Search Results (67)

This paper examines two-way relaying cognitive radio networks utilizing fountain coding (FC), reconfigurable intelligent surfaces (RIS), and radio frequency energy harvesting (EH). In the proposed schemes, two secondary sources attempt to exchange data with each other through the assistance of an RIS deployed in the network. Using FC, one source sends its encoded packets to the other source, which must collect enough packets for a successful data recovery. The transmit power of the two sources is adjusted according to an interference constraint given by a primary user and the energy harvested from a power station. In the conventional scheme, one source continuously transmits FC packets to the other, using the maximum number of transmissions allowed. In the modified scheme, as soon as one source collects a sufficient number of FC packets, it notifies the other source to stop transmission. We derive closed-form expressions of outage probability (OP) at each source, system outage probability (SOP), and average number of FC-packet transmissions for the successful data exchange of the considered schemes over Rayleigh fading channels. Simulation results are provided to validate our analysis, to compare the performance of the considered schemes, and to examine the impact of key parameters on performance. Full article

Unmanned aerial vehicle (UAV)-enabled vehicular communications in the sixth generation (6G) are characterized by line-of-sight (LoS) and dynamically varying channel conditions. However, the presence of obstacles in the LoS path leads to shadowed fading environments. In UAV-assisted cellular vehicle-to-everything (C-V2X) communication, vehicle and UAV mobility and shadowing adversely impact latency and throughput. Moreover, 6G vehicular communications comprise data-intensive applications such as augmented reality, mixed reality, virtual reality, intelligent transportation, and autonomous vehicles. Since vehicles’ sensors generate immense amount of data, the latency in processing these applications also increases, particularly when the data are not independently identically distributed (non-i.i.d.). Furthermore, when the sensors’ data are heterogeneous in size and distribution, the incoming packets demand substantial computing resources, energy efficiency at the UAV servers and intelligent mechanisms to queue the incoming packets. Due to the limited battery power and coverage range of UAV, the quality of service (QoS) requirements such as coverage rate, UAV flying time, and fairness of vehicle selection are adversely impacted. Controlling the UAV trajectory so that it serves a maximum number of vehicles while maximizing battery power usage is a potential solution to enhance QoS. This paper investigates the system performance and communication disruption between vehicles and UAV due to Doppler effect in the orthogonal time–frequency space (OTFS) modulated channel. Moreover, a low-complexity UAV trajectory prediction and vehicle selection method is proposed using federated learning, which exploits related information from past trajectories. The weighted total energy consumption of a UAV is minimized by jointly optimizing the transmission window ($L_w$), transmit power and UAV trajectory considering Doppler spread. The simulation results reveal that the weighted total energy consumption of the OTFS-based system decreases up to 10% when combined with federated learning to locally process the sensor data at the vehicles and communicate the processed local models to the UAV. The weighted total energy consumption of the proposed federated learning algorithm decreases by 10–15% compared with convex optimization, heuristic, and meta-heuristic algorithms. Full article

This paper aims to examine the physical layer security (PLS) performance of a reconfigurable intelligent surface (RIS)-aided wiretap multiple-input single-output (MISO) system over generalized fading conditions by assuming inherent phase shift errors at the RIS. Specifically, the procedures (i.e., the method) to conduct this research is based on learning-based approaches to model the magnitude of the end-to-end RIS channel, i.e., employing an unsupervised expectation-maximization (EM) approach via a finite mixture of Nakagami-m distributions. This general framework allows us to accurately approximate key practical factors in RIS’s channel modeling, such as generalized fading conditions, spatial correlation, discrete phase shift, beamforming, and the presence of direct and indirect links. For the numerical results, the secrecy outage probability, the average secrecy rate, and the average secrecy loss under different setups of RIS-aided wireless systems are assessed by varying the fading parameters of the N-wave with a diffuse power fading channel model. The results show that the correlation between RIS elements and unfavorable channel conditions (e.g., Rayleigh) affect secrecy performance. Likewise, it was confirmed that the use of a RIS is not essential when there is a solid line-of-sight link between the transmitter and the legitimate receiver. Full article

