Search Results (81)

Reliable last-mile connectivity at the cell edge remains a central challenge for Advanced Metering Infrastructure (AMI) in smart grids. This work addresses how to select between LTE-M and NB-IoT communications under weak-coverage conditions by combining field measurements with distribution-based channel modeling. We analyze multi-month Reference Signal Received Power (RSRP) datasets from three areas of a real AMI deployment (N = 30, 35, and 38 m, respectively) and fit canonical fading surrogates—Rayleigh, Rician, and Nakagami—to the normalized measurements. The principal decision statistic is the probability that RSRP falls below a practical threshold (−105 dBm), obtained from empirical and modeled CDF and translated into the predicted number of meters requiring fallback to NB-IoT. Across areas, Nakagami consistently provides the lowest or near-lowest Root Mean Square Error (RMSE) against empirical CDF and the closest agreement with observed fallback counts at −105 dBm, whereas Rayleigh tends to underestimate deep fade tails and Rician degrades when line-of-sight is weak. A threshold sweep sensitivity study (−110 to −89 dBm) using Area 3 illustrates how the predicted fallback population changes monotonically with the decision threshold and supports policy tuning. Overall, a CDF-anchored, Nakagami-guided rule at −105 dBm aligns technology selection with measured channel statistics, improving the robustness of Cellular IoT (CIoT) last-mile communications. Full article

Unmanned aerial vehicles (UAVs) are pivotal for 6G ubiquity, yet their open line-of-sight channels increase vulnerability to interception, posing new challenges for covert communication. This paper proposes a joint optimization scheme for multi-UAV relay-assisted covert communication system with the maximum channel capacity relay selection (MCRS) criterion. Distinct from conventional single-UAV approaches, this scheme uniquely couples UAV geometric positions with the time-varying characteristics of the wireless channels, exploiting spatial diversity from UAV relays to mitigate small-scale fading in dense urban environment, and jointly optimizes the transmit power and UAVs’ altitude. Specifically, we first designed an optimal relay selection strategy and derived analytical expressions for detection error and outage probabilities over altitude-dependent Nakagami-m fading channels. Furthermore, we maximized the effective covert rate by jointly optimizing the UAVs’ hovering altitude and adaptive transmit power of source and relays, subject to covert constraints. Extensive numerical results demonstrate a near-perfect match between the derived theoretical expressions and Monte Carlo simulations and validate the accuracy of our theoretical model. Compared against conventional single-UAV and multi-fixed-altitude UAV benchmark schemes, simulations demonstrate that the joint optimization scheme with relay selection proposed significantly enhances the covert performance of UAV-assisted communication systems. Full article

Integrated sensing and communication (ISAC) is expected to be a key enabler for future wireless networks, improving spectral and hardware efficiency by jointly performing radar sensing and wireless communication within a unified framework. This paper proposes BeamNet, an unsupervised deep learning framework for transmit beamforming in dual-function radar-communication systems operating over general fading with imperfect channel state information (CSI). BeamNet maps noisy estimates of the communication and sensing channels to a transmit beamforming vector and is trained end-to-end by maximizing a weighted sum of the communication rate (CR) and sensing rate (SR), thereby learning the CR–SR Pareto frontier without beamforming labels or embedded optimization solvers. Using Rayleigh fading with perfect CSI, we first show that BeamNet reproduces the analytical Pareto-optimal beamforming solutions. We then use BeamNet to characterize, for Nakagami-m and Rician fading, the CR–SR trade-off across a range of fading parameters, and to assess robustness under distribution mismatch between training and test channels. Finally, under imperfect CSI, we demonstrate that BeamNet yields CR–SR trade-offs that are consistently sandwiched between the perfect-CSI and mismatched analytical baselines, outperforming the closed-form beamformer applied to imperfect CSI and recovering part of the performance loss caused by channel estimation errors. These results indicate that unsupervised learning offers a flexible and robust approach to ISAC beamforming in fading environments with imperfect channel knowledge. Full article

