S. Rana, S. Pramanik, D. Mitra, C. Koley [references] [full-text] [DOI: 10.13164/re.2025.0575] [Download Citations]
Design and Analysis of Multifunctional Metasurface for Linear and Circular Polarized Incident Wave

A passive multifunctional metasurface design has been proposed in this work for both linear and circular polarized incidences, between a frequency range of 4-7 GHz. The proposed unit cell structure comprises of concentric split pentagonal rings, loaded with two lumped capacitors on the top layer, having single dielectric layer. The main functionalities include polarization selective absorption (4.31-4.36 GHz) and reflective cross-polarization conversion (5.79-6.02 GHz) for linear polarized incidences. Moreover, polarization handedness maintaining reflection (4.57-5.45 GHz) and polarization selective absorption (6.12-6.26 GHz) for circular polarized incidences has been achieved. A sample prototype of 10 X 10-unit cells (2lambda_0 X 2lambda_0), was fabricated and the experimental results were verified with the simulated ones. Since the proposed design has such diversified functionalities for both linear and circular polarized incidences, it can find probable applications in polarimetric imaging techniques, polarization modulation devices, polarization sensors etc.

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Keywords: Lumped capacitor, multifunctional metasurface, polarization converter, polarization selective absorber

L. Leitold, M. Alrwashdeh, Z. Kollar [references] [full-text] [DOI: 10.13164/re.2025.0583] [Download Citations]
High-Performance Multi-Precision Tool for Floating-Point Computations

This paper presents a MATLAB toolbox for multiple-precision arithmetic, enabling high-precision numerical computations beyond the standard double-precision format. The development step and functionality of the toolbox are described, and how it integrates seamlessly with the MATLAB computational ecosystem, offering a user-friendly interface. The performance enhancement and usability of the toolbox are demonstrated through four use cases where floating-point arithmetic becomes an issue. These benchmark results illustrate the toolbox's computational accuracy and performance, highlighting its ability to mitigate numerical instabilities and roundoff errors in sensitive computations. The toolbox empowers researchers and engineers to implement more reliable models, test advanced algorithms, and validate system designs and a diverse set of operations for applications that require enhanced precision, such as numerical analysis, scientific computing, and applied mathematics.

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Keywords: MATLAB, floating-point, GMP, MPFR, multiple-precision, quantization, QNP

R. P. K. Emani, P. Telagathoti, P. Nizampatanam [references] [full-text] [DOI: 10.13164/re.2025.0591] [Download Citations]
Fusion Based Method for Wide Band Speech Reconstruction Over Legacy Telephone Networks

Public Switched Telephone Networks (PSTNs) are limited to Restricted Band (RB) speech in the 0-4 kHz range, which reduces speech quality compared to Wideband (WB) speech (0-8 kHz). This study proposes a transform-based hybrid steganography technique combining Curvelet Transform (CT) and Fast Fourier Transform (FFT) to enhance RB speech quality while maintaining full PSTNs compatibility. The Curvelet Transform, capable of representing directional and edge-like features across multiple scales and angles, allows efficient capture of speech components such as formant transitions and unvoiced consonants, which are critical for improving quality and intelligibility. In the proposed approach, WB speech is decomposed into RB and Extended Band (4-8 kHz) components. Detailed coefficients of the RB are extracted using CT, and spread parameters of the Extended Band are embedded within the RB signal. Inverse CT and FFT are performed to form a Composite Restricted Band (CRB) signal for transmission. At the receiver, the embedded parameters are recovered to reconstruct the Extended Band, which is merged with the CRB signal to yield a high-quality Reconstructed Wideband (RWB) signal. Tests with participants aged 60-75 years demonstrated superior performance over conventional methods, with strong robustness to channel and quantization noise.

