Frequency Band Research Articles

Exploring the Impact of Split Ring Resonator Metamaterial Structure Integration on 4X4 MIMO Antenna Performance in Sub-6GHz Bands for 5G Applications

This research delves into the realm of antenna engineering, with a specific focus on examining the performance of 4x4 MIMO antennas with and without integration of split ring resonator metamaterial structure. The objective is to comprehend the influence of split ring resonator metamaterials on antenna characteristics within the 6 GHz frequency range. Employing CST Studio Suite software, comprehensive simulations are conducted to evaluate various parameters including gain, directivity, radiation efficiency, S-parameters, power distribution, VSWR, and total efficiency. In the frequency band up to 6GHz, observed gain values were 24.62dB without split ring resonator metamaterial integration and ranging from 6dB to 27dB with integration. Through a systematic comparison, the study aims to delineate the precise effects of split ring resonator metamaterials on antenna performance, thereby offering valuable insights into their potential for enhancing MIMO antenna systems.

High-Speed Surface Property Recognition with a 140 GHz Frequency

In the field of integrated sensing and communication, there is a growing need for advanced environmental perception. The terahertz (THz) frequency band, significant for ultra-high-speed data connections, shows promise in environmental sensing, particularly in detecting surface textures crucial for autonomous systems’ decision-making. However, traditional numerical methods for parameter estimation in these environments struggle with accuracy, speed, and stability, especially in high-speed scenarios like vehicle-to-everything communications. This study introduces a deep learning approach for identifying surface roughness using a 140-GHz setup tailored for such conditions. A high-speed data acquisition system was developed to mimic real-world scenarios, and a diverse set of rough surface samples was prepared for realistic high-speed datasets to train the models. The model was trained and validated in three challenging scenarios: random occlusions, sparse data, and narrow-angle observations. The results demonstrate the method’s effectiveness in high-speed conditions, suggesting terahertz frequencies’ potential in future sensing and communication applications.

Design of an adjustable sound-absorbing structure with low frequency advantages

The thickness of microperforated panel absorbers with low-frequency sound absorption ability is often large and the absorption bandwidth is limited. To address this issue, a adjustable microperforated panel structure with low-frequency advantage (ASWLF) was designed. Compared to conventional structures, the introduction of inclined chambers allows the structure to absorb lower-frequency noise at the same thickness, enhancing spatial utilization efficiency. The addition of a rotating structure design broadens the frequency range over which the structure can operate effectively. The addition of a rotating structure design broadens the frequency range of the structure's action. The acoustic absorption coefficient of the model can be calculated using acoustic-electric analogy, which is used to predict the acoustic absorption coefficient of the ASWLF structure. The experimental results show that, with the same acoustic absorption performance, the thickness of the structure is reduced by 36.7%. The multi-stage combination allows the structure to achieve better acoustic absorption performance in a wider frequency band. By introducing the PSO optimization algorithm, the optimized ASWLF structure further improves the acoustic absorption frequency band by 32.9%. This study provides an effective method for solving noise environments under different conditions in industrial practical applications.

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice

Although mice are social, multiple animals’ neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure. The power of lower frequency bands—delta to alpha—were correlated with each other and anti-correlated with gamma power. The high-to-low-power ratio (HLR) provided a useful measure to understand LFP changes along the change of behavioural and locomotive states. The HLR during huddled conditions was lower than that during non-huddled conditions, dividing the social context into two. Multi-brain analyses of HLR indicated that the mice in the group displayed high cross-correlation. The mice in the group often showed unilateral precedence of HLR by Granger causality analysis, possibly comprising a hierarchical social structure. Overall, this study shows the importance of the social environment in brain dynamics and emphasises the simultaneous multi-brain recordings in social neuroscience.

Fault feature extraction method based on maximum envelope spectrum PFGI2 and empirical wavelet transform

Fast kurtogram (FK) is an efficient method for processing non-stationary signals, widely recognized by scholars as a rapid and effective approach for fault diagnosis. However, it has limitations in distinguishing between periodic pulse and random interference pulses due to the drawbacks in its frequency band segmentation methods and the inherent shortcomings of the kurtosis index itself. To address this, this paper proposes a fault feature extraction method based on the maximum envelope spectrum power function-based Gini indices (PFGI2) and empirical wavelet transform. This method, inspired by the concept of FK, constructs a series of band-pass filters following the principles of empirical wavelet decomposition. It applies envelope spectrum analysis to a series of sub-bands and calculates the PFGI2 value for each, to identify the optimal sub-band. The effectiveness of the proposed method is validated through simulations of vibration signals and experimental data.

