Search Results (1,261)

In complex urban wireless environments, unmanned aerial vehicle–mobile edge computing (UAV-MEC) systems face challenges like link blockage and single-antenna eavesdropping threats. The traditional single reconfigurable intelligent surface (RIS), limited in collaboration, struggles to address these issues. This paper proposes a double-RIS cooperative UAV-MEC optimization scheme, leveraging their joint reflection to build multi-dimensional signal paths, boosting legitimate link gains while suppressing eavesdropping channels. It considers double-RIS phase shifts, ground user (GU) transmission power, UAV trajectories, resource allocation, and receiving beamforming, aiming to maximize secure energy efficiency (EE) while ensuring long-term stability of GU and UAV task queues. Given random task arrivals and high-dimensional variable coupling, a dynamic model integrating queue stability and secure transmission constraints is built using Lyapunov optimization, transforming long-term stochastic optimization into slot-by-slot deterministic decisions via the drift-plus-penalty method. To handle high-dimensional continuous spaces, an end-to-end proximal policy optimization (PPO) framework is designed for online learning of multi-dimensional resource allocation and direct acquisition of joint optimization strategies. Simulation results show that compared with benchmark schemes (e.g., single RIS, non-cooperative double RIS) and reinforcement learning algorithms (e.g., advantage actor–critic (A2C), deep deterministic policy gradient (DDPG), deep Q-network (DQN)), the proposed scheme achieves significant improvements in secure EE and queue stability, with faster convergence and better optimization effects, fully verifying its superiority and robustness in complex scenarios. Full article

The pre-courtship behavior of Proholopterus chilensis on Nothofagus obliqua trees was recorded for the first time, documenting a putative female “calling” behavior and the consequent male “oriented search,” enabling the description of behavioral units, sequences, frequencies, and degrees of stereotypy. Post-resting activity in both sexes began with walking and grooming during the first hour of the scotophase, following a period of daytime inactivity. Subsequently, females extended their ovipositor both horizontally and vertically, alternating between contact with the tree substrate and, simultaneously, walking the surface (=putative calling behavior), while males became active, extending their antennae perpendicularly to the longitudinal body axis. In response to the putative call, males exhibited oriented flight and hasty walking that followed the trajectory and direction previously taken by females on the substrate, ultimately leading to their location. Statistical analysis of behavioral sequences and the stereotypy index indicated that both behaviors were non-random and partially stereotyped. These findings are consistent with previous chemical analyses of female aerations and terminalia performed by our research group, which identified semiochemicals likely functioning as long-range sex pheromones guiding males to the vicinity of the female’s tree, as well as potential trail pheromones facilitating close-range localization. This dual signaling system seems necessary to the high mobility displayed by females during calling behavior, characterized by frequent and extended bidirectional vertical walks along the trunk, which may enhance signal dispersal and/or reduce predation risk. If confirmed, this would represent a novel sexual encounter mechanism within Cerambycidae. Full article

This paper presents a novel design strategy for outlier-robust, three-element non-uniform linear array (NULA) configurations optimized for multiple-input multiple-output (MIMO) radar systems aimed at target direction of arrival (DoA) estimation. The occurrence of outliers, i.e., ambiguous estimates, is a well-known issue in DoA estimation based on the maximum likelihood (ML), which is caused by the local maxima of the likelihood function. Specifically, we study how the positioning of both transmitters and receivers affects both presence of outliers and accuracy of ML DoA estimation. By leveraging a theoretical prediction of the DoA mean squared error (MSE), we propose a design strategy to jointly optimize the positions of NULA array of three transmitting and receiving elements, only inside a subspace which guarantees that the outlier probability remains below a specified threshold. Compared to NULA configurations with a single transmitter, the proposed designs achieve superior estimation accuracy due to two key factors: improved asymptotic performance resulting from a narrower mainlobe, and enhanced robustness against outliers due to reduced sidelobes. Furthermore, the proposed approach is well-suited for practical implementation in low-cost radars using only 3 × 3 or 2 × 3 MIMO configurations, as it also incorporates practical design constraints such as minimum inter-element spacing to account for the physical dimensions of the antennas, and tolerance in the installation accuracy. Full article

This paper presents a Ka-band cylindrical conformal transceiver active phased array (CCTAPA) with a full-azimuth scanning gain fluctuation of 0.8 dB and low power consumption. The array comprises 20 panels of 4 × 4 antenna elements, RF beam-control circuits, a Wilkinson power divider network, and frequency converters. The proposed three-subarray architecture enables ±9° beam scanning with minimal gain degradation. By dynamically switching subarrays and transceiver channels across azimuthal directions, the array achieves full 360° coverage with low gain fluctuation and power consumption. Fabrication and testing demonstrate a gain fluctuation of 0.8 dB, equivalent isotropically radiated power (EIRP) between 50.6 and 51.3 dBm, and a gain-to-noise-temperature ratio (G/T) ranging from −8 dB/K to −8.5 dB/K at 28.5 GHz. The RF power consumption remains below 8.73 W during full-azimuth scanning. This design is particularly suitable for airborne platforms requiring full-azimuth coverage with stringent power budgets. Full article

