A self-focusing receive beamforming scheme is proposed in this paper. It is achieved by embedding information in the intermedium frequency (IF) components produced by non-linearly mixing the incoming multi-tone radio frequency (RF) signals. This receiver structure enjoys low-cost, low-power consumption, and, more importantly, the receive beamforming gain irrespective of the angles of arrival (AoAs) of the incoming RF signals. The theoretical derivations are presented, and are further validated through circuits and system simulations. The results highlight the self-focusing capability of the proposed receive architecture, offering a promising solution for the resource-constrained Internet of Things (IoT) applications.

This study investigates self-impedance tuning for antennas, a novel approach with the potential for dynamic impedance adjustments. Using half-wave dipoles as an example, the work capitalizes on a hybrid coupler system and a feed signal's power to adapt the antenna's impedance in real time by injecting an auxiliary control signal into the antenna feed terminals in order to adjust its input impedance. The study investigates how simultaneous impinging and auxiliary signals, along with varying phases between them, influence the antenna's input impedance. Additionally, it examines practical challenges related to impedance tuning. This study proposes a robust solution that is applicable to any one-port antenna type, for optimal power transfer in ever-evolving wireless environments.

This paper outlines the theory behind helicoid antenna array beamforming and the practical validation on an 8 & times; 8 helicoid antenna array. Design, simulation, and measurement are presented at 2.45 GHz. A practical method for obtaining the phase steering weights required to perform beam pointing over 360 degrees is presented. A specialised dipole was also developed, achieving 4.9 dBi and low mutual coupling. It was also shown by analysis, simulation and measurement that this type of array, unlike a planar array, does not exhibit beam pointing error, making it highly attractive for retrodirective applications when precision beam pointing is required.

Backscatter communication (BackCom) has emerged as a promising solution for ultra-low-power wireless information transmissions. Traditionally, it is commonly assumed that BackCom links can only be established at the frequencies at which the backscatter tag antennas resonate. In our study, it has been shown that it is feasible for BackCom systems to operate beyond the antenna resonant frequencies. A novel scattering cross-section (SCS)-assisted optimization approach is proposed, where the operating bands of the system are defined based on the experimentally measured SCS of the entire tag rather than tag antenna resonant frequencies. Simulation results demonstrate that the BackCom system can operate effectively beyond narrow resonant frequencies, enabling more flexible frequency band selections. These findings highlight the significance of tag scattering characteristics in optimizing BackCom designs.

Near-field (NF) microwave and millimeter-wave (mm-wave) imaging, extending into the terahertz (THz) frequency range, has seen remarkable advancements across diverse applications, particularly security screening. These technologies benefit from the unique properties of microwave, mm-wave, and THz (MMT) spectra, such as penetration, nonionizing radiation, material sensitivity and the capability to operate in all weather conditions. This article provides an overview of the evolution and current state of NF radar imaging, emphasizing the critical role of signal processing in overcoming challenges related to hardware complexity, long acquisition time, and image reconstruction quality. Advanced signal processing techniques—including Fourier-based algorithms, sparse imaging, low-rank matrix recovery, and deep learning—are highlighted for their contributions to enhancing image resolution and processing efficiency. The article also discusses recent innovations in antenna technologies, aperture configurations, and scanning methods that have significantly improved NF radar imaging capabilities. Future research directions are suggested to further advance the field, highlighting the importance of continued exploration and innovation in NF MMT imaging.