User location has emerged as a pivotal factor in human-centered environments, driving applications like tracking, navigation, healthcare, and emergency response that align with Sustainable Development Goals (SDGs). However, accurate indoor localization remains challenging due to the limitations of GPS in indoor settings, where signal interference and reflections disrupt satellite connections. While Received Signal Strength Indicator (RSSI) methods are commonly employed, they are affected by environmental noise, multipath fading, and signal interference. Round-Trip Time (RTT)-based localization techniques provide a more resilient alternative but are not universally supported across access points due to infrastructure limitations. To address these challenges, we introduce DistilLoc: a cross-knowledge distillation framework that transfers knowledge from an RTT-based teacher model to an RSSI-based student model. By applying a teacher–student architecture, where the RTT model (teacher) trains the RSSI model (student), DistilLoc enhances RSSI-based localization with the accuracy and robustness of RTT without requiring RTT data during deployment. At the core of DistilLoc, the FNet architecture is employed for its computational efficiency and capacity to capture complex relationships among RSSI signals from multiple access points. This enables the student model to learn a robust mapping from RSSI measurements to precise location estimates, reducing computational demands while improving scalability. Evaluation in two cluttered indoor environments of varying sizes using Android devices and Google WiFi access points, DistilLoc achieved sub-meter localization accuracy, with median errors of 0.42 m and 0.32 m, respectively, demonstrating improvements of 267% over conventional RSSI methods and 496% over multilateration-based approaches. These results validate DistilLoc as a scalable, accurate solution for indoor localization, enabling intelligent, resource-efficient urban environments that contribute to SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities). Full article

This paper proposes a drone-assisted NOMA communication system equipped with a reconfigurable intelligent surface (RIS). Given the Line-of-Sight nature of the Air-to-Ground link, a more realistic Rician fading environment is chosen for the study of system performance. The user’s outage performance and secrecy outage probability of the RIS-UAV-assisted NOMA downlink communication under the Rician channels are investigated. Jointly considering the Line-of-Sight and Non-Line-of-Sight links, the closed-form expressions of each user’s outage probability are derived by approximating the composite channels as Rician distributions to characterize the channel coefficients of the system’s links. Considering the physical layer security in the presence of the eavesdropper, the secrecy outage probability of two users is further studied. The relationship between the system outage performance and the Rician factor of the channel, the number of RIS elements, and other factors are analyzed. The results of this study show that compared with Rayleigh fading, the Rician fading is more practical with the actual Air-to-Ground links; the user’s outage probability and the secrecy outage probability are lower over the Rician channels. The number of RIS elements and the power allocation factor by the base station for the users are inversely proportional to the user’s outage probability, and RIS element number, path loss index, and distance factor also have a greater impact on the outage probability. Compared with OMA, NOMA has a certain enhancement to the system performance. Full article

Intelligent Reflecting Surfaces (IRS) and Multiple-Input Single-Output (MISO) technologies are essential in the fifth generation (5G) networks and beyond. IRS optimizes the signal propagation and the coverage and is a viable approach to address the issues caused by fading channels that limits the spectral efficiency, while MIMO enhances data rates, reliability, and spectral efficiency by using multiple antennas at both transmitter and receiver ends. This paper proposes an IRS-assisted MISO system using the Orthogonal Space-Time Block Code (OSTBC) scheme to enhance the channel reliability and reduce the Bit Error Rate (BER) in wireless communication systems. The proposed system exploits the benefits from the transmit diversity gain of the OSTBC scheme as well as from the bit energy to noise power spectral density (E_b/N_o) improvement of the IRS technology. The presented work explores these combined technologies across different modulation schemes. The obtained results outperform the similar previously published works by considering higher-order modulation schemes as well as the deployment of rate ¾ OSTBC-assisted IRS. Moreover, the obtained results demonstrate that the integration of OSTBC with IRS can yield significant performance improvements in terms of E_b/N_o by 7 dB and 13 dB when using 16 reflecting elements and 64 reflecting elements, respectively. Full article

