Search Results (84)

Predictive maintenance (PdM) is central to Industry 5.0 strategies for reducing unplanned downtime in rotating machinery. This work proposes and evaluates, as a proof of concept on a controlled single-machine testbed, a multimodal TinyML edge architecture for PdM designed to remain compatible across the application plane’s evolution toward sixth-generation (6G) networks. Three complementary modalities run local inference on commercial off-the-shelf smart sensor nodes—vibration, acoustic, and thermography—with an embedded gateway bridging per-modality decisions to a serverless cloud back-end. Using real vibration data from a controlled static-unbalance protocol, five anomaly-detection model variants, operating on ten frequency-independent time-domain features extracted from 6 s windows, are benchmarked on the actual Cortex-M4F target; the INT8-quantized fully connected autoencoder, scored by per-window reconstruction error, reaches F1 = 0.9807 with 254 µs inference latency and a 6056 B Flash footprint, well within the microcontroller budget. In a second acquisition session with the remounted sensor, the frozen model retains perfect fault recall, and a short per-installation healthy-baseline recalibration restores F1 = 0.975 without any weight retraining. The acoustic modality is classified in-sensor on log-Mel filterbank energies by the Syntiant NDP120 neural coprocessor, and the thermographic modality by a lightweight binary CNN on 96 × 96 px frames. A preliminary intra-session late-fusion analysis suggests that a logistic-regression meta-learner over the three modality confidence scores can improve on single-modality baselines when no single modality already saturates, motivating multimodal sensing primarily for robustness and redundancy. An end-to-end latency experiment shows that the cloud-uplink leg dominates the budget (79–88%), establishing edge-first inference as a necessary condition for 6G URLLC gains to be observable at the application level. All experiments are conducted over Wi-Fi and MQTT with no 5G or 6G radio, so 6G compatibility is presented as a forward-looking roadmap rather than a tested capability. Full article

Mobile Radio Frequency Identification (RFID) systems are emerging as a fundamental part of modern smart environments, enabling automatic identification, tracking, and data exchange among different mobile platforms. While these systems are increasingly being adopted, they have a major drawback: an RFID tag has very little computational power, and the wireless communication channels can be attacked by adversaries. Several authentication and key management mechanisms to protect data and provide secure access have been proposed to solve these problems. In this study, we propose a new scheme that improves system security through explicit three-party mutual authentication, epoch-based pseudonym indexing for $O\left(1\right)$ server lookup, and comprehensive resiliency against replay, impersonation, and man-in-the-middle attacks. An in-depth security analysis, along with performance evaluation, substantiates that the proposed protocol improves privacy and resilience without losing compatibility with low-cost RFID tags equipped only to perform lightweight cryptographic functions. This protocol also provides epoch-based unlinkability and is well suited for large-scale deployments, as found in healthcare, logistics, and Internet of Things (IoT) applications. Full article

This paper proposes a microstrip touch sensing design compatible with radio frequency (RF) signal communication ability. The design is based on surface plasmon polaritons (SPPs) and employs a microstrip touch sensing structure with multiple periodic parallel open circuit branches, which is further connected in parallel with the signal transmission microstrip. The SPP structure is designed in a U-shaped structure and exhibits multiple resonance characteristics for RF signals. Its S-parameter in the low frequency band is affected by finger or medium touch, while the parallel microstrip transmission line correspondingly maintains signal transmission capability in the high frequency band, which remains unaffected. A physics-informed regression framework based on spectral alignment and Gaussian Process Regression (GPR) is introduced for the analysis of both simulation and experimental results. Based on the spectral-position relationship, touch position detection with an accuracy of within 5 mm is achieved by monitoring changes in the S-parameter response below 4.7 GHz. Meanwhile, a communication passband unaffected by tactile sensing is maintained within the 4.7 GHz to 6.0 GHz frequency range. This design demonstrates significant potential for applications requiring integrated sensing and communication (ISAC), including the Internet of Things and smart wearable devices. Full article

