Search Results (838)

This paper presents a novel design approach for mitigating the adverse effects of antenna mountings on the radiation pattern of GNSS antennas. By employing a resistive structure integrated into the ground plane, the proposed solution suppresses unwanted edge diffraction and near-field reflections caused by nearby mounting hardware. The design is developed using the concept of tapered resistive sheets and optimized using a customized cost function that accounts for pattern degradation across multiple realistic mounting configurations, ensuring robust performance under varying installation conditions. The resulting structure is fabricated using additive manufacturing (AM), enabling precise realization of complex resistive profiles with tailored surface impedance. Comprehensive validation through both electromagnetic simulations and experimental measurements demonstrates significant improvements in radiation pattern stability and reduced sensitivity to near-field objects, particularly in critical GNSS bands such as E5a/L5 and E1/L1. The results demonstrate that the proposed structure significantly enhances antenna reliability and calibration integrity in real-world deployments, offering a practical, hardware-based solution to a persistent challenge in high-precision GNSS systems. Full article

This paper presents a compact fractal-based super-wideband multiple-input multiple-output (MIMO) antenna for millimeter-wave (mmWave) 5G new radio (NR) and prospective 6G applications. The MIMO system comprises four Koch fractal monopole elements integrated with a modified shared ground plane. By adopting the second Koch iteration, the antenna achieves enhanced impedance bandwidth and stable radiation behavior compared with lower-order iterations. The elements are arranged in a polarization-diversity configuration within a 30 × 30 mm² footprint on a 0.8 mm-thick Rogers RO4835 substrate (ε_r = 3.5, δ = 0.0025). The proposed design provides an impedance bandwidth exceeding 14 GHz over 26.5–41 GHz, covering key bands at 28, 32, 38, and 40 GHz, while maintaining high inter-element isolation (around 30 dB over the operating range). The optimized ground modification enables a fully connected common ground and suppresses mutual coupling without additional decoupling structures. The antenna achieves 4–6 dBi realized gain with radiation efficiency exceeding 95%. MIMO performance metrics, including the envelope correlation coefficient (ECC), mean effective gain (MEG), and diversity gain (DG), confirm excellent diversity characteristics. The antenna is further evaluated under bending, demonstrating stable matching and isolation for conformal and wearable scenarios, and the concept is extendable to a non-planar 12-port configuration within the same footprint. Measured results agree well with simulations, validating the proposed design for wideband mmWave 5G/6G devices. Full article

Wireless links in underground coal mines suffer from severe attenuation, blockage, and limited spatial coverage. To improve link quality under these conditions, we study a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted system with multiple movable antennas (MAs) installed at the base station (BS) panel. Unlike prior models that assume a continuous movement box, we explicitly account for practical panel constraints: mechanical supports and RF feed lines partition the BS panel into non-overlapping irregular feasible subregions. This turns the BS-side antenna-positioning task into a mixed-integer nonlinear program (MINLP). We formulate a joint optimization problem that couples BS beamforming, STAR-RIS transmission/reflection coefficients, BS-side MA positions, and MA-to-subregion assignment with collision-avoidance constraints. To solve it, we adopt a block coordinate descent (BCD) framework: successive convex approximation (SCA) for beamforming, semidefinite relaxation (SDR)-based updates for STAR-RIS coefficients, and a penalty-based continuous relaxation for MINLP handling. The MA solver further integrates Hungarian initialization, cross-region jump updates, and reassignment corrections to escape poor local subregions. Simulation results in coal mine channel settings show that the proposed method yields a 66.7% sum-rate gain over fixed-antenna baselines and reduces required transmit power by 16.8 dB at the target-rate operating point. Compared with a regular-region BS-MA baseline, the irregular-partition design achieves an additional 5.6 dB power saving, demonstrating the practical value of hardware-aware geometry modeling. Full article

This paper presents a four-phase beam-steering antenna for 28 GHz wireless communication, targeting the demand for high-efficiency and low-complexity beam-steering solutions in millimeter-wave systems. The proposed design employs a Butler matrix network to achieve multi-directional beam switching while reducing implementation complexity. The antenna is realized using microstrip technology on a printed circuit board (PCB), and the overall architecture consists of a 1 × 4 microstrip antenna array and a 4 × 4 Butler matrix network. Each component is carefully designed and analyzed to ensure optimized performance and proper system balance. The proposed antenna exhibits excellent performance in terms of bandwidth and compact size, while also providing advantages that include low cost, ease of fabrication, and structural simplicity. The beam-steering capability is experimentally verified through far-field measurements. The measurement results indicate that the four beam directions are −38°, −13°, +19°, and +41°, with corresponding gains of 8.79, 9.66, 10.8, and 9.21 dBi, respectively. In addition, a good agreement between the measurement and simulation results is observed, which validates the effectiveness and feasibility of the proposed design. Full article