This study presents a convex optimization framework for beam synthesis in Square Kilometre Array low-frequency radio telescope stations configured in a sunflower-like layout. The method minimizes the peak sidelobe level by computing an optimized set of beamforming weights, enabling precise control of the main beam while preserving angular resolution. The framework is validated through full-wave electromagnetic simulations based on detailed physical models of the antenna elements and station geometry. Compared to conventional beamforming employing constant unitary real weights, the optimized solutions yield a significant reduction in sidelobe levels, with only a minimal impact on directivity. These benefits are particularly evident at frequencies where mutual coupling between array elements is strong, confirming the suitability of the proposed approach for dense radio astronomy arrays. Full article

This work presents an 80 Gbps photonics-aided millimeter-wave (mm Wave) wireless communication system employing 16-Quadrature Amplitude Modulation (16-QAM) and a 1 × 2 single-input multiple-output (SIMO) architecture with maximum ratio combining (MRC) to achieve robust 87.5 GHz transmission over 4.6 km. By utilizing polarization-diverse optical heterodyne generation and spatial diversity reception, the system enhances spectral efficiency while addressing the low signal-to-noise ratio (SNR) and channel distortions inherent in long-haul links. A blind equalization scheme combining the constant modulus algorithm (CMA) and decision-directed least mean squares (DD-LMS) filtering enables rapid convergence and suppresses residual inter-symbol interference, effectively mitigating polarization drift and phase noise. The experimental results demonstrate an SNR gain of approximately 3 dB and a significant bit error rate (BER) reduction with MRC compared to single-antenna reception, along with improved SNR performance in multi-antenna configurations. The synergy of photonic mm Wave generation, adaptive spatial diversity, and pilot-free digital signal processing (DSP) establishes a robust framework for high-capacity wireless fronthaul, overcoming atmospheric attenuation and dynamic impairments. This approach highlights the viability of 16-QAM in next-generation ultra-high-speed networks (6G/7G), balancing high data rates with resilient performance under channel degradation. Full article

Measuring ocean currents is essential for oceanographic studies, and dual-beam squint airborne SAR measurements provide significant advantages, including flexibility, cost-effectiveness, and extensive coverage. However, substantial attitude changes in the airborne platform introduce challenges to achieving accurate ocean current measurements. Additionally, existing attitude correction methods fail to account for the off-nadir angle and squint angle errors of targets located at the edge of the beam’s ground footprint, further impacting measurement precision. To address these limitations, this paper proposes a dual-beam squint airborne velocity Doppler transfer model. The squint antenna view vector is initially defined in the aircraft-centered frame of reference and subsequently described using the flightpath frame of reference. By estimating the Doppler frequency caused by aircraft attitude changes, the velocity Doppler transfer model is established. This model is then applied to invert sea surface currents. An error analysis is conducted, and the Monte Carlo method is employed to validate the model’s accuracy. The results demonstrate that the proposed velocity Doppler transfer model effectively inverts sea surface currents with high accuracy in both velocity and direction. Compared to pre-existing methods, the proposed model shows superior performance, particularly in addressing off-nadir and squint angle errors, thereby enhancing overall measurement precision. Full article

This study presents a compact and high-efficiency microstrip antenna integrated with a square electromagnetic band-gap (EBG) structure for radio frequency energy harvesting to power battery-less Internet of Things (IoT) sensors and medical devices in the 5.8 GHz Industrial, Scientific, and Medical (ISM) band. The proposed antenna features a compact design with reduced physical dimensions of 36 × 40 mm² (0.69λ_o × 0.76λ_o) while providing high-performance parameters such as a reflection coefficient of −27.9 dB, a voltage standing wave ratio (VSWR) of 1.08, a gain of 7.91 dBi, directivity of 8.1 dBi, a bandwidth of 188 MHz, and radiation efficiency of 95.5%. Incorporating EBG cells suppresses surface waves, enhances gain, and optimizes impedance matching through 50 Ω inset feeding. The simulated and measured results of the designed antenna show a high correlation. This study demonstrates a robust and promising solution for high-performance wireless systems requiring a compact size and energy-efficient operation. Full article