The development of electronic substrates from locally available materials is critical for sustainable lunar infrastructure. This work investigates the synthesis, processing, and characterization of cyanate ester–lunar regolith simulant (CE-LRS) composites designed specifically for the extreme lunar environment. LRS were evaluated as functional fillers at loadings up to 55 wt.% with CE binder selected for its thermal stability (T_g > 230 °C), vacuum compatibility, and known radiation resistance from prior literature. A vacuum-assisted curing procedure was developed that utilizes the lunar environment as a processing advantage, reducing porosity from approximately 7% to less than 1% as quantified by X-ray micro-computed tomography. Dynamic mechanical analysis revealed that increased filler loading and vacuum processing enhanced the storage modulus and T_g through constraining polymer chain mobility at the filler-binder interface, confirming effective stress transfer and interfacial adhesion. Scanning electron microscopy also verified intimate polymer–filler wetting. Waveguide measurements in the microwave frequency range demonstrated that the composites remain non-magnetic while exhibiting moderately increased permittivity and low dielectric loss, meeting the requirements for radio-frequency substrate applications. Through material selection and process design that embraces, rather than ignores, lunar environmental constraints, this work establishes the CE-LRS composites that represent a viable pathway for the in situ fabrication of structural electronics on the Moon. Full article

Automatic modulation recognition (AMR) is increasingly relevant to communication-sensing front ends in robotic and human–robot collaborative systems, where reliable spectrum awareness and adaptive wireless reception are desired. However, existing methods often degrade sharply at low signal-to-noise ratios (SNRs), and large language models (LLMs) are not natively compatible with continuous I/Q signals due to the inherent modality gap. We propose BioLAMR, a GPT-2 adaptation framework for AMR inspired by the auditory system’s parallel time–frequency processing and cortical hierarchy. The framework combines bio-inspired dual-domain feature extraction with parameter-efficient LLM adaptation. BioLAMR includes three components. First, a lightweight dual-domain fusion (LDDF) module extracts complementary time- and frequency-domain features and fuses them through channel and spatial attention. Second, a convolutional embedding module converts continuous I/Q signals into GPT-2-compatible sequences without discrete tokenization. Third, a hierarchical fine-tuning strategy updates only 8.9% of parameters to preserve pretrained knowledge while adapting to modulation recognition. Experiments on the RadioML2016.10a and RadioML2016.10b benchmarks show that BioLAMR achieves overall accuracies of 64.99% and 67.43%, outperforming the strongest competing method by 2.60 and 2.47 percentage points, respectively. Under low-SNR conditions, it reaches 36.78% and 38.14%, the best results among the compared methods. Ablation studies verify the contribution of each component. These results demonstrate that combining dual-domain signal modeling with parameter-efficient GPT-2 adaptation is an effective route to robust AMR in challenging wireless environments. Full article

This paper proposes a SIM-compatible hardware coordination architecture for secure radio-frequency (RF)-triggered activation in mobile devices. The proposed concept functions as a passive coordination layer rather than as an additional wireless transceiver, enabling controlled interaction between external low-frequency RFID or high-frequency NFC fields and wireless subsystems already available in the host device. The architecture assumes a flexible nano-SIM-compatible form factor integrating passive RF detection structures, a trusted decision component, and a trigger-generation interface aligned with standard SIM/UICC electrical and logical interaction models. Upon detection of an external electromagnetic field, the coordination layer evaluates predefined authorization conditions and produces a controlled trigger event intended to propagate through existing telephony and system-service pathways. In contrast to architectures that embed active wireless transmitters, the proposed approach seeks to minimize hardware redundancy and reduce potential attack surfaces by relying on the host device’s native Bluetooth Low Energy (BLE) capabilities. Rather than directly controlling wireless modules, the interface operates as a hardware-originated coordination mechanism that may support low-power and context-aware activation scenarios in mobile and embedded environments. This paper focuses on the architectural model, system assumptions, security rationale, and implementation constraints of such a SIM-compatible interface. Particular attention is given to integration considerations related to smartphone baseband architectures, operating-system mediation, and secure-element isolation. The presented concept establishes a foundation for future prototype implementation and platform-specific validation of SIM-compatible RF-triggered coordination mechanisms. Full article