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Keywords: Curvelet transform, fast Fourier transform, hybrid steganography, speech quality, public switched telephone networks, linear predictive coding

T. I. Unger, M. Kuczmann [references] [full-text] [DOI: 10.13164/re.2025.0603] [Download Citations]
The Impact of Terrain Sampling Density on 5G NR-V2X Downlink Channel Modeling Using Various Propagation Models at the 3.6 GHz Band

This study investigates the sensitivity of radio wave propagation models to terrain sampling density in a 5G New Radio Vehicle-to-Everything downlink scenario at 3.6 GHz. Four widely used models are analysed: the empirical ITU-R P.1546-6, the deterministic Parabolic Equation Method, and the hybrid ITU-R P.1812-6 and ITU-R P.452-16. Real terrain profiles from Hungary are considered at multiple resolutions, allowing a systematic assessment of how accuracy degrades as the representation of terrain becomes oarser. The analysis reveals a consistent ranking across nvironments: the empirical model is the least affected by esolution changes, while deterministic and hybrid methods re significantly more sensitive. To interpret these differences, the study introduces a spectral complexity measure of errain profiles and establishes its strong relationship with error growth through regression analysis. This provides a novel ramework for explaining and quantifying the impact of terrain detail on model behaviour. The findings highlight both he methodological contribution of linking spectral complexity to propagation accuracy and the practical implications or optimising the trade-off between computational efficiency nd prediction reliability in vehicular network planning.

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Keywords: Outdoor wave propagation models, terrain sensitivity, radio frequency electromagnetic waves, path loss prediction, channel modeling, vehicle-to-everything communications

X. Yao, Z. Xu, F. Qiang [references] [full-text] [DOI: 10.13164/re.2025.0624] [Download Citations]
High-Precision Indoor Localization via Dual-Modal AOA/TOA Fusion with Deep Learning and Particle Filters

As the era of IoT and artificial intelligence advances, the demand for high-precision indoor positioning systems continues to grow. Achieving accurate positioning in indoor environments remains challenging due to the presence of obstacles and signal interference, especially in Non-Line-of-Sight (NLOS) conditions. To address these challenges, this paper proposes a novel indoor positioning algorithm based on the fusion of Angle of Arrival (AOA) and Time of Arrival (TOA) data. A hybrid model combining Asymptotic Gradient Boosted Regression Trees (GBRT) and Elastic Net (EN) is used to reduce AOA measurement errors in NLOS environments, followed by the application of the Levenberg-Marquardt (LM) optimization algorithm to enhance localization accuracy. Experimental results show a significant reduction in positioning error, with an average error of 0.47 meters, representing a 41.25% improvement compared to the KF+WLS algorithm. Meanwhile, to improve TOA positioning, a deep learning-based TOA fingerprinting algorithm is proposed, this algorithm captures complex spatiotemporal features in TOA data, leading to a 25.00% and 15.22% reduction in root mean square error (RMSE) compared to the WKNN and WLS algorithms, respectively. Finally, a fusion strategy based on Particle Filtering (PF) is introduced to combine AOA and TOA data, achieving further RMSE reductions of 35.42% and 20.51%, compared to individual AOA and TOA methods.

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Keywords: Indoor localization, angle of arrival, time of arrival.machine learning, particle filter

X. Dai, J. Zhao, Z. Shen, H. Hong, G. Li [references] [full-text] [DOI: 10.13164/re.2025.0641] [Download Citations]
A Broadband Low-Profile Dual-Polarized Antenna Based on a Metasurface

This article presents a wideband low-profile dual-polarization antenna based on a metasurface (MS). The antenna consists of a 4×4 metasurface array made up of 16 circular metal patches, a radiating patch, and a metallic ground plane. The metasurface excites the surface waves of the radiating patch to generate multiple resonant points, thereby broadening the antenna bandwidth. In addition, two rectangular cross-slot structures at the center of the patch enhance port isolation. Finally, a prototype with dimensions of 46 mm × 46 mm × 3.2 mm (1.28λ₀ × 1.28λ₀ × 0.88λ₀) was fabricated. Measurement results show that the antenna achieves a return loss better than -10 dB and an isolation better than -16 dB within the operating bandwidth of 6.38–10.3 GHz. It can be concluded that the experimental results of the antenna are in good agreement with the simulation results.

