Search Results (285)

The rapid development of 6G wireless networks requires ultra-high data rates that traditional microwave frequencies cannot support. Photonics-assisted terahertz (THz) technologies offer a promising solution by combining high-capacity optical fibers with wideband wireless transmission. However, as bandwidth expands, sampling frequency offset (SFO) becomes a critical issue that degrades signal quality in single-carrier systems. This paper evaluates the performance of two main compensation methods within a photonics-assisted THz system operating at 320 GHz. We compare the Gardner clock recovery algorithm and the Digital Interpolation Compensation Algorithm (DICA) across various modulation formats and offset levels. Our findings indicate that the Gardner algorithm is effective for low-order modulation when the SFO is below 100 ppm, but its performance fails outside this range. Conversely, the DICA provides robust compensation up to 1000 ppm regardless of the modulation format, provided that the exact offset value is known. Without proper compensation, the system BER increases significantly as the SFO grows. These results demonstrate the complementary nature of these two algorithms and provide a practical guide for selecting compensation strategies in future high-speed THz communication links. Full article

Efficient and approximate evaluation of urban coverage is important for wireless network planning. While standard statistical propagation models are fast, they do not directly describe the physical environment of a specific urban scene and consequently often fail to accurately capture local blockage and site-specific propagation effects. Ray tracing can model these effects more directly, but becomes costly when testing many tiles, frequencies, and transmitter heights simultaneously. To address this problem, the present study investigates the use of an RT-supervised simulation-to-simulation tile-based learning framework for path loss prediction based on geographic environmental information. This methodology first builds realistic 3D city scenes from geographic data, then uses offline ray tracing to generate supervision labels across multiple carrier frequencies and base-station heights. Each city region is divided into 500 m by 500 m tiles, which are then further discretized into 125 by 125 grids. For each tile, raster priors, such as occupancy, normalized height, and a valid-ground mask, are prepared. During training and inference, the model input is organized as an 8-channel raster tensor together with a 2D condition vector for frequency and transmitter height. The raster tensor combines three stored environment priors and five online-generated transmitter-related feature maps. By utilizing masked supervision, the network learns the excess loss residual exclusively on valid outdoor pixels, and the final path loss map is reconstructed by combining the residual prediction with the FSPL prior. The final model in this work was trained on 134,317 samples and validated on 33,589 samples. In the in-city setting, used as a preliminary verification before subsequent cross-city experiments, it achieved an MAE of 5.0116 dB and an RMSE of 9.3182 dB. On the formal cross-city test with a completely unseen target city, it achieved an MAE of 4.8536 dB and an RMSE of 9.3504 dB. These results demonstrate that the proposed framework can provide a stable tile-level approximation of RT-generated path loss maps under multiple conditions. Because both training labels and evaluation references are generated by RT rather than drive-test measurements, the present study should be understood as a simulation-to-simulation surrogate framework rather than a direct validation of real-world propagation accuracy. Full article

Spectrum scarcity has become a critical issue due to the rapid deployment of fifth-generation (5G) networks and the explosive growth of future wireless data traffic. Spectrally Efficient Frequency Division Multiplexing (SEFDM) is a promising technique to enhance spectral efficiency by compressing subcarrier spacing and allowing spectral overlap; however, it suffers from severe inter-carrier interference (ICI) caused by the loss of orthogonality. In particular, under Rayleigh fading channels, the combined effects of ICI and multipath fading lead to significant degradation in bit error rate (BER) performance. Conventional SEFDM systems employing a cyclic prefix (CP) encounter an unavoidable error floor due to residual interference stemming from non-orthogonality. On the other hand, while zero-padding (ZP)-based SEFDM offers superior multipath tolerance, further enhancement in communication quality is still desired. This paper proposes a novel receiver architecture utilizing sector antennas to spatially separate multipath components based on the angle of arrival (AoA). Furthermore, we investigate and compare sector selection algorithms specifically tailored for SEFDM systems. Simulation results demonstrate that the proposed method, employing a sector selection scheme based on the maximum channel response power, effectively suppresses inter-symbol interference (ISI) and improves BER performance for both CP-SEFDM and ZP-SEFDM. Furthermore, our quantitative evaluations confirm that the proposed architecture successfully achieves the theoretical maximum spectral efficiency even in higher-order modulation schemes (16QAM), while maintaining a low computational complexity compared to conventional spatial diversity techniques. Full article

