Metamaterial absorbers, an emerging technology, are predominantly employed to reduce the radar cross section (RCS) of objects. This paper presents a novel unstressed chipless RFID sensor based on metamaterial absorbers, enabling passive wireless monitoring of crack widths on highly reflective metal surfaces without the requirement of background calibration. The proposed sensor integrates two elements based on a U-shaped resonator array, whose relative displacement is employed to characterize the crack width, effectively addressing the defect that the sensors based on monolithic patch are prone to fracture under force when monitoring large deformation. In wireless interrogation, the sensor utilizes the square loop consisting of two U-shaped resonators to absorb electromagnetic waves, encoding crack width information in the reflected signal's spectrum, thereby cleverly avoiding the interference of the reflected signal to the conventional chipless RFID backscattered signal. The equivalent circuit model of the sensor is established to analyze the absorption mechanism and sensing principle. Both simulation and experimental results demonstrate that the sensor’s resonant frequency exhibits an approximately linear increase corresponding to the widening of the crack. Furthermore, the experimental results also prove that increasing the number of sensor’s unit cells can enhances the signal absorption capacity, deepens the notch depth of reflected signals, and consequently extends the wireless reading distance. The proposed sensor based on metamaterial absorbers has the advantages of simple structure, low cost and stable wireless reading performance, which provides a competitive scheme for large-scale distributed sensor deployment in Internet of Things (IoT) and structural health monitoring (SHM).

A novel near-field integrated sensing and communications framework for secure unmanned aerial vehicle (UAV) networks with high time efficiency is proposed. A ground base station (GBS) with large aperture size communicates with one communication UAV (C-UAV) under the existence of one eavesdropping UAV (E-UAV), where the artificial noise (AN) is employed for both jamming and sensing purpose. Given that the E-UAV’s motion model is unknown at the GBS, we first propose a near-field localization and trajectory tracking scheme. Specifically, exploiting the variant Doppler shift observations over the spatial domain in the near field, the E-UAV’s three-dimensional (3D) velocities are estimated from echo signals. To provide the timely correction of location prediction errors, the extended Kalman filter (EKF) is adopted to fuse the predicted states and the measured ones. Subsequently, based on the real-time predicated location of the E-UAV, we further propose a joint GBS beamforming and C-UAV trajectory design scheme for maximizing the instantaneous secrecy rate, while guaranteeing the sensing accuracy constraint. To solve the resultant non-convex problem, an alternating optimization approach is developed, where the near-field GBS beamforming and the C-UAV trajectory design subproblems are iteratively solved by exploiting the successive convex approximation method. Finally, our numerical results unveil that: 1) the E-UAV’s 3D velocities and location can be accurately estimated in real time with our proposed framework by exploiting the near-field spherical wave propagation; and 2) the proposed framework achieves superior secrecy rate compared to benchmark schemes and closely approaches the performance when the E-UAV trajectory is perfectly known.

Pinching-antenna systems (PASS) have emerged as a promising technology due to their ability to dynamically reconfigure wireless propagation environments. A novel PASS-based multi-user non-orthogonal multiple access (NOMA) framework is proposed by exploiting the waveguide-division (WD) transmission characteristic. Specifically, each NOMA user cluster is served by one dedicated waveguide, and the corresponding pinching beamforming is exploited to enhance the intra-cluster performance while mitigating the inter-cluster interference. Based on this framework, a sum-rate maximization problem is formulated for jointly optimizing power allocation, pinching beamforming, and user scheduling. To solve this problem, a two-step algorithm is developed, which decomposes the original problem into two subproblems. For the joint power allocation and pinching beamforming design, a penalty dual decomposition (PDD) algorithm is proposed to obtain the locally optimal solutions. Specifically, the coupling constraints are alleviated through augmented Lagrangian relaxation, and the resulting augmented Lagrangian (AL) problem is decomposed into four subproblems, which are solved by the block coordinate descent (BCD) method. For the user scheduling, a low-complexity matching algorithm is developed to solve the user-to-waveguide assignment problem. Simulation results demonstrate that 1) the proposed PASS-based NOMA framework under the WD transmission structure achieves significant sum-rate gain over conventional fixed-position antenna systems and orthogonal multiple access (OMA) scheme; and 2) the proposed matching-based user scheduling algorithm achieves near-optimal user-waveguide association with low computational complexity.