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23. AFSHANI, A., WU, K. Dual-polarized patch antenna excited concurrently by a dual-mode substrate integrated waveguide. IEEE Transactions on Antennas and Propagation, 2022, vol. 70, no. 3, p. 2322–2327. DOI: 10.1109/TAP.2021.3118816
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Keywords: Dual-polarization, metasurface, low-profile, broadband

J. Zhang, K. Wang, J. Wang, H. Wei, J. Chang, J. Yao, L. Zhang [references] [full-text] [DOI: 10.13164/re.2025.0648] [Download Citations]
Hybrid Small-Signal Modeling of GaN HEMT Enhanced by the Integration of SVD and RIME Optimization

For the 20-element small-signal model of GaN HEMT, a combination of the singular value decomposition (SVD) algorithm and the frost ice optimization algorithm is proposed in this paper to extract and optimize the intrinsic parameters of the small-signal model. When the traditional algorithm is employed for parameter extraction, issues of low extraction accuracy and efficiency are encountered. By introducing an optimization algorithm for parameter extraction, the accuracy and efficiency of the process are enhanced. However, previous studies have focused on improving the optimization algorithm to optimize the eigenparameters of GaN HEMT without taking into account the correlation among the parameters within the model. In this study, the SVD algorithm is utilized to process the real and imaginary parts of the intrinsic model Y-parameters, thereby strengthening the correlation between the intrinsic parameters. Subsequently, the new intrinsic model Y-parameters and the RIME algorithm are employed to extract the intrinsic parameters. The experimental results demonstrate that the combination of the SVD algorithm and the frost ice optimization algorithm breaks the isolation between the eigenparameters, improves the parameter correlation, and can accurately extract and optimize the eigenparameters of the small-signal model within the frequency range of 0.5 - 20.5 GHz.

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Keywords: GaN HEMT, small-signal model, hybrid approach, Singular Value Decomposition (SVD) algorithm, Rime Optimization algorithm

J. Wang, Y. Liu, C. Li, Z. Wang, Y. Li [references] [full-text] [DOI: 10.13164/re.2025.0660] [Download Citations]
A Two-Stage Optimization Framework for Radar Jamming Effectiveness Evaluation

In complex electromagnetic environments, radar signals intercepted by jammers often contain biased data due to factors such as radar mode switching, electromagnetic interference, and receiver noise. To address this challenge, this paper proposes a two-stage optimization framework for jamming effect evaluation from the jammer’s perspective. In the first stage, a pre-evaluation is conducted using an entropy-optimized K-means discretization algorithm (KDEOA) to adaptively partition pulse descriptor word (PDW) parameters, enhancing robustness against noise. A GCSAO-LSSVM model is then employed to improve classification accuracy through optimal parameter tuning and a periodic oscillation mutation strategy. In the second stage, an improved entropy weight method (IEWM) integrating Tsallis entropy, kernel density standardization, and game theory is used for objective weighting, followed by an enhanced TOPSIS method (ITOPSIS) incorporating interquartile range standardiza-tion and dynamic ideal solution fusion for quantitative scoring. Experimental results demonstrate that the pro-posed framework achieves the highest pre-evaluation accuracy across all noise levels (up to 50% contamination), with IEWM exhibiting the lowest weight variation rate (0.11–0.23%) and ITOPSIS showing the strongest correlation (0.7290) with baseline scores under high noise. The main limitations include sensitivity to severe signal distortion and assumption of stable radar behavior. This approach enables accurate, non-cooperative jamming assessment and supports robust decision-making in cognitive electronic warfare.

