Iet Microwaves Antennas & Propagation最新文献

This paper introduces an efficient method of moments (MoM) designed to explore electromagnetic scattering in multilayered anisotropic structures. Each layer is made up of a dielectric anisotropic material characterised by a generalised tensor for permittivity, which is unrestricted in its geometrical configuration. The authors’ approach analyses each layer independently, employing the surface equivalence theorem to substitute the interfaces between layers with suitable equivalent electric and magnetic surface current densities. The authors derive the necessary surface integral equations (SIEs) for each interface by implementing the proper boundary conditions. The analysis utilises rotated dyadic Green's functions that populate the infinite space with the material properties specific to each anisotropic layer. The rotation angle corresponds to the deviation between the local principal coordinate system of the material and the global coordinate system, which is determined by diagonalising the full dielectric tensor of the respective anisotropic material given in the global coordinate system. To address the SIEs for determining the unknown equivalent electric and magnetic surface current densities, Galerkin's MoM is applied. This involves expanding the unknown surface currents using suitable basis functions, simplifying the issue to a matrix equation solved through the inversion of a block-tridiagonal impedance matrix. The diagonal nature and sparse structure of the impedance matrix, along with an effective block-inversion method, significantly boost computational efficiency and reduce memory demands. To demonstrate the feasibility of the proposed method, the authors present a detailed derivation of the impedance matrix for the case of non-magnetic uniaxial anisotropic media for which the Green's functions are available in closed form. The validity and efficiency of the proposed SIE-MoM scheme are demonstrated by comparing the results of several case studies against those found in literature and results obtained via commercial numerical codes.

This paper presents the design of novel compact multifunctional coaxial to waveguide power combining transition (PCT) for X-band applications. For the proof of the proposed concept, 2-way PCT operating over the entire X-band (8.2–12.4 GHz) and 4-way PCT operation from 9.5 to 10.8 GHz are designed, developed, and characterised. Two-way PCT achieves a measured return loss better than 14 dB over the operating band, and the measured amplitude imbalance and phase imbalance are within 0.25 dB and 4°, respectively. Four-way PCT achieves a measured return loss better than 15 dB over the operating band, and the measured amplitude imbalance and phase imbalance are within 1 dB and 10°, respectively. Furthermore, a 6-way PCT is also designed, fabricated, and measured to demonstrate the scalability of the proposed concept. The 6-way PCT achieves the measured return loss better than 15 dB from 9.9 to 10.475 GHz, and measured amplitude and phase imbalances are within 0.6 dB and 10°, respectively. The designed power combining transition is proposed to be used in X-band applications like antenna array applications and power combining applications.

A novel broadband water-based Fabry–Pérot (FP) antenna with beam-steerable technology is proposed. The antenna consists of a water-based reconfigurable partially reflective surface (RPRS) and a source antenna. The proposed water-based RPRS has 13 columns of microfluidic channels inside. The water-based RPRS achieved 1-D beam steering by regulating phase distribution through the injection of water into its microfluidic channels. The antenna has exhibited a 10-dB impedance bandwidth from 5.07 to 6.46 GHz (a fractional bandwidth of 24.1%). This design achieves a beam steering from −11° to +11° in the elevation plane, with measured realised gains over 10 dBi. To verify the correctness of the design, an antenna prototype was fabricated. The measured results are in good agreement with the simulated results, confirming the accuracy of the design principle. The measured results demonstrate that the main beam of the antenna prototype tilts to −12° in the broadside direction.

Intelligent Reflecting Surfaces (IRS) enhance wireless communication by optimising signal reflection from the base station (BS) towards users. The passive nature of IRS components makes tuning phase shifters difficult and direct channel measurement problematic. This study presents a machine learning framework that directly maximises the beamformers at the BS and the reflective coefficients at the IRS, bypassing conventional methods that estimate channels before optimising system parameters. This is achieved by mapping incoming pilot signals and data, including user positions, with a deep neural network (DNN), guiding an optimal setup. User interactions are captured using a permutation-invariant graph neural network (GNN) architecture. Simulation results show that implicit channel estimation method requires fewer pilots than standard approaches, effectively learns to optimise sum rate or minimum-rate targets, and generalises well. Specifically, the sum rate for GDNNet (GNN + DNN) improves by $��12.57�\%�$ over linear minimum mean square error (LMMSE) and by $��12.42�\%�$ over perfect CSI concerning the number of users, and by $��28.57�\%�$ over LMMSE and by $��14.28�\%�$ over perfect CSI concerning pilot length. Offering a feasible solution with reduced computing complexity for real-world applications, the proposed GNN + DNN method outperforms conventional model-based techniques such as LMMSE and approaches the performance of perfect CSI, demonstrating its high effectiveness in various scenarios.