The fading affect bias (FAB) occurs in autobiographical memory when unpleasant emotions fade faster than pleasant emotions and the phenomenon appears to be a form of emotion regulation. As emotion regulation is positively related to problem solving, the current study examined FAB in the context of problem solving. In-person and online studies asked participants to provide basic demographics, describe their problem-solving abilities, and rate various healthy and unhealthy variables, including emotional intelligence and positive problem-solving attitudes. Participants also completed an autobiographical event memory form for which they recalled and described two pleasant and two unpleasant problem-solving and non-problem-solving events and rated the initial and current affect and rehearsals for those events. We found a robust FAB effect that was larger for problem-solving events than for non-problem-solving events in Study 1 but not in Study 2. We also found that FAB was positively related to healthy variables, such as grit, and negatively related to unhealthy variables, such as depression. Moreover, many of these negative relations were inverted at high levels of positive problem-solving attitudes, and these complex interactions were partially mediated by talking rehearsals and thinking rehearsals. Full article

With the rapid development of the internet of things (IoT) era, IoT devices may face limitations in battery capacity and computational capability. Simultaneous wireless information and power transfer (SWIPT) and mobile edge computing (MEC) have emerged as promising technologies to address these challenges. Due to wireless channel fading and susceptibility to obstacles, this paper introduces intelligent reflecting surfaces (IRS) to enhance the spectral and energy efficiency of wireless networks. We propose a system model for IRS-assisted uplink offloading computation, downlink offloading computation results, and simultaneous energy transfer. Considering constraints such as IRS phase shifts, latency, energy harvesting, and offloading transmit power, we jointly optimize the CPU frequency of IoT devices, offloading transmit power, local computation workload, power splitting (PS) ratio, and IRS phase shifts. This establishes a multi-variate coupled nonlinear problem aimed at minimizing IoT devices energy consumption. We design an effective alternating optimization (AO) iterative algorithm based on block coordinate descent, and utilize closed-form solutions, Dinkelbach-based Lagrange dual method, and semidefinite relaxation (SDR) method to minimize IoT devices energy consumption. Simulation results demonstrate that the proposed scheme achieves lower energy consumption compared to other resource allocation strategies. Full article

With the rapid development of wireless communications, the occupation of time and frequency resources becomes more crowded. The exploitation of space resources is necessary and the diversity combining techniques have substantial applications. Diversity combining achieves great diversity gains and improves the ability to combat multipath fading, among which the maximum ratio combining (MRC) performs as the optimal linear combining approach. However, MRC suffers from detrimental factors such as channel fading and no Gaussian noise in practical scenarios. In this paper, we focus on a comprehensive investigation of MRC. Starting from the MRC principle and system model, we summarize typical scenarios and analyze the channel fading statistics. For the influential factors, we further review related literature on channel correlation, cochannel interference (CCI) and impulsive noise. Major performance criteria and performance bounds are derived and compared. MRC confronts new developing challenges and the major development directions are reviewed. The paper finally discusses recent works and open problems for MRC applications and development. Emerging techniques such as artificial intelligence provide novel solutions for MRC performance improvements. The paper aims to present a summarized insight to assist readers in clarifying the analyzed methodology of MRC, so as to motivate new technology integration and extensive applications of advanced communication systems. Full article

In this paper, we propose a novel system integrating reconfigurable intelligent surfaces (RISs) with cognitive radio (CR) technology, presenting a forward-looking solution aligned with the evolving standards of 6G and beyond networks. The proposed RIS-assisted CR networks operate with a base station (BS) transmitting signals to two users, the primary user (PU) and secondary user (SU), through direct and reflected signal paths, respectively. Our mathematical analysis focuses on deriving expressions for SU in the RIS-assisted CR system, validated through Monte Carlo simulations. The investigation covers diverse aspects, including the impact of the signal-to-noise ratio (SNR), power allocations, the number of reflected surfaces, and blocklength variations. The results provide nuanced insights into RIS-assisted CR system performance, highlighting its sensitivity to factors like the number of reflectors, fading severity, and correlation coefficient. Careful parameter selection, such as optimizing the configuration of reflectors, is shown to prevent a complete outage, showcasing the system’s robustness. Additionally, the work suggests that the optimization of reflectors configuration can significantly enhance overall system performance, and RIS-assisted CR systems outperform reference schemes. This work contributes a thorough analysis of the proposed system, offering valuable insights for efficient performance evaluation and parameter optimization in RIS-assisted CR networks. Full article

