Search Results (118)

Integrating Joint Source–Channel Coding (JSCC) with the LoRa Chirp Spread Spectrum (CSS) physical layer (PHY) presents a significant challenge due to the complexity of joint optimization, which remains underexplored despite the known advantages of JSCC. Traditional LoRa systems rely on decoupled source and channel coding, resulting in redundant overhead and limited adaptability under dynamic Wireless Body Area Network (WBAN) conditions. To address these limitations, we propose a novel LoRa–JSCC framework: a fully learned, end-to-end differentiable architecture that jointly optimizes source compression and channel redundancy. The proposed system integrates a Denoising Autoencoder (DAE) for non-linear source compression with learned neural channel encoder and decoder modules, trained via backpropagation to minimize reconstruction distortion under noisy channel conditions. Rigorous Monte Carlo simulations conducted under unified and reproducible channel conditions demonstrate consistent performance improvements across LoRa configurations. The proposed approach achieves an average 25–30% improvement in goodput across moderate-to-high SNR regimes, with gains exceeding 100% under noise-limited conditions. It further reduces Time on Air (ToA) by approximately 30–35%, enhancing spectral efficiency and lowering effective energy cost per delivered bit. In the transitional Bit Error Rate (BER) region, the proposed LoRa–JSCC framework exhibits an effective SNR gain of approximately 18–20 dB relative to conventional LoRa, corresponding to multiple orders-of-magnitude reduction in BER. These results indicate substantial improvements in reliability, coverage robustness, and energy efficiency for WBAN and IoT deployments. Full article

With more renewables being integrated into distribution grids, the problem of voltage fluctuation has become prominent. Effective Volt/VAR regulation is a commonly used method to ensure the safe operation of distribution networks. Model-based approaches tend to work well only if detailed network parameters are available, while data-driven approaches can suffer from overfitting and may not generalize well. We created the PHY-GAT-SAC framework to address these issues. Physics-regularized reinforcement learning uses bidirectional graph attention, which combines a physics-informed model with a safety projection method that relies on sensitivity matrices. This makes it so that the voltage regulation is practical, interpretable, and secure. The framework works with two combined branches. One branch takes care of the nonlinear mapping from power injections to voltage states using a forward graph encoder and a reverse consistency constraint. At the same time, another branch extracts features directly from the voltages to improve the perception of system violation risk. The framework has a sensitivity-based safety layer as well. This layer projects every control action into a feasible area formed by linearized voltage restrictions, thus securing operation safety. Experiments on an IEEE 33-node system show that the framework works well. A safety layer guarantees a safe operating range without exact impedance values. And PHY-GAT-SAC greatly lowers voltage violations compared to multi-agent deep reinforcement learning. By successfully combining physics with learning, this study gives a unified framework for merging graph neural networks and reinforcement learning within intricate grid management. Full article

This paper introduces a novel methodology that integrates 6G wireless Federated Edge Learning (FEEL) frameworks with MAC to PHY cross layer optimization strategies. In the context of mobile edge computing, typically ensuring robust channel estimation within the 6G network use cases presents critical challenges, particularly in managing data retransmissions. Inaccurate updates from distributed 6G devices can undermine the reliability of federated learning, affecting its overall performance. To address this, rather than relying on direct evaluations of the objective function, we propose an AI/ML-assisted algorithm for global optimization based on radial basis functions (RBFs) decision-making process to assess learned preference options. Full article

Slicing functionality makes it possible for an operator to share a 5G physical infrastructure between several virtual networks operated by different institutions. The deployed slices can support a wide range of applications with conflicting QoS targets. The coexistence of these slices on top of a common infrastructure is challenging and remains an open issue. Identifying traffic associated with a given type of slice is required to operate and control network resources in an efficient and secure way. This work proposes new algorithms operating at the physical and MAC layers. The solutions designed identify traffic generated by URLLC and eMBB slices by defining a new LightGBM framework. The algorithms can operate at the base station level in an O-RAN-type architecture. They provide a valuable input to radio resource management and traffic steering procedures. Full article