This article presents an in-depth investigation into the design and experimental validation of an antenna array for a metallic casing handset device, optimized for millimeter-wave (mmWave) 5G frequencies, specifically within the 3GPP n257 band (26.5-29.5 GHz). It outlines the transformation of a single antenna element into a 4 x 1 linear array configuration. Deploying three such arrays within the mobile device, the study evaluates their performance across various scenarios mimicking real-world user interactions, with a focus on signal blockage due to hand placement. The study demonstrates that the optimized antenna locations achieve considerable gain coverage, further enhanced through the implementation of beam steering, aimed at mitigating signal blockage effects. This article also explores the diminishing returns of increasing the phase shifter resolution. Experimental results, supported by extensive simulations and far-field measurements, validate the antenna array's efficacy in providing quasi-omnidirectional radiation patterns and robust performance in the face of user-induced blockages. The practical mobile device antenna array results are used for a comprehensive analysis in the form of the cumulative distribution function (cdf) performance of the mobile device. Spectral efficiency (SE) is also assessed for direct line-of-sight (LOS) scenarios, and also in reflective intelligent surface (RIS) assisted wireless environments in which LOS is not available, which showcases the practicality of the device in B5G/6G applications. The set of conclusions provides valuable insights for next-generation mobile communication system design and deployment.

This article provides a summary of the development of a technique for creating coherence of transmissions from multiple, independent, distributed transmitters at the location of a non-communicative receiver for the purposes of long-range wireless power transfer (WPT). This technique has been named sequential phase optimization. This article presents a brief review of long-range distributed WPT techniques, the development of the sequential phase optimization process including results of mathematical modeling performed in MATLAB, and the results of laboratory experiments to demonstrate the technique. This article presents new simulations and experimental results that are additional to what has been presented before. The testing demonstrated that each additional power beacon (PB) added approximately 3 dB of power at the receiver once the synchronization process had been completed. Synchronization time was demonstrated using phase cycling times as short as 24.6 mu s.

This communication presents an approach for the fast and accurate direction of arrival (DoA) estimating using a chaotic cavity-backed antenna integrated with a Rotman lens-based demultiplexer coupled with a diode detector estimator module. The proof of concept is demonstrated at millimeter-wave (mmWave) frequencies. The designed chaotic cavity antenna receives a signal and compresses the source plane wave fields into a single channel. Leveraging a Rotman lens connected to a set of open-circuited transmission lines provides frequency-selective reflections and the wideband signal is split into multiple subbands to enable parallel processing and use of low-cost narrowband mmWave components. The subbands are then processed through parallel diode detector estimation modules. This communication validates the proposed approach using the experimental data. The proposed technique aids in low cost, low processing bandwidth, and low hardware complexity for DoA estimation in mmWave systems.

Directional modulation (DM) is a physical-layer security (PLS) technique implemented at the transmitter, leveraging antenna arrays to ensure secure communications. Through a process of spatial precoding between transceivers to transmit signals in specific directions, DM is capable of disrupting communications in unintended directions to prevent eavesdropping. In general, recent progress in the development of MIMO systems, including advanced radio frequency (RF), antenna technologies, along with innovative precoding algorithms, has enhanced the capabilities of DM techniques, leading to a multitude of robust DM variants. Hence, this survey aims to offer a comprehensive overview of DM, covering its fundamentals, promising variants, applications, hardware implementations, and future trends. Initially, the basic principle of DM is outlined in a general manner for subsequent comprehension. Subsequently, the large family of DM techniques is categorized into distinct variants based on the types of transmitting arrays. Next, we give a comprehensive survey of DM in common wireless scenarios, including multiuser (MU), relay, Internet of Things (IoT), and nonorthogonal access (NOMA) networks. Furthermore, we provide an illustration of DM system implementations, encompassing foundational architectures and cost-effective hardware realizations. Finally, concerning the unresolved challenges and current research focal points in DM, we present future research directions that merit further exploration and reference.

This article presents an innovative metamaterial-based radio frequency (RF) energy harvesting system designed to efficiently capture ambient RF energy across multiple frequency bands, including Wi-Fi (2.45 GHz) and 5G (0.9, 1.8, 2.1 GHz). Utilizing electric inductive-capacitive resonators and a rectification circuit, the system converts ambient RF energy into direct current (dc) power with high efficiency. Specifically, a single unit cell of the proposed 8 x 8 harvester is capable of generating up to 562 mu W under an RF ambient power density of 40 mu W/cm(2). This high efficiency and scalability make it ideal for powering low-power Internet-of-Things (IoT) devices and sensors. The design emphasizes optimizing the unit cell to minimize computational complexity, enabling a more straightforward and scalable implementation. Experimental results demonstrate the system's ability to efficiently harvest RF power across the specified bands, validating its potential as a sustainable solution for the growing power demands of IoT networks.