This paper proposes a two-dimensional orthogonal pattern division multiple access (OPDMA) technique to address key challenges in massive MIMO systems, including complex channel estimation, multipath interference, Doppler effects, and inter-antenna interference. Byleveraging optimal frequency hopping patterns with ideal autocorrelation and cross-correlation properties, constructed using a two-dimensional cyclic shift method, OPDMA eliminates the need for equalizers and channel estimation, thereby simplifying receiver design and mitigating pilot contamination. A method for constructing these patterns is introduced, based on an algebraic Costas array with a two-dimensional cyclic shift approach. The simulation results show that OPDMA significantly reduces the bit error rate (BER), simplifies system architecture, and enhances communication quality. These findings highlight OPDMA’s potential to improve performance and streamline the design of massive MIMO systems compared to traditional methods, which implies that OPDMA can be a promising low-complexity interference-suppression strategy when the optimal frequency hopping patterns design parameters match the expected Doppler shift and multipath delay. Full article

Ground-Penetrating Radar (GPR) serves as an essential non-destructive tool for subsurface exploration, and its antenna system largely determines the performance of the overall system. This paper presents a comprehensive review of advanced GPR antenna technologies, examining six major types: Vivaldi, bowtie, tapered, dipole, envelope, and spiral. This analysis shows that trade-offs among these antennas are unavoidable. High-frequency wideband antennas deliver high gain, but their penetration depth is limited to very shallow targets. Some wideband designs achieve wide bandwidth and reasonable gain with compact footprints, while others are suited for detecting embedded metallic objects. By comparison, low-frequency designs operating in the VHF and UHF bands enable very deep penetration, making them suitable for detecting deeply buried targets in lossy media and subsurface utilities. However, deep penetration often comes at the cost of lower gain or larger physical size. Ultimately, no universal antenna exists; the optimal choice depends on whether depth, resolution, or adaptability to attenuating environments is prioritized. Emerging metasurface-integrated and frequency-selective surface (FSS)-backed antennas represent a promising frontier, enabling better bandwidth, gain, and compactness. Ongoing challenges include miniaturization without compromising performance, reliable operation in heterogeneous and lossy soils, and the development of robust, manufacturable designs for field deployment. This review offers researchers and practitioners a structured reference, guiding the development of next-generation GPR systems that balance deeper penetration, higher resolution, and operational versatility. Full article

As essential radiating elements in RF and microwave microsystems, microstrip antennas require sufficient bandwidth to ensure stable operation, integration flexibility, and overall microsystem performance. From a microsystem optimization perspective, this paper proposes a bandwidth extension method for microstrip antennas that combines swarm intelligence and reinforcement learning. The proposed ICOA-TD3 framework is designed to enhance antenna bandwidth within target frequency bands and thus improve the performance robustness of compact RF microsystems. In the proposed method, an improved crayfish optimization algorithm (ICOA) is first used to explore the global design space and achieve global bandwidth enhancement, followed by the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm for local refinement and further exploitation of the antenna structure’s bandwidth potential. In Experiment 1, the impedance bandwidth ($S_{11}\le -10\mathrm{dB}$) is increased by up to 200%. In Experiment 2, the impedance bandwidth ($S_{11}\le -10\mathrm{dB}$) and axial-ratio (AR) bandwidth ($\mathrm{AR}\le 3\mathrm{dB}$) are improved by up to 27% and 250%, respectively. The results indicate that the proposed method is a feasible solution for bandwidth-oriented optimization of microstrip antennas and is promising for the intelligent design of high-performance RF microsystems. Full article

Conventional multi-electrode photoconductive antennas (PCAs) can only radiate linearly polarized terahertz waves with polarization angles in increments of 45°, limiting their use for the characterization of diverse anisotropic material. We propose a multi-electrode PCA with an asymmetric offset electrode structure, enabling linear polarization at 30° increments. Furthermore, the electrode design is optimized with a semicircular geometry to reduce electric field concentration at electrode edges, effectively suppressing electrical breakdown. Simulation results demonstrate that the applied bias voltage can be increased to 70 V, yielding a radiation power of 14.5 µW. The proposed design thus achieves dynamic polarization control without sacrificing output power. Full article