Wireless Sensor Networks (WSNs) operate under strict energy constraints and are therefore highly vulnerable to radio interference, particularly jamming attacks that directly affect communication availability and network lifetime. Although jamming and anti-jamming mechanisms have been extensively studied, energy is frequently treated as a secondary metric, and analyses are often conducted in partial isolation from system assumptions, protocol behavior, and deployment context. This fragmentation limits the interpretability and comparability of reported results. This article presents a systematic literature review (SLR) covering the period from 2004 to 2024, with a specific focus on energy-aware jamming and mitigation strategies in IEEE 802.15.4-based WSNs. To ensure transparency and reproducibility, the literature selection and refinement process is formalized through a mathematical search-and-filtering model. From an initial corpus of 482 publications retrieved from Scopus, 62 peer-reviewed studies were selected and analyzed across multiple dimensions, including jamming modality, affected protocol layers, energy consumption patterns, evaluation assumptions, and deployment scenarios. The review reveals consistent energy trends among constant, random, and reactive jamming strategies, as well as significant variability in the energy overhead introduced by defensive mechanisms at the physical (PHY), Medium Access Control (MAC), and network layers. It further identifies persistent methodological challenges, such as heterogeneous energy metrics, incomplete characterization of jamming intensity, and the limited use of real-hardware testbeds. To address these gaps, the paper introduces an energy-centric taxonomy that explicitly accounts for attacker–defender energy asymmetry, cross-layer interactions, and recurring experimental assumptions, and proposes a minimal set of standardized energy-related performance metrics suitable for IEEE 802.15.4 environments. By synthesizing energy behaviors, trade-offs, and application-specific implications, this review provides a structured foundation for the design and evaluation of resilient, energy-proportional WSNs operating under availability-oriented adversarial interference. Full article

The Internet of Military Things (IoMT) relies on Long-Range Wide Area Networks (LoRaWAN) for low-power, long-range communication in critical applications like border security and soldier health monitoring. However, conventional priority-based flow control mechanisms, which rely on static classification thresholds, lack the adaptability to handle the nuanced, continuous nature of physiological data and dynamic network states. To overcome this rigidity, this paper introduces a novel, domain-adaptive Fuzzy Logic Flow Control (FFC) protocol specifically tailored for LoRaWAN-based IoMT. While employing established Mamdani inference, the FFC system innovatively fuses multi-parameter physiological data (body temperature, blood pressure, oxygen saturation, and heart rate) into a continuous Health Score, which is then mapped via a context-optimised sigmoid function to dynamic transmission intervals. This represents a novel application-layer semantic integration with LoRaWAN’s constrained MAC and PHY layers, enabling cross-layer flow optimisation without protocol modification. Simulation results confirm that FFC significantly enhances reliability and energy efficiency while reducing latency relative to traditional static priority architectures. Seamlessly integrated into the NS-3 LoRaWAN simulation framework, the FFC protocol demonstrates superior performance in IoMT communications. Simulation results confirm that FFC significantly enhances reliability and energy efficiency while reducing latency compared with traditional static priority-based architectures. It achieves this by prioritising high-priority health telemetry, proactively mitigating network congestion, and optimising energy utilisation, thereby offering a robust solution for emergent, health-critical scenarios in resource-constrained environments. Full article

Lightweight, lead-free polymer–mineral composites have attracted increasing interest as radiation-attenuating materials for applications where reduced mass and environmental compatibility are required. In this work, the $\gamma$-ray attenuation behavior of poly(ether ether ketone) (PEEK) reinforced with natural palygorskite and pumice was evaluated at filler concentrations of 10–40 wt%. Photon interaction parameters, including the linear attenuation coefficient ($\mu$), half-value layer (HVL), mean free path ($\lambda$), and effective atomic number ($Z_{\mathrm{eff}}$), were computed over the energy range 15 keV–15 MeV using the Phy-X/PSD platform and validated through full Geant4 Monte Carlo transmission simulations. At 15 keV, $\mu$ increased from $1.46{\mathrm{cm}}^{-1}$ for pure PEEK to $4.21{\mathrm{cm}}^{-1}$ and $8.499{\mathrm{cm}}^{-1}$ for the 40 wt% palygorskite- and pumice-filled composites, respectively, reducing the HVL from 0.69 cm to 0.24 cm and 0.11 cm. The corresponding $Z_{\mathrm{eff}}$ values increased from 6.5 (pure PEEK) to 9.4 (40 wt% palygorskite) and 15.3 (40 wt% pumice), reflecting the influence of higher-Z oxide constituents in pumice. At higher photon energies, the attenuation curves converged as Compton scattering became dominant, although pumice-filled PEEK retained marginally higher $\mu$ and shorter $\lambda$ up to the MeV region. These findings demonstrate that natural mineral fillers can enhance the photon attenuation behavior of PEEK while retaining the known thermal stability and mechanical performance of the polymer matrix as reported in the literature, indicating their potential use as lightweight, secondary radiation-attenuating components in medical, industrial, and aerospace applications. Full article

