In this article, we study reconfigurable intelligent surface (RIS)-assisted networks to support Internet of Things (IoT) devices. We propose RIS beamforming strategies to maximize sum rate and fairness and analyze the RIS location. We derive a theoretical lower bound of the minimum number of RIS elements needed to guarantee specific network performance metrics and validate our results via simulations. We present two RIS scenarios in this study, both with the same total number of RIS elements: 1) centralized RIS, where a single RIS assists the network and 2) distributed RIS, where each transmitter has its own dedicated RIS. We study addressing two practical challenges related to RIS elements and channel state information (CSI) assumptions. First, we consider hardware limitations by assuming that each RIS element is equipped with a discrete phase shifter (PS). Second, we investigate the impact of CSI perfectness and availability in the network; therefore, we evaluate the performance of the RIS-assisted network under two scenarios: 1) centralized RIS with imperfect global CSI and 2) distributed RIS, where imperfect local CSI is available at each transmitter.

As potential solutions to empower transmissions among the Internet of Things (IoT) devices, ambient radio frequency (RF) backscatter technology and reconfigurable intelligent surfaces (RISs) have recently attracted a lot of attention. To improve energy and spectrum efficiency, we design a system with a transmit antenna selection (TAS)-aided base station (BS) relying on nonorthogonal multiple access (NOMA), RIS, and backscatter communications (BackCom) with robust transmission links, allowing more users to be served effectively. We adopt the two-user grouping model in the coverage of main BS associated with a particular RIS and interference from coordinate BS is also considered to showcase differences among the performance of the two different kinds of users (i.e., the IoT user with and the IoT user without a dedicated RIS). To exhibit the system performance, we derive closed-form expressions for two main system performance metrics, namely, outage probability and ergodic capacity. A degraded performance is also considered for the case of imperfect successive interference cancellation (SIC). The benefits of the BackCom RIS-aided NOMA system are then demonstrated by comparing its performance to that of traditional orthogonal multiple access (OMA) RIS-aided backscatter systems. We then introduce analytical models to characterize the impact of the main factors on the outage performance and characterize the optimal performance in specific cases. Together with extensive simulations, our analysis shows that the system performance can be adjusted by controlling factors, including power allocation coefficients, the number of metasurfaces of RIS, and target rates.

In this paper, we consider a wireless network enabled by multiple unmanned aerial vehicles (UAVs), which observe physical processes and transmit status updates to a monitor node over an error-prone communication channel. The communication scenarios are classified into two modes based on monitor types: UAV-to-UAV (U2U) and UAV-to-network (U2N) scenarios. Specifically, the U2N scenario is capable of covering a larger area compared to U2U scenario with a high signal-to-noise ratio (SNR). However, the U2U scenario constructs communication links more quickly, resulting in lower latency and higher rates. To evaluate the timeliness of the UAV-aided network, we utilize the age of information (AoI) as a fundamental indicator. AoI measures the time delay between the most recent data generation and the current moment. To compensate for the error-prone channel, this study employs a combination of hybrid automatic repeat request (HARQ) protocols, which include fixed-redundancy HARQ (FR-HARQ) and infinite incremental redundancy HARQ (IIR-HARQ) protocols. Furthermore, the average and peak Age of Information (AAoI and PAoI) of UAV-aided networks are derived for both U2U and U2N scenarios, and the theoretical expressions agree with simulation results. Additionally, FR-HARQ performs a better time performance than IIR-HARQ, and such observation van be verified through simulations.

This study proposes an interesting approach for vehicle-to-vehicle (V2V) communication, which integrates blockchain technology, federated learning (FL), and allocation optimization of latency and resources. The research evaluates the proposed system using various performance metrics such as packet delivery ratio (PDR), model accuracy, and latency and demonstrates its superiority over existing techniques. Further-more, the system provides enhanced security through consensus optimization and k-anonymity for data privacy. Overall, the proposed system is a promising solution for efficient and secure V2V communication in the era of connected and autonomous vehicles. Moreover, the proposed approach achieves higher reli-ability, lower latency, and better resource utilization compared to traditional 5G.