Data-centric approaches are increasingly shaping wireless communication research, where the availability and quality of datasets directly influence the reliability of learning-based and model-driven methods. In this context, unmanned aerial vehicle (UAV) communication poses unique challenges, as it requires datasets that jointly capture geometric information, propagation conditions, and diverse link configurations. This work introduces a geometry-aware UAV communication dataset designed to support research on controlled UAV communication link directions and propagation scenarios. The dataset is generated using standardized 3GPP and ITU-R channel models across multiple urban, suburban, and rural regions, accounting for variations in altitude, carrier frequency, and node distribution. The dataset provides spatially resolved channel parameters along with geometry-rich files containing environmental features, which can be used to extract relevant parameters for UAV communication studies. These data support reproducible research in geometry-aware channel modelling, path-loss prediction, LOS/NLOS analysis, delay-related modelling, and trajectory-conditioned link-quality analysis. Full article

This paper presents a novel dual-mode memristor-based ring oscillator designed for energy-efficient, wireless biomedical signal conditioning systems. The proposed architecture leverages a compact DTMOS memristor emulator, consisting of only two transistors and one capacitor, to replace the conventional NMOS pull-down devices in a three-stage PMOS ring oscillator. This integration enables two distinct operating modes within a single compact core: a fixed-frequency mode for stable clock generation and carrier synthesis, and a programmable chirp mode for frequency-modulated signal generation. The fixed-frequency mode achieves continuous tuning from 3.142 GHz to 4.017 GHz via varactor control, with an ultra-low power consumption of only 111 µW at 4.017 GHz. The chirp mode generates linear frequency sweeps starting from 0.8 GHz, with the sweep range independently controllable through the state capacitor value and the pulse width of the control signal (SW_Chirp). Designed in a standard 0.18 µm CMOS process, the oscillator exhibits a low phase noise of −87.82 dBc/Hz at a 1 MHz offset for the three-stage configuration, improving to −94.3 dBc/Hz for the five-stage design. The overall frequency coverage spans 0.8–4.017 GHz, representing a 133.6% fractional range. The calculated figure of merit (FoM) is −169.45 dBc/Hz. Experimental validation using a discrete CD4007 prototype confirms the oscillation principle, while comprehensive simulations demonstrate robust performance across process corners and temperature variations. With its zero-static-power memristor core, wide tunability, and dual-mode reconfigurability, the proposed oscillator is ideally suited for multi-standard wireless biomedical applications, including implantable telemetry, neural stimulation, ultra-wideband (UWB) transmitters, and non-contact vital sign monitoring. Full article

The increasing demand for higher data rates in optical communication systems, especially within data centers and backbone networks, calls for the development of advanced modulation formats that can significantly enhance system performance. In this work, we introduce a novel modulation format based on the Kramers–Kronig relations, designed to improve upon traditional techniques such as Pulse Amplitude Modulation (PAM) and Carrier-less Amplitude Phase (CAP) modulation. The novel modulation format was rigorously validated through experimental investigations using an optical wireless communication (OWC) link. The results demonstrate a notable improvement in bit error rate (BER) performance and receiver sensitivity when compared to the conventional PAM-4 modulation scheme and CAP-16 modulation schemes. Moreover, the proposed scheme effectively reduces the complexity of digital filtering required by CAP while lowering the demands on the Digital-to-Analog Converter (DAC), making it a more practical solution for high-speed optical communication. This advancement facilitates higher data transmission rates, proving the Kramers–Kronig relations modulation format as a promising alternative to existing methods. Its potential for enhancing the efficiency and capacity of optical communication systems is evident. Future research will focus on optimizing the modulation parameters and exploring their application in more complex scenarios, such as high-speed underwater visible light communication systems, where advanced modulation formats are crucial for overcoming bandwidth limitations. Full article