The integration of low Earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) into the maritime Internet of Things (MIoT) offers an effective solution to overcoming the limitations of connectivity and transmission reliability in conventional MIoT, thereby supporting marine data acquisition. However, the highly dynamic ocean environment necessitates a theoretical framework for system-level performance evaluation before practical deployment. In this article, we consider a LEO satellite and UAV-assisted MIoT (LSU-MIoT) network and develop an analytical framework to evaluate its transmission performance. Specifically, marine devices and relaying buoys are modeled as a Matérn cluster process on the sea surface, UAVs as a homogeneous Poisson point process, and LEO satellites as a spherical Poisson point process. Signal transmissions over marine, aerial, and space links are characterized by Nakagami-m, Rician, and shadowed Rician fading, respectively, with the two-ray path loss model applied to sea and air links for accurately capturing propagation characteristics. By leveraging stochastic geometry, we derive analytical expressions for transmission success probability and end-to-end delay of regular and emergency data under the time division multiple access and non-orthogonal multiple access schemes. Simulation results validate the accuracy of derived expressions and reveal the impact of key parameters on the performance of LSU-MIoT networks. Full article

Due to the high mobility, flexibility, and low cost, unmanned aerial vehicles (UAVs) can provide an efficient way for provisioning data communication and computing offloading services for massive Internet of Things (IoT) devices, especially in remote areas with limited infrastructure. However, current transmission schemes for unmanned aerial vehicle-assisted Internet of Things (UAV-IoT) predominantly employ polling scheduling, thus not fully exploiting the potential multiuser diversity gains offered by a vast number of IoT nodes. Furthermore, conventional opportunistic scheduling (OS) or opportunistic beamforming techniques are predominantly designed for downlink transmission scenarios. When applied directly to uplink IoT data transmission, these methods can incur excessive uplink training overhead. To address these issues, this paper first proposes a low-overhead multi-UAV uplink OS framework based on channel reciprocity. To avoid explicit massive uplink channel estimation, two scheduling criteria are designed: minimum downlink interference (MDI) and the maximum downlink signal-to-interference-plus-noise ratio (MD-SINR). Second, for a dual-UAV deployment scenario over Rayleigh block fading channels, we derive closed-form expressions for both the average sum rate and the asymptotic sum rate based on the MDI criterion. A degrees-of-freedom (DoF) analysis demonstrates that when the number of sensors, K, scales as ${\rho }^{\alpha }$, the system can achieve a total of $2\alpha$ DoF, where $\alpha \in \left[0,1\right]$ is the user-scaling factor and $\rho$ is the transmitted signal-to-noise ratio (SNR). Third, for a three-UAV deployment scenario, the Gamma distribution is employed to approximate the uplink interference, thereby yielding a tractable expression for the average sum rate. Simulations confirm the accuracy of the performance analysis for both dual- and three-UAV deployments. The normalized error between theoretical and simulation results falls below 1% for K > 30. Furthermore, the impact of fading severity on the system’s sum rate and DoF performance is systematically evaluated via simulations under Nakagami-m fading channels. The results indicate that more severe fading (a smaller m) yields greater multiuser diversity gain. Both the theoretical and simulation results consistently show that within the medium-to-high SNR regime, the dual-UAV deployment outperforms both the single-UAV and three-UAV schemes in both Rayleigh and Nakagami-m channels. This study provides a theoretical foundation for the adaptive deployment and scheduling design of UAV-assisted IoT uplink systems under various fading environments. Full article

This study investigates a dynamic switching method for signal relay protocols in Cooperative Pattern Division Multiple Access (Co-PDMA) networks. The proposed approach aims to fully utilize the advantages of signal relays in fading-prone environment while simultaneously reducing the network outage probability and improving the throughput and energy efficiency. To demonstrate the necessity of implementing the dynamic switching method for signal relay protocols, Co-PDMA networks with Decode-and-Forward (DF) or Amplify-and-Forward (AF) protocols are explored over Nakagami-m fading. Based on the analysis of these two scenarios, the overall outage probability, throughput, and energy efficiency of the Co-PDMA network with a dynamic DF/AF protocol are determined. The results demonstrate that the proposed method selects the optimal signal relay protocol for forwarding user data in a simple and efficient manner across varying transmit signal-to-noise ratios, quality of service, and signal relay locations. Compared with fixed signal relay protocols, the proposed method is more conducive to achieving green communication in Co-PDMA networks, as it enhances communication reliability and the total volume of data transmitted. Full article

This work examines the performance of a multi-antenna cooperative non-orthogonal multiple access (NOMA) network that employs short-packet communications and operates under the effect of hardware impairments. Specifically, a multi-antenna source transmits superposition-coded NOMA signals to a near user and a far user. Acting as a decode-and-forward (DF) relay, the near user adopts successive interference cancellation (SIC) to decode and subsequently forward the message intended for the far user. In addition, the transmission strategy at the source is the maximum ratio transmission (MRT) and the reception strategy at the far user is selection combining (SC). For Nakagami-m fading channels, closed-form expressions for the average block error rate (BLER) and effective throughput are derived. Then, the effective throughput is maximized through the optimization of the blocklength, accounting for constraints on transmission latency and reliability. The results obtained from simulations confirm the analytical findings and demonstrate that the proposed scheme, with a two-antenna source configuration, achieves a superior effective throughput, reaching up to 240% at a transmit signal-to-noise ratio (SNR) of 33 dB, compared to the existing NOMA scheme in the literature. Full article