Massive multiple-input multiple-output (MIMO) systems have gained increasing importance in applications such as target detection, tracking, and wireless communications, where accurate and efficient direction-of-arrival (DOA) estimation is crucial. However, the high computational complexity involved in estimating both azimuth and elevation angles using massive antenna arrays poses a significant challenge for real-time implementation. In this paper, two novel approaches are proposed for efficient active azimuth-elevation DOA estimations in massive MIMO radar systems: the one-dimensional (1D) spatial searches approach (1D-SSA) and the spatial searchless approach (SSLA). These approaches address the high computational complexity typically associated with multi-dimensional spectral searches and solving optimization problems in massive MIMO systems. The 1D-SSA reduces the computational burden by creating a special arrangement of the collected data and breaking the spectral search into multiple 1D searches, while the SSLA eliminates the need for spectral searches entirely by leveraging structured subarrays and eigendecomposition techniques. Both approaches are evaluated in terms of accuracy, resolution and computational efficiency. Also, the performance of different methods is compared with the Cram & eacute;r-Rao bounds (CRBs) derived in this paper. The proposed approaches are shown to be well-suited for near real-time massive MIMO radar systems with high accuracy and reduced computational overhead.

In this study, we investigate and fabricate a superdirective antenna array composed of strip dipole elements operating at a frequency of 3.5 GHz. The spacing, dimensions, and phase difference of the elements are optimized to achieve a super realized gain antenna with a theoretical efficiency of 98.8% and computed efficiency of 99.3%. By employing an element spacing of 0.2$\lambda$, the end-fire antenna array demonstrates a maximum theoretical realized gain of 6.4 dBi, and a maximum computed realized gain of 6.3 dBi. Significantly, our proposed superdirective antenna array distinguishes itself from existing approaches by achieving high directivity, high radiation efficiency, and impedance matching to 50 $\Omega$ solely through careful adjustments in the strip dimensions and the inter-element phase. This eliminates the need for additional impedance matching networks, amplifiers, or attenuators.

There are scenarios where Distributed Wireless Power Transfer (WPT) might be required to work without any steering (pilot signal) or information feedback from the power receiver. A new Sequential Phase Optimization (SPO) technique has been developed to create coherence from independent, distributed transmitters at the spatial location of a non-communicative power receiver. This would increase the efficiency of the power transfer compared to incoherent systems. The proposed technique was tested under laboratory conditions.

Direction-of-arrival (DOA) estimation plays a crucial role in array signal processing across various domains, including radar, sonar, wireless communications, and seismic exploration. However, traditional DOA techniques often assume either far-field (FF) or near-field (NF) propagation, limiting their applicability in scenarios involving mixed-field sources. DOA estimation and localization in scenarios involving mixed NF and FF sources is a complex and dynamic field that has garnered significant research attention in recent years. This multifaceted and evolving area holds promise for addressing challenges in radar, wireless communications, and acoustic sensing applications. This review paper provides a comprehensive overview of the methodologies, techniques, and advancements in this domain. We categorize existing methodologies, discussing their advantages and limitations. Furthermore, we delve into the mathematical modeling of mixed-field sources and essential signal processing techniques for parameter estimation. Special attention is given to technical issues such as aperture loss, computational complexity, and hardware considerations. The paper discusses the various sources of noise in the mentioned scenario and highlights the importance of modeling noise accurately for effective estimation. It also explores different scenarios and assumptions considered in the literature, ranging from non-Gaussian and non-stationary noise environments to scenarios involving multipath propagation and unknown mutual coupling effects. A detailed examination of the statistical approaches used in DOA estimation and localization reveals a diverse range of methods, including higher-order statistics and second-order statistics, each with its own advantages and applications. A comparative evaluation of various approaches highlights their performance in terms of estimation accuracy, resolution, aperture loss and computational efficiency. This provides insights into the trade-offs involved in choosing between different approaches. The review also identifies promising future research directions, such as the exploration of advanced signal processing techniques like compressive sensing and deep learning, exact NF modeling, estimation based on one-bit measurements, the integration of polarization diversity, employing metasurface antennas, tracking parameters, and the utilization of full-wave or experimental data for a more realistic representation of the challenges. By reviewing advances in methodologies and techniques, as well as outlining future research directions aimed at addressing the complexities of mixed-field scenarios, this paper paves the way for the development of more robust and reliable localization systems capable of handling real-world complexities.