Unmanned aerial vehicle (UAV)-assisted Internet of Things (IoT) systems have been implemented for over a decade, from transportation to military surveillance, and is proven worthy of integration in the next generation of wireless protocols. Though UAVs have immense potential, they have major drawbacks when it comes to real-world implementation, such as energy capacity, loss of signal quality, and spectrum limitations. To overcome these challenges, integration of UAVs with spectrum-efficient techniques, including cognitive radio (CR) and nonorthogonal multiple access (NOMA) has been proposed. In this article, we incorporate transmit-antenna selection (TAS) into an underlay cognitive radio NOMA network, which provides additional benefits through employing multiple-antenna-selection approach at the UAV with the goal of better serving the ground NOMA devices. The links associated with the multiantenna UAV are theoretically assumed to experience Nakagami-$m$fading distribution. We also emphasize the degraded performance caused by imperfect successive interference cancelation (SIC) when decoding signals at the ground NOMA devices. The closed-form expressions for the proposed model are derived to evaluate two main performance metrics, namely, the outage probability and the ergodic capacity. Monte Carlo simulations are performed to analyze the performance of the system in different scenarios. We observe that the power allocation factors for the devices in a group and the altitude of UAV have a noticeable impact on the performance of the system. Furthermore, the increase in the number of antennas at the UAV can complement these effects and further improve the system performance.

With the large-scale commercialization of 5G networks, the era of Internet of Things (IoT), which is oriented toward the Internet of Everything (IoE), is coming. Under the circumstance, reliable and secure communication are the great challenges for future wireless network because of the broadcasting characteristics of electromagnetic wave. Physical-layer security (PLS) is an effective way to ensure secure communication by exploiting random nature of fading channels. Motivated by this, we investigate PLS of the wireless-powered cooperative multirelaying for IoT networks in the presence of eavesdropper with the estimation errors of channel (EEC) and imbalance between in-phase and quadrature-phase (IIQ). Specifically, the relays can be charged by the source with the aid of energy harvesters, and a novel more secure modify-and-forward (MF) relay protocol is proposed. For further improving energy efficiency and reducing extra interference, the$K$th superior relay selection scheme is proposed since some best ones are not available due to some scheduling or failure. Based on the system under study, we derive the analytical expressions for the outage probability (OP), intercept probability (IP), and secrecy OP (SOP) to evaluate the reliable and secure performance of this consideration system. Particularly, we then analyze the asymptotic behaviors of the OP, IP, and SOP, respectively. Through computer simulation, we show that: 1) with EEC, the error floors of the OP and SOP are of presence; 2) multiple relays lead to better OP and SOP performance; and 3) IIQ improves the security and is detrimental to the system reliability.

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 rapid growth of vehicles, the vehicular networks meet main challenges such as dynamic, heterogeneous, and large scaled. In addition, the cellular-based vehicular networks must satisfy further strict requirements, including ultralow latency, high reliability, high spectrum efficiency, and massive connections of the next-generation (6G) network. Recently, by exploiting vehicle clustering utilized for reducing the complexity of vehicle-to-everything (V2X) systems, it could ultimately improve road traffic efficiency. In some specific scenarios related to Internet of Things, a group of vehicles can be served effectively in terms of spectrum efficiency when two key techniques are enabled, i.e., nonorthogonal multiple access and cognitive radio (CR) schemes are joint deployed. These techniques certainly benefit to 6G V2X services to reduce specific challenges, such as traffic congestion and massive connections. Different from existing works, we propose wireless power transfer applied to the roadside unit to improve the situation that energy shortening in small devices deployed in V2X communications. In particular, we derive expressions of throughput to exhibit performance of the two grouped vehicles. To further indicate advantages of spectrum efficiency, we compare two schemes of V2X systems with and without CR schemes. The numerical results demonstrate that the non-CR NOMA-V2X scheme outperforms the CR-based NOMA-V2X scheme with fixed power allocation, but the non-CR NOMA-V2X scheme costs higher spectrum resource compared with the counterpart. Besides, by comparing with orthogonal multiple access (OMA)-assisted V2X, NOMA-V2X schemes demonstrate superiority in terms of throughput performance whilst achieving the benefits of both NOMA and CR schemes.

As important services of the future sixth-generation (6G) wireless networks, vehicular communication and mobile edge computing (MEC) have received considerable interest in recent years for their significant potential applications in intelligent transportation systems. However, MEC-enabled vehicular networks depend heavily on network access and communication infrastructure, often unavailable in remote areas, making computation offloading susceptible to breaking down. To address this issue, we propose an MEC-enabled vehicular network assisted through aerial-terrestrial connectivity to provide network access and high data-rate entertainment services to a vehicular network. We present a time-varying, dynamic system model where high altitude platforms (HAPs) equipped with MEC servers, connected to a backhaul system of low-earth orbit (LEO) satellites, are used to provide computation offloading capability to the vehicles, as well as to provide network access for vehicle-to-vehicle (V2V) communications. Our main objective is to minimize the total computation and communication overhead of the joint computation offloading and resource allocation strategies for the system of vehicles. Since our formulated optimization problem is a mixed-integer non-linear programming (MINLP) problem, which is NP-hard, we propose a decentralized value-iteration-based reinforcement learning (RL) approach as a solution. In our Q-learning-assisted analysis, each vehicle acts as an intelligent agent to form optimal strategies for offloading and resource allocation. We further extend our solution to deep Q-learning (DQL) and double deep Q-learning to overcome the issues of dimensionality and the over-estimation of the value functions, as in Q-learning. Simulation results prove the effectiveness of our solution in successfully reducing system costs compared to baseline schemes.