Spatial Modulation (SM) is a promising technique for future wireless communication systems, as it reduces hardware cost and complexity while maintaining good bit error rate (BER) performance in MIMO systems. However, in real-world scenarios, systems often face challenges like antenna correlation and partial knowledge of the channel at the receiver (CSIR). This paper examines the performance of a new communication method called Generalized Quadrature Spatial Modulation (GQSM), combined with Quasi-Orthogonal Space-Time Block Codes (QOSTBC), under realistic fading conditions using Nakagami-m channels. To address the impact of imperfect CSIR, the paper introduces three new QR decomposition-based detection techniques. These methods are specifically designed to reduce errors and enhance reliability in conditions where traditional maximum likelihood (ML) detection performs poorly. A detailed theoretical analysis of all three detection schemes is provided to explain their performance and advantages. Among them, Technique III yields the best results in extensive Monte Carlo simulations, demonstrating improved error performance with significantly lower computational complexity than ML detection. Overall, the proposed detection methods not only overcome the limitations of ML detection but also provide a practical and scalable solution for challenging wireless environments by effectively leveraging the numerical stability of QR decomposition. Full article

This research introduces and studies the performance of the $\alpha$-Fluctuating Nakagami-m model, which addresses the limitations of conventional models for wireless communications. For the assumed channel model, the research presents a complete first-order statistical description (including the probability density function (PDF), cumulative distribution function (CDF), moment generating function (MGF), and raw moments) and provides closed-form results for system performance (assessed in terms of outage probability, average bit error rate (ABER), and channel capacity). All of the expressions have the same numerical complexity as the base-line Fluctuating Nakagami-m model, and are accompanied by their high signal-to-noise ratio (SNR) asymptotics. The derived results helped to identify the amount of fading (AoF) and diversity/coding gain of the proposed channel model. In-depth analysis of the system performance was carried out for all possible fading channel parameter values. Numerical analysis of the proposed solutions demonstrated their high computational efficiency. The comparison with experimental results demonstrated that the model offers enhanced flexibility and better characterization of fading regimes. Numerical analysis and simulation results show a high degree of correspondence with the analytical work and help study the dependence of channel nonlinearity effects on overall system performance. Full article

Vehicular Ad Hoc Networks (VANETs) serve as critical platforms for inter-vehicle communication within constrained ranges, facilitating information exchange. However, the inherent challenge of dynamic network topology poses persistent disruptions, hindering safety and emergency information exchange. An alternative generalised statistical model of the channel is proposed to capture the varying transmission range of the vehicle node. The generalised model framework uses simple wireless fading channel models (Weibull, Nakagami-m, Rayleigh, and lognormal) and the large vehicle obstructions to model the transmission range. This approach simplifies analysis of connection of vehicular nodes in environments were communication links are very unstable from obstructions from large vehicles and varying speeds. The connectivity probability is computed for two traffic models—free-flow and synchronized Gaussian unitary ensemble (GUE)—to simulate vehicle dynamics within a multi-lane road, enhancing the accuracy of VANET modeling. Results show that indeed the dynamic range distribution is impacted at shorter inter-vehicle distances and vehicle connectivity probability is lower with many obstructing vehicles. These findings offer valuable insights into the overall effects of parameters like path loss exponents and vehicle density on connectivity probability, thus providing knowledge on optimizing VANETs in diverse traffic scenarios. Full article

This study analyzes the performance of a multi-user digital communication system aided by reflecting intelligent surfaces (RIS) in terms of bit error probability and secrecy outage probability for a system sending symbols with M-QAM modulation passing through channels with Weibull fading, where RIS are employed to improve the signal-to-noise plus interference ratio (SINR) for each user. The performance analysis is conducted based on the statistical properties of the phase correction error of the transmitted signal, which follows a von Mises distribution. Furthermore, this study demonstrates that the resulting SINR follows a gamma distribution, with its parameters derived analytically. The RIS performance increases the line of sight strength and reduces the secrecy outage probability and error probability when the number of reflectors is sufficiently large, even without direct links between the users and the transmitter. Full article