This paper presents the design of a batteryless near-field communication (NFC) multi-sensor node with an integrated adaptive power-management system for sensing applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power an ultra-low power sensing platform. The design consists of the TI RF430FRL152H, an integrated NFC transponder with an embedded MSP430 microcontroller core and ferroelectric random-access memory (FRAM) non-volatile memory. The system combines an ISO/IEC 15693 NFC front end, a tuned loop antenna for optimized power harvesting, and multiple analog and digital sensor interfaces, and a firmware architecture for intermittent harvested energy operation. The aforementioned design performs on-demand data acquisition, logs measurements in the FRAM, and communicates the measured results through an ISO15693 compliant NFC link while powered entirely by the reader’s radio-frequency (RF) field. Since NFC provides only limited harvested power, efficient energy management is critical. The proposed scheme continuously monitors the storage capacitor voltage and activates each sensor only when sufficient energy is available. After every measurement, the system reassesses the stored charge before triggering the next acquisition, ensuring stable multi-sensor operation. A BMP390 temperature and pressure sensor and the on-chip temperature sensor demonstrate the platform’s capability. Experimental results show that the system harvests 1.064 mW (1.85 V, 560 µA), achieves a wireless operating range of up to 40 mm, and delivers a response time of 800 ms, demonstrating its suitability for low-power temperature and pressure sensing applications. Full article

This paper proposes a novel Bidirectional Beetle-Informed RRT* (BBI-RRT*) Connect algorithm to enhance the safety and path planning efficiency of 6-DOF robotic manipulators operating in the complex high-altitude environment of angle-steel towers. By digitally reconstructing the tower environment through model registration, the algorithm establishes an accurate foundation for subsequent path planning. A bidirectional beetle antennae search mechanism is employed to guide node sampling, effectively accelerating the convergence rate of the algorithm. To ensure the generation of feasible path, a multi-constraint objective function is designed to balance path length, smoothness, and operability. Additionally, an Informed RRT* process is integrated to refine the path within an adaptive 3D ellipsoid, achieving global path optimization. Both simulation tests on the Unity platform and real-world experiments are conducted to validate the effectiveness and superiority of the proposed algorithm. Full article

The large-scale accumulation of coal gangue has created increasing environmental pressure, while its use as aggregate in cementitious materials remains limited by its high water absorption, porous structure and unstable mechanical performance. This study develops a machine learning-assisted multi-objective optimization framework for lightweight shotcrete incorporating surface-pretreated coal gangue aggregates and polyvinyl alcohol fibres. Two pretreatment methods—namely, silica-fume slurry coating (CGACM) and dry adsorption activation (CGACD)—were applied to improve the aggregate surface characteristics. Experimental data on compressive strength, splitting strength and density were used to train backpropagation neural networks and support vector machine and random forest models, with hyperparameters optimized by the Beetle Antennae Search algorithm. The trained models were then coupled with a multi-objective optimization procedure to balance mechanical performance, density, material cost and CO₂ emissions. The results show that surface pretreatment can improve the performance of coal gangue lightweight shotcrete, while the proposed optimization framework can identify mixture designs with balanced strength, reduced density and improved economic and environmental performance. Compared with untreated or non-optimized mixtures, the optimized surface-pretreated mixtures achieved a more favorable trade-off among mechanical, cost and carbon-emission objectives. This study provides a data-driven approach for the sustainable design and practical utilization of coal gangue in lightweight shotcrete. Full article

Recent advancements in computational hardware and parallel processing are driving developments in metaheuristic algorithms. These advancements help solve increasingly complex real-world optimization problems. As a result, more sophisticated and computationally demanding algorithms can now be implemented. This paper presents a comparative performance evaluation of ten modern metaheuristic algorithms for the optimal design of Electromagnetic Devices (EMDs). It also evaluates seven well-established metaheuristics, which are referred to as reference algorithms. In addition to the comparison, a novel hybrid optimization strategy called Multiple Combined Algorithms for Optimization (MuCAO) is proposed. MuCAO probabilistically combines the best-performing algorithms to leverage their complementary strengths. All algorithms, including MuCAO, were tested on six benchmark problems with various complexities and design variables. These benchmarks include analytical models and problems based on the Finite Element Method (FEM). For validation, the approach was also applied to a real-life application, which is Sidelobe Level Reduction in a Circular Antenna Array (CAA). The results show that MuCAO outperformed all other algorithms and achieved the highest overall ranking. Three modern metaheuristics followed. The best-performing reference algorithm ranked lower, with DE in fifth place. The study confirms that modern metaheuristics generally offer superior performance for EMD design and optimization compared to traditional metaheuristics. Full article