This study evaluates lead-free high-density polyethylene (HDPE) composites reinforced with high-Z oxides (Bi₂O₃, WO₃, Gd₂O₃, TeO₂, and a Bi₂O₃/WO₃ hybrid) as lightweight materials for gamma-ray and fast-neutron shielding. A hybrid computational framework combining Phy-X/PSD with Geant4 Monte Carlo simulations was used to obtain key shielding parameters, including the linear and mass attenuation coefficients (μ, μ/ρ), half-value layer (HVL), mean free path (MFP), effective atomic number (Z_eff), effective electron density (N_eff), exposure and energy-absorption buildup factors (EBF, EABF), and fast-neutron removal cross section (Σ_R). The incorporation of heavy oxides produced a pronounced improvement in gamma-ray attenuation, particularly at low energies, where the linear attenuation coefficient increased from below 1 cm⁻¹ for neat HDPE to values exceeding 130–150 cm⁻¹ for Bi- and W-rich composites. In the intermediate Compton-scattering region (≈0.3–1 MeV), all oxide-reinforced systems maintained a clear attenuation advantage, with μ values around 0.12–0.13 cm⁻¹ compared with ≈0.07 cm⁻¹ for pure HDPE. At higher photon energies, the dense composites continued to outperform the polymer matrix, yielding μ values of approximately 0.07–0.09 cm⁻¹ versus ≈0.02 cm⁻¹ for HDPE due to enhanced pair-production interactions. The Bi₂O₃/WO₃ hybrid composite exhibited attenuation behavior comparable, and in some regions slightly exceeding, that of the single-oxide systems, indicating that mixed fillers can effectively balance density and shielding efficiency. Oxide addition significantly reduced exposure and energy-absorption buildup factors below 1 MeV, with a moderate increase at higher energies associated with secondary radiation processes. Fast-neutron removal cross sections were also modestly enhanced, with Gd₂O₃-containing composites showing the highest values due to the combined effects of hydrogen moderation and neutron capture. The close agreement between Phy-X/PSD and Geant4 results confirms the reliability of the dual-method approach. Overall, HDPE composites containing about 60 wt.% oxide filler offer a practical compromise between shielding performance, manufacturability, and environmental safety, making them promising candidates for medical, nuclear, and aerospace radiation-protection applications. Full article

Environmentally friendly materials with superior structural, physical, optical, and shielding capabilities are of great technological importance and are continually being investigated. In this work, novel multicomponent borate glasses with the composition xTiO₂-10BaO-5Al₂O₃-5WO₃-20Bi₂O₃-(60-x) B₂O₃, where 0 ≤ x ≤ 15 mol%, were produced via the melt-quenching technique. The increase in TiO₂ content results in a decrease in molar volume and a corresponding increase in density, indicating the formation of a compact, rigid, and mechanically hard glass network. Elastic constant measurements further confirmed this behavior. FTIR analysis confirms the transformation of BO₃ to BO₄ units, signifying improved network polymerization and structural stability. The prepared glasses exhibit an optical absorption edge in the visible region, demonstrating their strong ultraviolet light blocking capability. Incorporation of TiO₂ leads to an increase in refractive index, optical basicity, and polarizability, and a decrease in the optical band gap and metallization number; all of these suggest enhanced electron density and polarizability of the glass matrix. Radiation shielding properties were evaluated using Phy-X/PSD software. The outcomes illustrate that the Mass Attenuation Coefficient (MAC), Effective Atomic Number (Z_eff), Linear Attenuation Coefficient (LAC) increase, while Mean Free Path (MFP) and Half Value Layer (HVL) decrease with increasing TiO₂ at the expense of B₂O₃, confirming superior gamma-ray attenuation capability. Additionally, both TiO₂-doped and undoped samples show higher fast neutron removal cross sections (FNRCS) compared to several commercial glasses and concrete materials. Overall, the incorporation of TiO₂ significantly enhances the optical performance and radiation-shielding efficiency of the environmentally friendly glass system, making these potential candidates for advanced photonic devices and radiation-shielding applications. Full article