The increased demand for user device connectivity has led to spectral congestion which is driving exploration of higher frequency spectrum, such as millimetre wave frequencies. As millimetre wave propagation is predominantly line-of-sight, shadowing becomes prevalent in indoor environments due to obstructions from clutter. Accordingly, there is a need to find solutions which can provide additional coverage. In this work, octant-shaped spherical reflectors are deployed in small office environments with varying degrees of clutter to provide additional ray paths to improve millimetre wave coverage into shadow regions. Cost weightings have been allocated to prioritise regions of high importance and are used to compare reflector deployment strategies. Appropriate positioning of reflectors in the environment is shown to improve coverage into shadow regions in all three environments considered, with placement in the top corners of a room found to be a valid solution. In densely cluttered environments, more than one reflector may be required to provide sufficient coverage. Reducing the reflector radius by 0.1 m has been shown to increase reflected power by up to 6 dB in some cases.

This paper presents a compact, broadband, high-gain dielectric rod antenna. By utilising an air–dielectric hybrid method for designing the radiating and matching sections, gradual variations in the average equivalent permittivity along the rod are achieved, and the mechanism of the method is analysed. This approach facilitates a smooth impedance transition from the feed to the air, resulting in good impedance matching characteristics. Additionally, the antenna is fed through a tapered double-ridged waveguide (DRW) with a coaxial line to tapered DRW transition. The proposed antenna achieves an impressive impedance bandwidth of 90.2%, covering the entire K and Ka bands. The unique structure of the proposed dielectric rod significantly enhances the antenna's gain, reaching a maximum value of 17.86 dBi. With its small aperture and compact longitudinal dimensions, this antenna is suitable for applications in settings like the Space Environment Simulation Research Infrastructure (SESRI).

This paper proposes a single-shot computational imaging using a new frequency-diverse aperture, an open-ended cavity with a rough surface base. First, it shows that scattering from a conducting rough surface made of conducting cones placed at random positions on a conducting ground plane, normally illuminated by an ultra-wideband horn antenna (working in the 2–20 GHz range) provides random patterns with a frequency correlation function (FCF) width of Δf, about hundreds of MHz. Next, by introducing four conducting walls placed around the rough surface, it obtains a higher number of spatially uncorrelated radiation patterns and a narrower FCF width of about Δf/10, tens of MHz. To approximate the radiation patterns and measurement matrices in the numerical simulations, the geometrical optics (GO) approximation is used taking into account multiple interactions. On the other hand, to estimate them in practice, a trihedral corner reflector installed on an XYZ positioning table is employed. Finally, the image of a planar object with the shape of plus is reconstructed using the minimum least-squares technique. The paper shows that for a 0.81 square metre image size, a decent-focused image with a pixel size of about 0.81/400 square metres (about 5 cm × 5 cm) is realisable by using 400 frequency samples within the frequency range of 2–20 GHz.

In this paper, a 280–300 GHz hybrid-integrated transmitter is proposed. The advantages of the SiGe and InP chips are fully made use by integrating these two chips. For low cost and high integration, the local oscillator chain and mixer are based on chips in SiGe technology, and the 300-GHz power amplifier and on-chip antenna are realised in InP technology for high output power and small die size. The low-cost bonding wires are introduced for the interconnection between these two chips, and the lens are attached above the on-chip antenna for further EIRP enhancement. Finally, the proposed transmitter is fabricated and measured, which shows comparable performances with 21.9 dBm EIRP (equivalent isotropic radiated power) and 10 Gbps data rate.

This paper presents a systematic antenna design methodology that integrates machine learning, leveraging the progressive growth technique of Progressive Growing of GANs (PGGAN) to generate images of various dual-band PIFA-like antenna structures. The process involves using data augmentation methods to generate 4180 antenna samples. In the latent space, the authors employ Latin Hypercube Sampling to maintain diversity and combine it with the Hough Transform to enhance the edge features of the antennas while providing labelling functionality. This labelling method strengthens the relationship between antenna frequency and wavelength characteristics. The paper clearly outlines the design process, starting from the simulation of two types of single-frequency PIFA-like antennas (2.45 and 5.2 GHz, respectively) to the completion of PGGAN's generation task, resulting in a novel dual-band Wi-Fi PIFA-like antenna structure. The measurement results of the dual-band antennas exhibit excellent consistency with the simulation results.

This work presents a numerical technique for the analysis of the Radar Cross Section (RCS) of large targets combining macro-basis functions, the multilevel fast multipole method and the generation of near-field preconditioners, using an approximate inverse matrix where the sparsity pattern is dynamic and computed considering an upper memory threshold. In order to improve the scalability, a group of rows is computed using the same least squares matrix minimising the Frobenius norm of the error, rendering each row group problem independent from the rest. This approach is applied to large and realistic problems in the test cases included. The presented preconditioner can be used to optimise the convergence of complex problems with respect to the hardware resources available in each case while being transparent to the user.