Traditional algorithms such as Dijkstra and APF rely on complete environmental information for path planning, which results in numerous constraints during modeling. This not only increases the complexity of the algorithms but also reduces the efficiency and reliability of the planning. Swarm intelligence algorithms possess strong data processing and search capabilities, enabling them to efficiently solve path planning problems in different environments and generate approximately optimal paths. However, swarm intelligence algorithms suffer from issues like premature convergence and a tendency to fall into local optima during the search process. Thus, an improved Artificial Bee Colony-Beetle Antennae Search (IABCBAS) algorithm is proposed. Firstly, Tent chaos and non-uniform variation are introduced into the bee algorithm to enhance population diversity and spatial searchability. Secondly, the stochastic reverse learning mechanism and greedy strategy are incorporated into the beetle antennae search algorithm to improve direction-finding ability and the capacity to escape local optima, respectively. Finally, the weights of the two algorithms are adaptively adjusted to balance global search and local refinement. Results of experiments using nine benchmark functions and four comparative algorithms show that the improved algorithm exhibits superior path point search performance and high stability in both high- and low-dimensional environments, as well as in unimodal and multimodal environments. Ablation experiment results indicate that the optimization strategies introduced in the algorithm effectively improve convergence accuracy and speed during path planning. Results of the path planning experiments show that compared with the comparison algorithms, the average path planning distance of the improved algorithm is reduced by 23.83% in the 2D multi-obstacle environment, and the average planning time is shortened by 27.97% in the 3D surface environment. The improvement in path planning efficiency makes this algorithm of certain value in engineering applications. Full article

This paper proposes a compact, broadband, and low-profile filtering antenna designed for Sub-6 GHz communication. By applying characteristic mode analysis to the radiating elements, the operational mechanism of the antenna is clearly elucidated. The current cancellation among different radiating elements results in two radiation nulls in the primary radiation direction, effectively enhancing the filtering effect. The antenna achieves a wide operational bandwidth ($S_{11}\le -10$ dB) of 35.9% (4.3–6.4 GHz), making it highly suitable for Sub-6 GHz communication systems. Despite its compact size of 25 × 25 mm², the antenna consistently maintains stable broadside radiation patterns, with a peak gain of 6.14 dBi and a minimal gain fluctuation of less than 1 dBi at 4.6–6.45 GHz. This design ensures reliable and robust communication performance for V2V systems operating in the designated frequency band. Full article

Satellite communications are pivotal to global Internet access, connectivity, and the advancement of information warfare. Despite these importance, the open nature of satellite channels makes them vulnerable to eavesdropping, making the enhancement of interception resistance in satellite communications a critical issue in both academic and industrial circles. Within the realm of satellite communications, polarization modulation and quadrature techniques are essential for information transmission and interference suppression. To boost electromagnetic countermeasures in complex battlefield scenarios, this paper integrates multi-parameter weighted-type fractional Fourier transform (MP-WFRFT) with directional modulation (DM) algorithms, building upon polarization techniques. Initially, the operational mechanisms of the polarization-amplitude-phase modulation (PAPM), MP-WFRFT, and DM algorithms are elucidated. Secondly, it introduces a novel variable polarization-amplitude-phase modulation (VPAPM) scheme that integrates variable polarization with amplitude-phase modulation. Subsequently, leveraging the VPAPM modulation scheme, an exploration of the anti-interception capabilities of MP-WFRFT through parameter adjustment is presented. Rooted in an in-depth analysis of simulation data, the anti-scanning capabilities of MP-WFRFT are assessed in terms of scale vectors in the horizontal and vertical direction. Finally, exploiting the potential of the robust anti-scanning capabilities of MP-WFRFT and the directional property of antenna arrays in DM, the paper proposes a secure transmission technique employing directional variable polarization modulation with MP-WFRFT. The performance simulation analysis demonstrates that the integration of MP-WFRFT and DM significantly outperforms individual secure transmission methods, improving anti-interception performance by at least an order of magnitude at signal-to-noise ratios above 10 dB. Consequently, this approach exhibits considerable potential and engineering significance for its application within satellite communication systems. Full article

As accuracy of the reflector surface of a space parabolic deployable antenna is an important factor to determine its electrical characteristics (transmission gain and side lobes), mechanical characteristics of parabolic antennas under various internal pressures should be studied. The objective of this paper is to explore the force analysis of parabolic antennas by theoretical method and to estimate the effect of different air pressures on the surface precision of parabolic antennas via experiments in horizontal and vertical directions, and then a numerical analysis of the vibration characteristics of the parabolic antenna is proposed to explore the transient response of parabolic antennas. It is found that the ratio of tension reduces as depth of the parabolic membrane increases and can infinitely converge to 1/2. For precision analysis, it is concluded that precision of the parabolic membrane surface in a vertical state is higher than that in a horizontal state. Full article