Reconfigurable intelligent surfaces (RISs) represent a paradigm shift in wireless communications, offering unprecedented control over electromagnetic wave propagation for next-generation 6G networks. This paper presents a comprehensive framework for high-precision indoor localization exploiting cooperative multi-RIS deployments. We introduce the adaptive multi-stage hybrid localization (AMSHL) algorithm, a novel approach that strategically combines fingerprinting-based and geometric time-difference-of-arrival (TDoA) methods through condition-aware adaptive fusion. The proposed framework employs a 4-RIS cooperative architecture with strategically positioned panels on room walls, enabling comprehensive spatial coverage and favorable geometric diversity. AMSHL incorporates five key innovations: (1) a hybrid fingerprint database combining received signal strength indicator (RSSI) and TDoA features for enhanced location distinctiveness; (2) a multi-stage cascaded refinement process progressing from coarse fingerprinting initialization through to iterative geometric optimization; (3) an adaptive fusion mechanism that dynamically adjusts algorithm weights based on real-time channel quality assessment including signal-to-noise ratio (SNR) and geometric dilution of precision (GDOP); (4) a robust iteratively reweighted least squares (IRLS) solver with Huber M-estimation for outlier mitigation; and (5) Bayesian regularization incorporating fingerprinting estimates as informative priors. Comprehensive Monte Carlo simulations at 3.5 GHz carrier frequency with 400 MHz bandwidth demonstrate that AMSHL achieves a median localization error of 0.661 m, root-mean-squared error (RMSE) of 1.54 m, and mean-squared error (MSE) of 2.38 m², with 87.5% probability of sub-2m accuracy, representing a 4.9× improvement over conventional hybrid fingerprinting in median error and a 7.1× reduction in MSE (from 16.83 m² to 2.38 m²). An optional sigmoid-based fusion variant (AMSHL-S) further improves sub-2m accuracy to 89.4% by eliminating discrete switching artifacts. Furthermore, we provide theoretical analysis including Cramér–Rao lower bound (CRLB) derivation with an empirical MSE comparison to quantify the gap between practical algorithm performance and theoretical bounds (MSE-to-CRLB ratio of approximately $4.0\times {10}^4$), as well as a computational complexity assessment. All reported metrics have been cross-validated for internal consistency across formulas, tables, and textual descriptions; improvement factors and error statistics are verified against primary simulation outputs to ensure reproducibility. The complete simulation framework is made publicly available to facilitate reproducible research in RIS-aided positioning systems. Full article

Reconfigurable intelligent surface (RIS)-aided index modulation (IM) shows great potential for next-generation wireless communications. Nevertheless, obtaining channel state information (CSI) for RIS-based IM incurs high pilot overhead, particularly for multi-domain IM. In this paper, we integrate orthogonal frequency division multiplexing into RIS-aided differential reflecting modulation (DRM) communications, introducing the differential reflecting frequency modulation (DRFM) system. In DRFM, information bits are jointly conveyed through the activation permutations of reflecting patterns, grouped carriers, and constellation symbols. The transmitter combines the differentially coded reflecting-time block and the time–frequency block using the Kronecker product. This allows DRFM to operate without relying on CSI at the transmitter, RIS, or receiver. Moreover, we design a novel high-rate quadrature amplitude modulation (QAM) scheme for DRFM. Compared to PSK-based DRFM, this QAM scheme can boost either the throughput or the performance of DRFM. Simulation results illustrate the superiority of the DRFM system, along with an acceptable SNR penalty, compared to non-differential modulation with coherent detection. At the same spectral efficiency, the proposed QAM-aided DRFM outperforms schemes using traditional PSK, amplitude phase shift keying (APSK), and star-QAM constellation modulations. Full article