This paper presents the design, optimization, and performance evaluation of a Satellite-Based Augmentation System (SBAS) ground segment tailored to Colombia’s air navigation infrastructure, with emphasis on ionospheric anomalies in equatorial latitudes. The configuration comprises six Reference Stations (RIMS), strategically sited via geometric dilution of precision (GDOP) minimization and airspace demand models from ADS-B data. A simulation suite—integrating STK^®, Radio Mobile™, and Stanford-ESA certified monitors—quantifies service volume, link margins, and protection level compliance. Ionospheric threat characterization uses regional scintillation datasets (σln ≈ 0.36, ROTI₉₅ ≈ 85 mm/km), informing GIVE inflation and dual-frequency pseudorange integrity validation. Simulations confirm the system sustains ≥ 99.8% APV-I availability over the CAR/SAM FIR, with Horizontal and Vertical Protection Levels (HPL/VPL) bounded below 28 m and 46 m. Uplink integrity and GEO broadcast continuity are modelled under worst-case masking and multipath, confirming ICAO Annex 10 SARPs compliance. The architecture achieves a high performance-to-cost ratio, enabling nationwide SBAS coverage with a 65% cost reduction versus legacy navaids. The system is forward-compatible with dual-frequency multi-constellation SBAS (DFMC), supporting future APV-II scalability. These results position Colombia as a regional node for GNSS augmentation, fostering safety, efficiency, and procedural harmonization. Full article

This paper presents a broadband compact omnidirectional UHF antenna–radome package for airborne applications, where reliable communication, low observability, and electromagnetic compatibility are critical. Omnidirectional radiation is essential for maintaining consistent radio communication links regardless of aircraft attitude during flight. Conventional blade antennas achieve such coverage but suffer from increased aerodynamic drag, higher radar cross-section (RCS), and limited conformal integration capability. To address these limitations, a low-profile hybrid structure combining a patch radiator with a broadband monocone is proposed. An integrated metallic ground wall reduces sensitivity to installation surroundings, suppresses structural interference, and enhances RF (Radio Frequency) compatibility. The antenna achieves an electrical size of 0.555λ × 0.555λ × 0.072λ at 338 MHz. A lightweight sandwich-structured glass fiber-reinforced plastic (GFRP) radome is fabricated to ensure mechanical robustness and environmental protection while maintaining negligible RF loss. Measurements confirm a −10 dB bandwidth of 32.7%, stable omnidirectional radiation, and gain exceeding −0.2 dBi throughout the operating band with peak realized gain of 2.6 dBi within the investigated frequency range. The radome causes negligible gain degradation, with insertion loss below 0.4 dB. The proposed package provides a practical solution for airborne platforms requiring compact, broadband, and installation-resilient antenna systems. Full article

Visible Light Positioning (VLP) is widely regarded as a promising technology for high-precision indoor localization due to its immunity to radio-frequency interference and compatibility with existing Light-Emitting Diode (LED) lighting infrastructure. Despite recent progress, current VLP systems remain fundamentally limited by nonlinear received signal strength (RSS) characteristics, unknown transmitter orientations, and dynamic indoor disturbances. Existing solutions typically address these challenges in isolation, resulting in limited robustness and scalability. This paper proposes SCENE-VLP (Sequential Deep Learning with Feature Compression and Optimal State Estimation), a structured positioning framework that integrates feature compression, temporal sequence modeling, and probabilistic state refinement within a unified estimation pipeline. Specifically, SCENE-VLP combines Principal Component Analysis (PCA) and Denoising Autoencoders (DAE) for linear and nonlinear observation conditioning, Gated Recurrent Units (GRU) for modeling temporal dependencies in RSS sequences, and Kalman-based filtering (KF/EKF) for recursive state-space refinement. The framework is formulated as a hierarchical approximation of the nonlinear observation model, linking data-driven measurement learning with Bayesian state estimation. A systematic ablation study across multiple scenarios, including same-dataset evaluation and cross-dataset generalization, demonstrates that each component provides complementary benefits. Feature compression reduces redundancy while preserving dominant signal structure; GRU significantly improves robustness over static regression; and recursive filtering consistently reduces positioning error compared to unfiltered predictions. While both KF and EKF improve performance, EKF provides incremental refinement under mild nonlinearities. Extensive simulations conducted on an indoor dataset collected from a realistic deployment with eight ceiling-mounted LEDs and a single photodetector (PD) show that SCENE-VLP achieves sub-decimeter localization accuracy, with P50 and P95 errors of 1.84 cm and 6.52 cm, respectively. Cross-scenario evaluation further confirms stable generalization and statistically consistent improvements. These results demonstrate that the structured integration of observation conditioning, temporal modeling, and Bayesian refinement yields measurable gains beyond partial pipeline configurations, establishing SCENE-VLP as a robust and scalable solution for next-generation indoor visible light positioning systems. Full article