This paper proposes a novel approach to 3-D microwave imaging using dynamic metasurface antennas in a multistatic configuration. By introducing a panel-to-panel model and a preprocessing technique, raw measurements are converted into the space-frequency domain for efficient data acquisition and reconstruction. Adapting the range migration algorithm in this work enables fast Fourier-based image reconstruction. Simulation results showcase the effectiveness of the proposed method, highlighting its potential for real-world applications.

This study presents a superdirective antenna array specifically designed for the sub-6 5G frequency range, incorporating pioneering Huygens antenna elements. The optimized structure achieves a realized gain that surpasses Harrington's well-known maximum theoretical limit for antenna directivity, effectively addressing practical concerns related to ohmic and return losses. Additionally, the compact size of the proposed antenna array, as opposed to a uniform linear array, offers the potential to fabricate highly radiation-efficient, high-directivity antennas in a compact form.

Achieving high imaging resolution in conventional monostatic radar imaging with mechanical scanning requires excessive acquisition time. Although real aperture radar systems might not suffer from such a limitation in acquisition time, they may still face challenges in achieving high imaging resolution, especially in near-field (NF) scenarios, due to diffraction-limited performance. Even with sophisticated electronic scanning techniques, increasing the aperture size to improve resolution can lead to complex hardware setups and may not always be feasible in certain practical scenarios. Multistatic systems can virtually increase the effective aperture but introduce challenges due to the required number of antennas and channels, making them expensive, bulky and power-intensive. An alternative solution that has been proposed in recent years is the compression of the physical layer using metasurface transducers. This paper presents a novel NF radar imaging approach leveraging dynamic metasurface antennas with multiple tuning states called masks, in a bistatic structure, using the Kirchhoff migration principle. The method involves expanding the compressed measured signal from the mask-frequency domain to the spatial-frequency domain to decode the scene's spatial content. The Kirchhoff integral is then developed based on the introduced special imaging structure to retrieve the three-dimensional spatial information of the target. Comprehensive numerical simulations analyze the masks' characteristics and their behavior under different conditions. The performance of the image reconstruction algorithm is evaluated for visual quality and computing time using both central processing units and graphics processing units. The results of computer simulations confirm the high reliability of the proposed approach in various cases.

In recent decades, microwave imaging technology has been used in a variety of applications including security, medicine, nondestructive testing and structural health monitoring. Traditional microwave imaging systems often suffer from drawbacks such as long acquisition times and complex array structures. To address these issues, this paper introduces a panel-to-panel microwave computational imaging (CI) technique for near-field operation using dynamic metasurface antennas for both transmission and reception, enhancing system diversity and enabling real-time applications. The paper also outlines mathematical models for three-dimensional image reconstruction algorithms tailored to this scenario. The results of numerical and electromagnetic simulations show the feasibility of this approach for CI-based imaging, with both Fourier and least squares-based image reconstruction techniques.

This paper reviews how recent advancements in sparse antenna arrays optimization help reduce mutual coupling, even in simple setups like 2 x 2 and 3 x 3 microstrip patch antennas Uniform Rectangular Array (URA). It discusses and compares techniques and widely used optimisation methods to enhance array analogue beamforming performance and minimise interference through side-lobe reduction. The study shows that careful positioning and use of optimisation algorithms can help not only maintain the array gain, but also reduce inter-element coupling, making it useful for very basic array configurations.