Lightweight and lead-free radiation shields are increasingly developed to overcome the toxicity and handling challenges associated with conventional heavy-metal-based materials. In this study, the $\gamma$-ray attenuation behavior of polymer–zeolite composites was examined by reinforcing high-density polyethylene (HDPE) and polylactic acid (PLA) with natural clinoptilolite zeolite at concentrations of 10–40 wt%. Photon-interaction parameters, including the linear attenuation coefficient ($\mu$), half-value layer (HVL), mean free path ($\lambda$), and effective atomic number ($Z_{\mathrm{eff}}$), were evaluated over 15 keV–15 MeV using the Phy-X/PSD platform. Zeolite incorporation consistently enhanced photon attenuation, particularly at low energies dominated by the photoelectric effect. At 15 keV, the HVL decreased from 0.60 cm to 0.08 cm for HDPE and from 0.043 cm to 0.033 cm for PLA as the zeolite loading increased to 40 wt%. Correspondingly, $Z_{\mathrm{eff}}$ increased from 2.7 to 4.3 for HDPE and from 6.5 to 11.6 for PLA, while $\mu$ reached approximately 41 cm⁻¹ and 56 cm⁻¹ at 15 keV for the respective 40 wt% composites. Beyond about 1 MeV, differences between compositions became minimal as Compton scattering dominated. PLA–zeolite composites exhibited higher $\mu$ and lower HVL than HDPE–zeolite, whereas HDPE maintained an advantage in mixed-field environments owing to its hydrogen-rich matrix. The results confirm that zeolite-reinforced polymers are safe, low-cost, and lightweight materials suitable for radiation shielding in medical, nuclear, and aerospace applications. Full article

The evolution from fifth generation (5G) to sixth generation (6G) networks demands a paradigm shift from AI-assisted functionalities to AI-native orchestration, where intelligence is intrinsic to the radio access network (RAN). This work introduces two AI-based enablers for PHY-layer awareness: (i) a waveform classifier that distinguishes orthogonal frequency-division multiplexing (OFDM) and orthogonal time frequency space (OTFS) signals directly from in-phase/quadrature (IQ) samples, and (ii) a numerology detector that estimates subcarrier spacing, fast Fourier transform (FFT) size, slot duration, and cyclic prefix type without relying on higher-layer signaling. Experimental evaluations demonstrate high accuracy, with waveform classification achieving 99.5% accuracy and numerology detection exceeding 99% for most parameters, enabling robust joint inference of waveform and numerology features. The obtained results confirm the feasibility of AI-native spectrum awareness, paving the way toward self-optimizing, context-aware, and adaptive 6G wireless systems. Full article

This paper presents a performance analysis of Direct Current-biased Optical OFDM (DCO-OFDM) under the IEEE 802.11bb standard for Visible Light Communication (VLC). The study covers all physical layer (PHY) modes (HT, VHT, and HE) through a complete simulation of the PHY processing chain, including scrambling, convolutional encoding, interleaving, and modulation. These results provide a standard-driven recipe to tune VLC transmitters while preserving IEEE 802.11bb interoperability. To the best of current knowledge, this is among the first IEEE 802.11bb-compliant evaluations of DCO-OFDM for VLC that jointly examine DC-biasing strategies and optical channel dispersion across HT/VHT/HE modes. The novelty lies in the presentation of practical and standard-oriented standard-based design guidelines for transmitter optimization under IEEE 802.11bb, rather than a new analytical model. This work provides one of the first IEEE 802.11bb-compliant evaluations of DCO-OFDM in VLC that jointly studies DC-biasing (static/dynamic/clipping) and optical dispersion ($L=1/3/5$) across HT/VHT/HE, reporting SNR@BER = 10⁻³ baselines, a mean $B_{CD}$ power proxy, and actionable bias–channel–mode design guidelines. Full article