Porous silicon (PSi), characterized by its high specific surface area and highly tunable morphology, presents significant potential across optoelectronics, energy storage, and biomedical applications. This review provides a systematic analysis of the synthesis methodologies, interfacial chemical engineering, and diverse applications of PSi. Initially, fabrication techniques are examined, contrasting the pore formation mechanisms of electrochemical anodization, metal-assisted chemical etching (MACE), and emerging vapor-phase etching methods, while elucidating the control of geometric parameters from microporous to macroporous scales. To address the thermodynamic instability of the hydride-terminated surface, this review systematically evaluates modification strategies such as thermal oxidation, hydrosilylation, carbonization, and atomic layer deposition (ALD). We critically analyze their efficacy in mitigating oxidative drift and enabling specific functionalization. Subsequently, the review summarizes current applications in sensing (refractive index and photoluminescence modulation), energy storage (lithium-ion battery anodes and supercapacitors), and microsystem technologies (radio frequency (RF) isolation, gettering, and micro-electro-mechanical systems (MEMS) sacrificial layers), emphasizing the critical role of structure–property relationships. Finally, an objective assessment is provided regarding the challenges in translating PSi technology to industrial scales, specifically addressing the trade-offs between biodegradability and stability, wafer-scale process uniformity, and the compatibility of wet-chemical processing with standard complementary metal–oxide–semiconductor (CMOS) integration flows. Full article

Self-heating effects severely limit the performance of gallium nitride high-electron-mobility transistors (GaN HEMTs) in high-power radio frequency (RF) applications. Diamond capping technology leveraging diamond’s exceptional thermal conductivity (>2000 W/m·K) has emerged as a highly promising near-junction cooling solution. However, its integration with GaN HEMTs faces challenges including lattice/thermal mismatch, high thermal boundary resistance (TBR), and process compatibility. This review summarizes recent progress in high-thermal-conductivity diamond film growth, TBR optimization, thermal simulations, and the integrated process with GaN devices. These technological breakthroughs enable diamond-capped GaN HEMTs with an excellent comprehensive performance. Continued advances in these fields will be critical for fully releasing the capabilities of diamond capping technology for GaN HEMTs in high-frequency and high-power applications. Full article

Recent developments in sixth-generation (6G) communication systems have increased interest in using sub-terahertz frequencies, particularly the W-band (75–110 GHz), for high-capacity indoor links. At these frequencies, electromagnetic (EM) wave attenuation introduced by building materials becomes a key factor limiting system performance. The objective of this study is to provide continuous, laboratory-validated attenuation characteristics of commonly used construction and finishing materials across the full W-band. Measurements were conducted in an accredited electromagnetic compatibility laboratory using a calibrated far-field setup with a vector network analyzer, W-band frequency extenders, and standard-gain horn antennas inside an anechoic chamber. For each frequency point, 20 measurements were recorded under controlled environmental conditions. The results show distinct attenuation behaviour depending on material type: wood-based materials exhibit 6–13 dB/cm, construction materials 2–4 dB/cm, and insulation materials below 0.3 dB/cm, while ceramic materials exceed 15–23 dB/cm. A general increase in attenuation with frequency is observed, particularly for materials with higher dielectric losses. The presented dataset enables more accurate indoor propagation modelling, supports ray-tracing and link-budget analyses, and provides practical guidelines for designing radio-transparent building components for future 6G communication systems. Full article