This paper investigates the outage performance of simultaneous wireless information and power transfer (SWIPT)-assisted device-to-device (D2D)-based hybrid satellite–terrestrial networks (HSTNs). In the considered system, an energy-constrained terrestrial user terminal (UT) harvests energy from the radio frequency (RF) signal of a terrestrial amplify-and-forward (AF) relay and utilizes the harvested energy to cooperate with the shadowed terrestrial Internet of Things (IoT) devices in a D2D communication. Both power splitting (PS)-based and time switching (TS)-based SWIPT-D2D schemes are adopted by the energy-constrained UT to obtain sustainable energy for transmitting information to the shadowed IoT device. Considering shadowed Rician fading for satellite–terrestrial links and Nakagami-m fading for terrestrial links, we analyze the system performance by deriving the closed-form expressions for the outage probability (OP) of both the UT and the IoT device. Our theoretical analyses are validated via Monte Carlo simulations. Full article

Due to the need for the implementation of various IoT services, novel generation networks are often characterized by a constant requirement for their expansion and a rising number of nodes. The IoT network nodes are usually low power, so security becomes a challenging issue as conventional cryptographic techniques are hard to implement due to power and computational limitations. Besides, wireless power transfer is an appealing approach for powering IoT systems in scenarios where many nodes are placed in hardly accessible areas. Finally, due to a variety of applications, network nodes are often mobile. Motivated by these facts, in this paper, we investigate physical layer security in IoT systems powered by means of a power beacon, where a legitimate user or eavesdropper can be mobile. The closed-form approximate secrecy outage probability expressions are derived for the Nakagami-m fading environment and three scenarios of receiving node mobility, described by using a random waypoint model with mobility patterns in one, two or three dimensions. The accuracy of the obtained analytical expressions is corroborated by an independently developed simulation model. Full article

With the rapid development of vehicular networks, the computational capabilities and application scenarios of vehicles are becoming increasingly diverse, leading to a continuous emergence of complex computational tasks. Facing these tasks, a single vehicle node often struggles to handle them effectively; thus, it is necessary to offload tasks to other vehicles with computational resources through Vehicle-to-Vehicle (V2V) communication. However, due to the mobility of vehicles and the limitations of computing and communication resources, efficiently completing these complex computational tasks presents a significant challenge. To address this, this paper proposes an innovative optimization scheme that combines Digital Twin (DT) technology with vehicular edge computing. It constructs digital twins of vehicles through Roadside Units (RSUs) and utilizes these digital twins to optimize task offloading strategies. The scheme aims to jointly optimize transmission power, task offloading ratios, and computational resource allocation to minimize the impact of communication constraints and vehicle mobility on task completion delay. The paper models the wireless communication channel between vehicles using the Nakagami-m fading model, taking into account both transmission delay and computation delay in the overall task completion time. To solve this non-convex optimization problem, we introduce a joiSACnt optimization framework based on the Soft Actor-Critic (SAC) algorithm for efficient task allocation and dynamic transmission power adjustment. The simulation results show that the proposed scheme significantly reduces the maximum task delay and improves overall communication efficiency, particularly when compared with baseline schemes without power optimization and digital twin modules, as well as the DQN and DDPG algorithms. It demonstrates better task processing efficiency and communication performance, providing an effective solution for task handling in vehicular networks. Full article

This paper presents research on the security performance of a multi-user interference-based mixed RF/FSO system based on SWIPT untrusted relay. In this work, the RF and FSO channels experience Nakagami-m fading distribution and Málaga (M) turbulence, respectively. Multiple users transmit messages to the destination with the help of multiple cooperating relays, one of which may become an untrusted relay as an insider attacker. In a multi-user network, SWIPT acts as a charging device for each user node. In order to prevent the untrusted relays from eavesdropping on the information, some users are randomly assigned to transmit artificial noise in order to interfere with untrusted relays, and the remaining users send information to relay nodes. Based on the above system model, the closed-form expressions of secrecy outage probability (SOP) and average secrecy capacity (ASC) for the mixed RF/FSO system are derived. The correctness of these expressions is verified by the Monte Carlo method. The influences of various key factors on the safety performance of the system are analyzed by simulations. The results show that the security performance of the system is considerably improved by increasing the signal–interference noise ratio, the number of interfering users, the time distribution factor and the energy conversion efficiency when the instantaneous signal-to-noise ratio (SNR) of the RF link instantaneous SNR is low. Full article