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Keywords: Non-cooperative dynamic adversarial, jamming effect evaluation, improved entropy weight method (IEWM), improved technique for order preference by similarity to ideal solution (ITOPSIS), biased data, K-means discretization based on entropy optimization algorithm (KDEOA)

D. Logeshwari, S. Asha, T. C. Jermin Jeaunita, M. Povaneswari [references] [full-text] [DOI: 10.13164/re.2025.0674] [Download Citations]
Proactive Channel Assignment and Modified CR-AODV for Stability-Driven Multi-hop Routing in Cognitive Radio Networks

Cognitive Radio Networks (CRNs) allow efficient spectrum usage by allowing Secondary Users (SUs) to exploit underused frequency bands allocated to a Primary User (PU). Current channel assignment techniques only document real-time channel availability without knowledge of future activity or channel availability warnings. This work proposes a proactive channel allocation framework for SU to predict long-term stability based upon route reliability. The framework simulates the activities of PU by using the logistic map to model non-linear, time-varying PU behavior. The bifurcation theory is used to determine the threshold point at which channel behavior begins to become chaotic. Then, a modified Cognitive Radio Ad hoc On-Demand Distance Vector (AODV) routing protocol is incorporated that allows possible links in route discovery to be restricted to stable channels. Our simulation results show that the framework improves channel allocation and routing efficiency, ensuring energy-efficient and reliable communication in dynamic CRN environments.

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32. Source code link: https://github.com/lw9318457/project32319.git

Keywords: Cognitive Radio Networks (CRN), channel assignment, chaos theory, bifurcation theory, logistic map, primary user behavior, spectrum prediction.

A.-T. Pham, S.-Q. Nguyen, P.-N. Le , H.-T. Le, M.-T. Dang, T.-M. Hoang [references] [full-text] [DOI: 10.13164/re.2025.0688] [Download Citations]
Average BLER Analysis of Ambient Backscatter RSMA Systems for URLLC Short-Packet Communications

Rate-splitting multiple access (RSMA) has emerged as a promising approach for ultra-reliable and low-latency communications (URLLC), addressing stringent delay and reliability requirements in next-generation networks. This study investigates downlink RSMA for URLLC short-packet communication (SPC) by analyzing the average block error rate (BLER) in an RSMA-enabled symbiotic backscatter system. A base station serving two users via RSMA is considered, while a backscatter device passively assists the transmission, improving overall efficiency. Closed-form expressions are derived for approximate BLERs and the overall system throughput, and validated through Monte Carlo simulations. Results indicate that RSMA achieves about one order-of-magnitude lower BLER than NOMA at rho_S = 30 dB and approximately 15-20% higher throughput in the considered short-packet regime. The impact of power allocation and blocklength on reliability is also investigated, providing design insights for URLLC optimization. These findings demonstrate that RSMA offers improved reliability and fairness under envisioned URLLC short-packet scenarios, while the inclusion of passive backscatter enhances energy efficiency without additional transmit power.

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Keywords: 6G, power allocation, rate-splitting multiple access (RSMA), short-packet communication (SPC), symbiotic backscatter radio

J. Lukac, M. Kimmer, J. Sykora [references] [full-text] [DOI: 10.13164/re.2025.0698] [Download Citations]
Matched-Filter Based Frame-Start Detector Resilient to Frequency Offset

The article proposes a (phase-marginalized) frame-start detector resilient to frequency offset between the transmitter and the receiver. The detector is a slight modification of the standard detector that looks for a known sequence/preamble using the matched filter, respectively correlation of the received signal with the known sequence. The modification is that the original long sequence is divided into shorter ones; the magnitude or magnitude-squared of the output of matched-filters is taken and then appropriately added to get the final detector metric. The proposed detector is a low-cost alternative to the standard approach (joint estimation of frame timing and frequency offset), where we need as many matched-filters as the number of testing frequency offsets. We derive probability characteristics of the proposed detector that reflect its resilience to the frequency offset. The frequency resilience of the detector is proportional to the number of segments into which the preamble is divided.

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Keywords: Frame synchronization, matched filtering, crosscorrelation, frequency offset