Partial discharge (PD) detection effectively identifies insulation defects in power equipment. Radio frequency (RF) methods for PD detection offer promising advantages due to their non-invasive measurement capability and ability to locate discharge sources. However, microstrip antennas used as RF sensors for PD detection suffer from narrow bandwidth and limited installation flexibility. To address these limitations, this paper presents a novel flexible microstrip antenna design. By incorporating a partial ground plane and oblique-cut meandering techniques and optimizing the structural parameters using an improved whale optimization algorithm (I-WOA), the operating bandwidth is expanded from 0.612–0.625 GHz to 0.346–2.0 GHz, while the overall size is reduced to 75.3% of its original dimensions. The antenna’s performance was validated through GTEM cell measurements and PD calibration pulse tests, confirming its suitability for RF detection of PD in power equipment such as transformers and cable joints. Notably, when the antenna was conformally wrapped around a cable joint, the response amplitude increased by 14%. This study contributes to the development of a low-cost, broadband, and flexibly installable RF sensor for partial discharge detection. Full article

In massive multiple-input multiple-output (MIMO) joint communication and sensing (JCAS) systems, hybrid beamforming (HBF) has attracted much attention because it can provide a favorable tradeoff between beamforming gain and hardware cost. However, HBF design in MIMO-JCAS systems is highly challenging. The main reasons are the strong coupling between the analog and digital precoders in joint communication-sensing optimization and the high-dimensional search space caused by large-scale antenna arrays. In this paper, a state-driven adaptive deep-unfolded hybrid beamforming algorithm is proposed for MIMO-JCAS systems. Specifically, the analog precoder update is redesigned in a manifold-based form to better match the geometry of the constant-modulus constraint, while the digital precoder update is enhanced by a learnable gradient-balancing mechanism to alleviate the dynamic imbalance between the communication-rate gradient and the sensing-error gradient. Furthermore, a lightweight state-driven control network is introduced to generate scaling factors for the hyperparameters according to the current iteration state, so that the unfolded model can adapt its update behavior during optimization. Different from conventional deep-unfolded methods with static hyperparameters during inference, the proposed method provides a more effective optimization strategy for the dynamic communication-sensing tradeoff in MIMO-JCAS hybrid beamforming. Simulation results demonstrate the effectiveness of the proposed state-driven adaptive deep-unfolded method. Compared with the conventional deep-unfolded projected gradient ascent (PGA) algorithm with 20 inner iterations, the proposed method improves the joint objective, while achieving faster convergence and stronger robustness. Full article

In this paper, a distributed quasi-generalized Reed–Solomon (Q-GRS)-coded cooperative split labeling diversity (DQ-GRSCC-SLD) scheme is proposed to support reliable cooperative transmission of small-volume information in typical scenarios such as device-to-device (D2D) communication, vehicular ad hoc networks (VANETs) and wireless sensor networks. The system employs distinct labeling mappers at the source and the relay, enabling single-antenna transmission while constructing equivalently a dual-antenna labeling diversity model at the destination, which enhances interference resistance and reduces transmission costs. In addition, an ingenious design is proposed to ensure that the destination obtains the joint Q-GRS code. To optimize the weight distribution of the joint code, a traversal search (TS) algorithm is developed. Furthermore, a low-complexity joint decoding algorithm for Q-GRS codes, namely bracketing decoding, is presented by leveraging the efficient decoding algorithm of generalized Reed–Solomon (GRS) codes. Compared to the conventional maximum likelihood (ML) decoding, its complexity has been reduced from comparing $q^k$ codewords to evaluating q or $q+1$ promising codewords. A theoretical performance analysis of the DQ-GRSCC-SLD scheme is provided. Simulation results reveal that the proposed DQ-GRSCC-SLD scheme demonstrates its superior performance under practical scenarios. Full article