This paper presents an advanced signal processing framework for multi-channel forward-scatter radar (MC-FSR) systems based on the Multiple Signal Classification (MUSIC) algorithm. The proposed framework addresses the inherent limitations of FFT-based space-domain processing, such as limited angular resolution and the poor detectability of weak or closely spaced targets, which become particularly severe in low-cost FSR systems, which are typically operated with small antenna arrays. The MUSIC algorithm is adapted to operate on real-valued data obtained from the non-coherent, amplitude-based MC-FSR approach by reformulating the steering vectors and adjusting the degrees of freedom (DoFs). While compatible with arbitrary transmitting waveforms, particular emphasis is placed on Orthogonal Frequency Division Multiplexing (OFDM) signals, which are widely used in modern communication systems such as Wi-Fi and cellular networks. An analysis of the OFDM waveform’s autocorrelation properties is provided to assess their impact on target detection, including strategies to mitigate rapid target signature decay using a sub-band approach and to manage signal correlation through spatial smoothing. Simulation results, including multi-target scenarios under constrained array configurations, demonstrate that the proposed MUSIC-based approach significantly enhances angular resolution and enables reliable discrimination of closely spaced targets even with a limited number of receiving channels. Experimental validation using an S-band MC-FSR prototype implemented with software-defined radios (SDRs) and commercial Wi-Fi antennas, involving cooperative targets like people and drones, further confirms the effectiveness and practicality of the proposed method for real-world applications. Overall, the proposed MUSIC-based MC-FSR framework exhibits strong potential for implementation in low-cost, hardware-constrained environments and is particularly suited for emerging Integrated Sensing and Communication (ISAC) systems. Full article

We present an experimental demonstration of a daylight-capable Optical Amplify-and-Forward (OAF) relaying system designed to support flexible and high-capacity network topologies. The proposed architecture integrates fiber-based infrastructure with OAF Free Space Optics (FSO) relaying, enabling bidirectional optical communication over 460 m (x2) using SFP-compatible schemes, while addressing Non-Line-of-Sight (NLOS) constraints and fiber disruptions. This work achieves a Bit Error Rate (BER) below the Hard-Decision Forward Error Correction (HD-FEC) limit, validating the feasibility of high-speed urban FSO links. By leveraging low-cost fiber-coupled optical terminals, the system transmits single-carrier 120 Gbps Intensity Modulation/Direct Detection (IM/DD) signals using NRZ (Non-Return-to-Zero) and PAM4 (4-Pulse Amplitude Modulation) modulation formats. Operating entirely in the optical C-Band domain, this approach ensures compatibility with existing infrastructure, supporting scalable mesh FSO deployments and seamless integration with hybrid Radio Frequency (RF)/FSO systems. Full article

Dynamic Spectrum Sharing (DSS) enables spectrum sharing between Long-Term Evolution (LTE) and New Radio (NR) systems, addressing spectrum scarcity in NR. To avoid interference when supporting NR traffic within LTE spectrum, key factors must be compatible. Effective DSS techniques are essential for coexistence. This paper discusses these issues in two parts. Part I covers LTE and NR coexistence using DSS, introducing resource grids, control signals, and channels, and explores DSS approaches for NR data traffic, including NR Synchronization Signal/Physical Broadcast Channels (SSB) transmission via LTE Multicast-Broadcast Single-Frequency Network (MBSFN) and non-MBSFN subframes with associated challenges and standardization efforts for DSS improvement. Part II presents a DSS technique using MBSFN subframes in a heterogeneous network with a macrocell and picocells running on LTE, and in-building small cells running on NR, sharing LTE spectrum via DSS. An optimization problem is formulated to manage traffic through MBSFN allocation, determining the optimal number of MBSFN subframes per LTE frame. System simulations indicate DSS improves Spectral and Energy Efficiency in small cells. The paper concludes with key lessons for LTE and NR coexistence. Full article