This paper investigates the impact of non-ideal environmental factors, including hardware impairments, random user distributions, and imperfect channel conditions, on the performance of distributed reconfigurable intelligent surface (RIS)-assisted air–ground fusion networks. Using an unmanned aerial vehicle (UAV) as an aerial base station, performance metrics such as the outage probability, ergodic rate, and energy efficiency are analyzed with Nakagami-m fading channels. To highlight the superiority of RIS-assisted air–ground networks, comparisons are made with point-to-point links, amplify-and-forward (AF) relay scenarios, conventional centralized RIS deployment, and fusion networks without hardware impairments. Monte Carlo simulations are employed to validate theoretical analyses, demonstrating that in non-ideal environmental conditions, distributed RIS-assisted air–ground fusion networks outperform benchmark scenarios. This model offers some insights into the improvement of wireless communication networks in emerging smart cities. Full article

In this study, we investigated reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication systems over Nakagami-m fading channels. To enhance the reliability of RIS-assisted D2D communications, we utilized the rate-splitting multiple access (RSMA) technique to maximize the achievable ergodic rate for our considered systems. Specifically, both devices decoded the common symbol by treating private symbols as interference, and then each private symbol was decoded by treating the other as interference. In order to maximize the achievable ergodic rate at the destination, we analyzed the achievable ergodic rate of the RIS link and the D2D link, and the destination jointly decoded both symbols transmitted from the source and device by involving the maximum ratio combination (MRC). We obtained a closed-form expression for the achievable ergodic rate of the proposed RIS-assisted D2D communication system. Finally, we investigated the influence of power allocation factors and the number of reflective elements on the achievable ergodic rate. As seen by the numerical results, there was a good match between the analysis and simulation results, as well as significant superiority compared with existing works. Full article

This study evaluates the performance of large intelligent surface (LIS) technology in the context of a multi-user MIMO mobile communication system (Mu-MIMO) proposed for the sixth generation (6G). LIS employs digitally controlled reflectors to enhance Signal-to-Interference plus Noise Ratio (SINR) and establish line of sight (LoS) connectivity in non-LoS environments, improving transmission security. Analytical expressions are derived to assess LIS performance metrics, including distribution parameters, bit error probability, and secrecy outage probability, considering the presence of eavesdroppers and environmental fading. The study highlights the potential of LIS technology to enhance the confidentiality and reliability of digital communication systems in next-generation networks. Full article

Smart cities like Neom require efficient and reliable transportation systems to support their vision of sustainable and interconnected urban environments. High-speed trains (HSTs) play a crucial role in connecting different areas of the city and facilitating seamless mobility. However, to ensure uninterrupted communication along the rail lines, advanced communication systems are essential to expand the coverage range of each base station (BS) while reducing the handover frequency. This paper presents the dual transceiver free space optical (FSO) communication system as a solution to achieve these objectives in the operational environment of HSTs in Neom city. Our channel model incorporates log-normal (LN) and gamma–gamma (GG) distributions to represent channel impairments and atmospheric turbulence in the city. Furthermore, we integrated the siding loop model, providing valuable insights into the system in real-world scenarios. To assess the system’s performance, we formulated the received signal-to-noise ratio (SNR) of the network under assumed fading conditions. Additionally, we analyzed the system’s bit error rate (BER) analytically and through Monte Carlo simulation. A comparative analysis with reconfigurable intelligent surfaces (RIS) and relay-assisted FSO communications shows the superior coverage area and efficiency of the dual transceiver model. A significant reduction of up to 76% and 99% in the number of required BSs compared to RIS and relay, respectively, is observed. This reduction leads to fewer handovers and lower capital expenditure (CAPEX) costs. Full article

Emotionally intelligent people are thought to be more skilled in recognizing, thinking about, using, and regulating emotions. This construct has garnered considerable interest, but initial enthusiasm has faded and it is time to take stock. There is consensus that ability-related measures of emotional intelligence (EI) can be favored to self-report tests, in part because the resulting scores cannot be equated with personality traits. However, there are questions surrounding measurement as well as predictive value. Experts in the field were encouraged to chart new directions, with the idea that these new directions could reinvigorate EI scholarship. Special Issue papers speak to theory, mechanism, measurement, and training. In addition, these papers seek to forge links with research traditions focused on interpersonal perception, emotional awareness, and emotion regulation. As a result of these efforts, new insights into what EI is and how it works can be anticipated in upcoming years. Full article