main contributions of the paper.