This work presents the fabrication and characterization of a bow-tie antenna integrated uni-traveling carrier photodiode (UTC-PD) on a silicon carbide (SiC) substrate for efficient terahertz (THz) wave generation. The proposed device exploits the superior thermal conductivity and mechanical robustness of SiC to overcome the self-heating limitations associated with conventional indium phosphide (InP)-based photodiodes. An epitaxial layer transfer technique was utilized to bond InP/InGaAs UTC-PD structures onto SiC. The study systematically examines the influence of critical geometric parameters, specifically the mesa diameter and length between the antenna arms, on the emitted THz intensity in the 300 GHz frequency band. Experimental results show that the THz radiation efficiency is primarily governed by the mesa diameter, reflecting the trade-off between light absorption, device capacitance, and bandwidth, while the length between the antenna arms exhibits only a weak influence within the investigated parameter range. The fabricated device demonstrates strong linearity between photocurrent and THz output power up to 7.5 mA, after which saturation occurs due to space-charge effects. This work provides crucial insights for optimizing SiC-based bow-tie antenna integrated UTC-PD devices to realize robust, high-power THz sources vital for future high-data-rate wireless communication systems such as beyond 5G and 6G networks. Full article

This paper studies long-term resource allocation for rate-splitting multiple access (RSMA) in multi-carrier downlink systems. RSMA provides a flexible interference-management mechanism that bridges spatial division multiple access (SDMA) and non-orthogonal multiple access (NOMA), but guaranteeing long-term quality-of-service (QoS) performance under dynamic fading channels remains challenging. To address this limitation, we develop an opportunistic scheduling framework based on Lagrangian duality and stochastic optimization, which maximizes the long-term weighted sum rate (WSR) while satisfying per-user time-average QoS constraints. The proposed method decomposes the long-term problem into per-slot subproblems with adaptive effective weights, and each subproblem is efficiently solved through a two-stage procedure consisting of subcarrier–user pair matching and power allocation. Simulation results show that the proposed RSMA scheduling framework significantly outperforms conventional NOMA while ensuring the QoS requirements of all users. These results demonstrate the practical applicability of RSMA for next-generation wireless networks requiring both high spectral efficiency and long-term reliability. Full article

Receiver-initiated MAC protocols, such as the IEEE 802.15.4e RIT scheme, are promising for energy-efficient communication in multi-hop wireless sensor networks. However, their practical use requires a better understanding of how multiple contention-avoidance mechanisms interact under realistic network conditions. This study develops an ns-3 implementation of an RIT-compliant receiver-initiated MAC protocol together with a flexible evaluation framework that enables selective activation of representative enhancement strategies, including carrier-sensing options for data and beacon transmissions and randomization of beacon intervals. Four realistic network scenarios were designed to simulate practical deployment settings. Simulation results revealed that the effectiveness of these enhancement strategies varied significantly depending on network load and topology. In particular, beacon interval randomization, although often assumed to improve robustness, was found to degrade performance under low-load conditions, indicating that even widely adopted mechanisms may behave differently depending on operational environments. Conversely, CSMA-based approaches provided consistent improvements in transmission reliability. These observations highlight the importance of considering environmental factors and parameter configurations when enabling enhancement mechanisms. Overall, the proposed platform provides a reproducible and unified environment for fair comparison of receiver-initiated MAC protocols and their optional mechanisms, offering practical insights for selecting appropriate configurations in real sensor network deployments. Full article

In this work, a dual-band, dual-mode, circularly polarized fully woven textile antenna with capability for Simultaneous Wireless Information and Power Transfer (SWIPT) in wearable applications is presented. The power and the data transfer modes work at 2.4 and 5.4 GHz, respectively. The radiating element is based on a square patch with an asymmetrical U-shaped slot and a chamfered corner. A single-diode rectifier, required for the power transfer mode, is mounted on a carrier thread and then connected to the antenna through a T-match network located at one of the patch corners. This feeding technique simultaneously provides complex conjugate matching to the rectifier and circular polarization. On the other hand, a coaxial probe port is used for the data transfer mode. A prototype was implemented and experimentally characterized. Regarding the power transfer mode, the measured RF-DC conversion efficiency is about 50% when the available power at the rectifier input is −10 dBm, and the axial ratio is smaller than 3 dB. In the data transfer mode, the antenna gain and the axial ratio are 0 and 2 dB, respectively. The experimental results are in good agreement with simulations, validating the proposed structure and design methods, and they are comparable to the state of the art for textile antennas/rectennas. Furthermore, the combination of the fully woven technology and the proposed single-layer layout provides a large degree of integration and robustness, which are valuable characteristics for wearable devices. Full article