This paper investigates physical layer security (PHY-security) for multi-hop transmission in underlay cognitive radio networks under various eavesdropping attacks. To enhance secrecy performance, we propose two opportunistic scheduling schemes. The first scheme, called the minimal node selection (MNS) scheme, selects the node in each cluster that minimizes the eavesdropper’s channel capacity. The second scheme, named the optimal node selection (ONS) scheme, chooses the node that maximizes secrecy capacity by using both the main and eavesdropper channel information. To reveal the relationship between network parameters and secrecy performance, we derive closed-form expressions for the secrecy outage probability (SOP) under different scheduling schemes and eavesdropping scenarios. Numerical results show that the ONS scheme provides the most robust secrecy performance among the considered schemes. Furthermore, we analyze the impact of key network parameters on secrecy performance. In detail, although the proposed ONS scheme requires more channel information than the MNS scheme, under a 20 dB interference threshold, the secrecy performance of the ONS scheme is 15% more robust than that of the MNS scheme. Full article

The rapid growth of Internet-connected devices integrating into our everyday lives has no end in sight. As more devices and sensor networks are manufactured, security tends to be a low priority. However, the security of these devices is critical, and many current research topics are looking at the composition of simpler techniques to increase overall security in these low-power commercial devices. Transmission security (TRANSEC) methods are one option for physical-layer security and are a critical area of research with the increasing reliance on the Internet of Things (IoT); most such devices use standard low-power Time-division multiple access (TDMA) or frequency-division multiple access (FDMA) protocols susceptible to reverse engineering. This paper provides a hardware validation of previously proposed techniques for the intentional injection of noise into the phase mapping process of a spread spectrum signal used within a receiver-assigned code division multiple access (RA-CDMA) framework, which decreases an eavesdropper’s ability to directly observe the true phase and reverse engineer the associated PRNG output or key and thus the spreading sequence, even at high SNRs. This technique trades a conscious reduction in signal correlation processing for enhanced obfuscation, with a slight hardware resource utilization increase of less than 2% of Adaptive Logic Modules (ALMs), solidifying this work as a low-power technique. This paper presents the candidate method, quantifies the expected performance impact, and incorporates a hardware-based validation on field-programmable gate array (FPGA) platforms using arbitrary-phase phase-shift keying (PSK)-based spread spectrum signals. Full article

Internet of Things (IoT) applications are rapidly adopting low-power wide-area network (LPWAN) technology due to its ability to provide broad coverage for a range of battery-powered devices. LoRaWAN has become the most widely used LPWAN solution due to its physical layer (PHY) design and regulatory advantages. Because LoRaWAN has a broad communication range, the coverage of the gateways might overlap. In LoRa technology, packets can be received concurrently by multiple gateways. Subsequently, the network server selects the packet with the highest receiver strength signal indicator (RSSI). However, this method can lead to the exhaustion of channel availability on the gateways. The optimisation of configuration parameters to reduce collisions and enhance network throughput in multi-gateway LoRaWAN remains an unresolved challenge. This paper introduces a novel low-complexity model for ZBMG-LoRa, mitigates the collisions using channel utilisiation, and categorises nodes into distinct groups based on their respective gateways. This categorisation allows for the implementation of optimal settings for each node’s subzone, thereby facilitating effective communication and addressing the identified issue. By deriving key performance metrics (e.g., network throughput, energy efficiency, and probability of effective delivery) from configuration parameters and network size, communication reliability is maintained. Optimal configurations for transmission power and spreading factor are derived by our method for all nodes in LoRaWAN networks with multiple gateways. In comparison to adaptive data rate (ADR) and other related state-of-the-art algorithms, the findings demonstrate that the novel approach achieves higher packet delivery ratio and better energy efficiency. Full article