The real-time near-field beamforming framework with the aided of 3D velocity sensing and localization for unmanned aerial vehicle (UAV) communications is proposed. Exploiting the variant Doppler shift over the spatial domain in the near field, the three-dimensional (3D) velocities are estimated with the echo signals. To provide timely correction of the location prediction errors with the estimated velocities, the extended Kalman filter (EKF) is adopted to fuse the predicted states and the estimated ones. Subsequently, the near-field beamforming can be conducted with the predicted locations of the UAV, thereby realizing zero-pilot and low-latency transmission. Numerical results unveil that, the proposed scheme can achieve the accurate tracking of the UAV's flying route.

A smart aggregate can provide the health state of a structural member for the next generation of intelligent infrastructures. This paper proposes an innovative passive aggregate with dual sensitivity enhancement for strain sensing, which has an augmented sensing unit and a compliant displacement amplification mechanism. The sensing unit is composed of a sensor based on a combined patch antenna with an air gap coupling feed to realize the sensitization enhancing. Compliant displacement amplification mechanism is used as the sensor sensitizing mechanism to further enhance the sensitivity. The packaging shell and displacement amplification mechanism of the smart aggregate are integrating 3D printed with VERO high toughness resin and embedded in concrete for experiment. Through sensor modeling and optimization, the effects of various parameters were analyzed to determine the optimal sensor configuration. Experimental results demonstrated the feasibility of the smart aggregate for monitoring internal concrete strain, achieving a maximum sensitivity of 110 MHz/le using quadratic curve fitting and 59 MHz/le with linear fitting. This innovative design provides an effective passive solution for structural health monitoring in complex concrete environments.

Currently, the reader based on frequency modulated continuous wave (FMCW) radar used to dynamically interrogate the chipless RFID sensor needs to collect the envelope of the echo signal through the oscilloscope, which entails expensive acquisition equipment and occupies a considerable amount of space. This paper introduces a low-cost FMCW reader for chipless RFID sensor’s dynamic interrogation. The reader mixes the received signal with the local oscillator signal and down-converts it into a low-frequency signal, which can be directly sampled by a low-cost Analog to Digital Converter (ADC). Then the sensor’s resonant frequency can be extracted from the amplitude and phase variation of the reader’s sampled signal respectively within a single interrogation signal period. The working mechanism of the reader is analyzed theoretically, followed by verification through simulations performed in Advanced Design System (ADS). Hilbert-based algorithms are presented for restoring the amplitude and phase variations of sampled signal in time domain. Then the high-speed reader is employed to wirelessly query a crack sensor, and the measurement results acquired from the reader exhibit excellent concordance with those obtained from vector network analyzer (VNA), demonstrating the accuracy and reliability of the reader. Combined with other types of sensors, the reader can easily read information such as acceleration, dynamic temperature and humidity, providing massive dynamic data for structural health monitoring (SHM) and showing great potential in Internet of Things (IOT).

Traditional acceleration sensors use cables to transport data and batteries to supply power, which may increase failure risk, deployment inconvenience, and maintenance difficulty. This article proposes a passive and wireless acceleration sensing system, namely, a newly designed patch-antenna-based sensing node interrogated by frequency-modulated continuous-wave (FMCW) radar. The acceleration is correlated with the location of a cantilever beam, whose oscillation alters the additional capacitance of the patch antenna and consequently the resonant frequencies. The testing range can be adjusted by changing the material and dimensions of the cantilever beam, which is designed up to ±110 m/s 2 with a sampling rate of 500 Hz to meet the requirements of different conditions. The working mechanism of the sensing system is analyzed theoretically and then verified by the simulation in COMSOL Multiphysics. Then, an experiment is carried out to evaluate the performance of the sensing system. Both the resonant frequency and remaining power can be utilized to extract the acceleration response, and results show a good fit with the actual response (i.e., an average error of 4.5%). Empowered by FMCW Radar, the passive accelerometer may have great potential in identifying structure strain mode, impedance-based detection of bolt loosening, automation in construction, etc.