This paper presents an open, modular sensor platform based on wireless energy and data transmission. The platform is powered by the carrier signal of a transceiver and transmits the measured sensor data using backscatter modulation. Through the use of modular ready-to-buy components, the sensor platform can be flexibly adapted to different applications and is therefore suitable for both building automation systems and industrial automation tasks. Energy storage, power management, and modulation are designed so that the overall energy demand of the platform is mainly determined by the sensor in use. The performance of the system was verified with a demonstrator measuring underfloor temperature and humidity. The demonstrator operates at a carrier frequency of 868 MHz, an output power of $27 \mathrm{dBm}$ EIRP at the transceiver antenna, and an antenna gain of 0 dBi at the receiver antenna. A transmission range of more than 3 m has been achieved. The platform provides an input sensitivity of $-15 \mathrm{dBm}$. Its open design enables a straightforward scaling from prototype to small- and medium-volume production. Full article

Wireless communications in industrial environments are challenged by severe multipath propagation, which causes significant signal distortion. Conventional mitigation techniques, such as complex equalizers, are unsuitable as they contradict the stringent low-power and low-complexity requirements of Reduced Capability (RedCap) devices. This paper introduces a novel method for optimizing single-carrier pulse shapes under a distortion constraint to combat multipath propagation. The performance was evaluated through simulations in MATLAB 2023b using a ray-traced warehouse model. The results show that the proposed optimal pulses achieve a significant reduction in Error Vector Magnitude (EVM) (up to 40% in non-line-of-sight scenarios) compared to conventional root-raised cosine (RRC) pulses, while adhering to the 20 MHz RedCap bandwidth requirement. Furthermore, this performance is attainable with a low-complexity scaling equalizer. EVM degradation under Doppler shift is estimated and the pilot period required to maintain the target distortion level is specified. The resulting bit rate of approximately 2.9 Mbps supports industrial sensor networks and low-definition video streaming, confirming the approach’s suitability for resource-constrained industrial applications. Full article

This research paper presents a smart IoT-based COVID-19 vaccine supply chain, monitoring, and control system. This proposed system is designed to efficiently and effectively monitor COVID-19 vaccine storage sites by tracking their temperature, humidity, quantity, and location on a map across various supply chain categories. It ultimately aims to monitor and control temperatures outside the range at the tracked location. The approach utilized temperature, humidity, and ultrasonic sensors, a GPS module, a Wi-Fi module, and an Arduino Uno microcontroller. The system was designed and implemented using Arduino and Proteus integrated design environments (IDEs) and coded using the embedded C/C++ programming language. A real-life working system prototype was designed and implemented. The measured sensor readings can be viewed via a computer system capability or any mobile device, such as an Android phone, iPhone, iPad, or laptop, with the aid of a cloud-based platform, namely, Thingspeak.com. The experimentally measured sensor readings are stored in a data log file for subsequent download and analysis whenever the need arises. The data aggregation and analytics are coded using MATLAB and viewed as charts, and the location map of vaccine carrier coordinates is sent to the web cloud for tracking. An alarm message is sent to the monitoring and control system if an unfavorable vaccine environment exists in either the store or the carrier container. A suitable sensor-based interface architecture and web portal are provided, allowing health practitioners to remotely monitor the vaccine supply chain system. This method encourages health workers by reducing the high levels of supervision required by vaccine supervisors to ensure the smooth supply of vaccines to vaccine collection centers, by using a wireless sensor network and IoT technology. Experimental results from the implemented system prototype demonstrated the benefits of the proposed approach and its possible real-life health monitoring applications. Full article