The implementation of a variety of complex and energy-intensive mobile applications by resource-limited mobile devices (MDs) is a huge challenge. Fortunately, mobile edge computing (MEC) as a new computing paragon can offer rich resources to perform all or part of the MD’s task, which greatly reduces the energy consumption of the MD and improves the quality of service (QoS) for applications. However, offloading tasks to the edge server is vulnerable to attacks such as tampering and snooping, resulting in a deep learning (DL) security feature developed by major cloud service providers. An effective security strategy method to minimize ongoing attacks in the MEC setting is proposed. The algorithm is based on the synthetic principle of a special set of strategies, and it can quickly construct suboptimal solutions even if the number of targets achieves hundreds of millions. In addition, for a given structure and a given number of patrollers, the upper bound of the protection level can be obtained, and the lower bound required for a given protection level can also be inferred. These bounds apply to universal strategies. By comparing with the previous three basic experiments, it can be proved that our algorithm is better than the previous ones in terms of security and running time.

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.

Unmanned aerial vehicle (UAV) is a key enabler for communication systems beyond the fifth generation due to its applications in almost every field, including mobile communications and vertical industries. However, there exist many challenges in 3-D UAV placement, such as resource and power allocation, trajectory optimization, and user association. This problem becomes even more complex as UAV changes its height, which in turn varies the channel conditions and reduces the coverage on account of high co-channel interference. To maximize the user coverage in uplink transmission, we propose to jointly optimize the 3-D UAV placement and path-loss compensation factor. Moreover, we also optimize the latter for various UAV deployment heights in the suburban environment. Simulation results have demonstrated that the joint optimization of the UAV height and path-loss compensation factor results in better coverage and throughput performance as compared to the baseline scheme.

As a new energy saving approach for green communications, energy harvesting (EH) could be suitable technique to facilitate massive connections for large number of devices in such networks. The spectrum shortage occurs in huge number of devices which access with small-cell and macro-cell networks. To tackle these challenges, we develop a tractable framework relying on prominent techniques such as non-orthogonal multiple access (NOMA), antenna selection and energy harvesting. In this paper, we aim at practical scenarios of small cell networks by jointly evaluating capable of interference management and EH. We benefit from transmission approaches including full duplex (FD) and bi-directional transmission to improve the main performance system metrics such as outage probability and throughput. Three useful schemes are explored by considering EH and inter-cell interference. We derive the closed-form and asymptotic expressions for system metrics. We then perform extensive simulations with different system configurations to confirm the effectiveness of the proposed small-cell NOMA systems.

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.

In this paper, we examine the influence of intercell interference (ICI) on the system outage behavior with important derived results in the proposed model of simultaneous wireless information and power transfer (SWIPT) together with the nonorthogonal multiple access (NOMA) using the amplify‐and‐forward protocol. We derive the closed‐form expression of coverage probability for two NOMA users as a function of the signal‐to‐interference‐plus‐noise ratio (SINR). To fully take into account the effect of ICI, we adopt more practical parameters to evaluate the optimal power splitting coefficient regarding energy harvesting system performance analysis. Furthermore, to consider a more practical scenario, based on the fact that the number of ICI sources can affect wireless powered relays, we investigate the average outage probability by considering impacts of the reasonable number of participating ICI.

Fourth generation (4G) wireless technology are expected to be based on worldwide interoperability for microwave access (WiMAX) systems. However, high peak to average power ratio (PAPR), a main drawback in mobile WiMAX using orthogonal frequency division multiplexing (OFDM), are solved in some solutions for many years. Especially, such wireless systems with large number of sub-carriers lead to undesired problems for practical applications. In this investigation, we present the PAPR reduction performance with two different PAPR reduction schemes: partial transmit sequence (PTS) and selective mapping (SLM). These methods are analyzed in terms of complementary cumulative distribution function (CCDF) under different models. Simulations results show that the proposed schemes reduce the PAPR of the transmit signals considerably.