The localization of multiple interference sources in Global Navigation Satellite Systems (GNSS) can be achieved using carrier-to-noise ratio (C/N₀) information provided by GNSS receivers, such as those embedded in smartphones. However, in increasingly prevalent complex scenarios—such as the coexistence of multiple directional interferences, increased diversity and density of GNSS interference, and the presence of multiple low-power interference sources—conventional localization methods often fail to provide reliable results, thereby limiting their applicability in real-world environments. This paper presents a multi-interference sources localization method using object detection in GNSS C/N₀ distribution maps. The proposed method first exploits the similarity between C/N₀ data reported by GNSS receivers and image grayscale values to construct C/N₀ distribution maps, thereby transforming the problem of multi-source GNSS interference localization into an object detection and localization task based on image processing techniques. Subsequently, an Oriented Squeeze-and-Excitation-based Faster Region-based Convolutional Neural Network (OSF-RCNN) framework is proposed to process the C/N₀ distribution maps. Building upon the Faster R-CNN framework, the proposed method integrates an Oriented RPN (Region Proposal Network) to regress the orientation angles of directional antennas, effectively addressing their rotational characteristics. Additionally, the Squeeze-and-Excitation (SE) mechanism and the Feature Pyramid Network (FPN) are integrated at key stages of the network to improve sensitivity to small targets, thereby enhancing detection and localization performance for low-power interference sources. The simulation results verify the effectiveness of the proposed method in accurately localizing multiple interference sources under the increasingly prevalent complex scenarios described above. Full article

Breast cancer detection through non-invasive and accurate techniques remains a critical challenge in medical diagnostics. This study introduces a deep learning-based framework that leverages a microwave radar system equipped with an arc-shaped array of six antennas to estimate key tumor parameters, including position, size, and depth. This research begins with the evolutionary design of an ultra-wideband octagram ring patch antenna optimized for enhanced tumor detection sensitivity in directional near-field coupling scenarios. The antenna is fabricated and experimentally evaluated, with its performance validated through S-parameter measurements, far-field radiation characterization, and efficiency analysis to ensure effective signal propagation and interaction with breast tissue. Specific Absorption Rate (SAR) distributions within breast tissues are comprehensively assessed, and power adjustment strategies are implemented to comply with electromagnetic exposure safety limits. The dataset for the deep learning model comprises simulated self and mutual S-parameters capturing tumor-induced variations over a broad frequency spectrum. A core innovation of this work is the development of the Attention-Based Feature Separation (ABFS) model, which dynamically identifies optimal frequency sub-bands and disentangles discriminative features tailored to each tumor parameter. A multi-branch neural network processes these features to achieve precise tumor localization and size estimation. Compared to conventional attention mechanisms, the proposed ABFS architecture demonstrates superior prediction accuracy and interpretability. The proposed approach achieves high estimation accuracy and computational efficiency in simulation studies, underscoring the promise of integrating deep learning with conformal microwave imaging for safe, effective, and non-invasive breast cancer detection. Full article

The swift advancement of fifth-generation (5G) wireless technology brings forth a range of enhancements to address the increasing demand for data, the proliferation of smart devices, and the growth of the Internet of Things (IoT). This highly interconnected communication environment necessitates using multiple-input multiple-output (MIMO) systems to achieve adequate channel capacity. In this article, a 2-port MIMO system using two flipped parallel 1 × 2 arrays and a 2-port MIMO system using two opposite 1 × 4 arrays designed and fabricated antennas for 5G wireless communication in the sub-6 GHz band, are presented, overcoming the limitations of previous designs in gain, radiation efficiency and MIMO performance. The designed and fabricated single-element antenna features a circular microstrip patch design based on ROGER 5880 (RT5880) substrate, which has a thickness of 1.57 mm, a permittivity of 2.2, and a tangential loss of 0.0009. The 2-port MIMO of two 1 × 2 arrays and the 2-port MIMO of two 1 × 4 arrays have overall dimensions of 132 × 66 × 1.57 mm³ and 140 × 132 × 1.57 mm³, respectively. The MIMO of two 1 × 2 arrays and MIMO of two 1 × 4 arrays encompass maximum gains of 8.3 dBi and 10.9 dBi, respectively, with maximum radiation efficiency reaching 95% and 97.46%. High MIMO performance outcomes are observed for both the MIMO of two 1 × 2 arrays and the MIMO of two 1 × 4 arrays, with the channel capacity loss (CCL) ˂ 0.4 bit/s/Hz and ˂0.3 bit/s/Hz, respectively, an envelope correlation coefficient (ECC) ˂ 0.006 and ˂0.003, respectively, directivity gain (DG) about 10 dB, and a total active reflection coefficient (TARC) under −10 dB, ensuring impedance matching and effective mutual coupling among neighboring parameters, which confirms their effectiveness for 5G applications. The three fabricated antennas were experimentally tested and implemented using the MIMO Application Framework version 19.5 for 5G systems, demonstrating operational effectiveness in 5G applications. Full article