Research on the application of the terahertz technique

Terahertz is a new radiation source with many unique advantages and terahertz technology is a very important cross-cutting frontier field, providing a very attractive opportunity for technological innovation, national economic development and national security that may lead to revolutionary developments in science and technology. This article introduces the advantages and disadvantages of electromagnetic waves in the terahertz frequency band, the origin and development history of terahertz technology, and the composition of common terahertz systems, and outlines the technologies of secure communication, detection, imaging, etc., according to their principles. The analysis shows that under the premise of ensuring the size of its key devices to be miniaturized in application, and solving the technical difficulties such as its complicated use, high overall cost and reliance on low-temperature operation, the terahertz technology will have a broad market prospect in the fields of biology, medical treatment, communication, military security and so on.

A hybrid wave vibration energy harvester with electromagnetic double-speed and piezoelectric up-frequency driven by a rotating ball

The energy crisis and environmental pollution have driven the development of ambient energy harvesting technologies, and ocean waves usually contain abundant vibration energy, making the study of wave energy harvesting technology of profound value. This paper proposes a hybrid wave vibration energy harvester with electromagnetic double-speed and piezoelectric up-frequency driven by a rotating ball. For the electromagnetic generator (EMG), the excitation magnet and coil move simultaneously, resulting in double the flux variation rate compared with traditional structures, enhancing the output voltage. For the piezoelectric transducer (PZT), four piezoelectric cantilever beams are magnetically coupled with the EMG, generating power through bistable motion and broadening the working frequency band of the cantilever beam structure. The harvester is modeled and simulated, and its performance is tested on a simulated vibration platform, with simulation and experimental results in good agreement. Under external excitation at 0.8 Hz, the optimal load and maximum power for each EMG are 8.2 Ω and 207.2 mW, respectively, and the optimal load and maximum power for each PZT are 100 kΩ and 1.52 mW, respectively. The harvester can produce a maximum output power of 420.48 mW, demonstrating high efficiency in energy capture under low-frequency and multidirectional wave excitation.

Broad‐range, high‐linearity, and fast‐response pressure sensing enabled by nanomechanical resonators based on 2D non‐layered material: β‐In2S3

AbstractTwo‐dimensional (2D) non‐layered materials, along with their unique surface properties, offer intriguing prospects for sensing applications. Introducing mechanical degrees of freedom is expected to enrich the sensing performances of 2D non‐layered devices, such as high frequency, high tunability, and large dynamic range, which could lead to new types of high performance nanosensors. Here, we demonstrate 2D non‐layered nanomechanical resonant sensors based on β‐In2S3, where the devices exhibit robust nanomechanical vibrations up to the very high frequency (VHF) band. We show that such device can operate as pressure sensor with broad range (from 10−3 Torr to atmospheric pressure), high linearity (with a nonlinearity factor as low as 0.0071), and fast response (with an intrinsic response time less than 1 μs). We further unveil the frequency scaling law in these β‐In2S3 nanomechanical sensors and successfully extract both the Young's modulus and pretension for the crystal. Our work paves the way towards future wafer‐scale design and integrated sensors based on 2D non‐layered materials.image

Chaff Cloud Integrated Communication and TT&C: An Integrated Solution for Single-Station Emergency Communications and TT&C in a Denied Environment

In response to potential denial environments such as canyons, gullies, islands, and cities where users are located, traditional Telemetry, Tracking, and Command (TT&C) systems can still maintain core requirements such as availability, reliability, and sustainability in the face of complex electromagnetic environments and non-line-of-sight environments that may cause service degradation or even failure. This paper presents a single-station emergency solution that integrates communication and TT&C (IC&T) functions based on radar chaff cloud technology. Firstly, a suitable selection of frequency bands and modulation methods is provided for the emergency IC&T system to ensure compatibility with existing communication and TT&C systems while catering to the future needs of IC&T. Subsequently, theoretical analyses are conducted on the communication link transmission loss, data transmission, code tracking accuracy, and anti-multipath model of the emergency IC&T system based on the chosen frequency band and modulation mode. This paper proposes a dual-way asynchronous precision ranging and time synchronization (DWAPR&TS) system employing dual one-way ranging (DOWR) measurement, a dual-way asynchronous incoherent Doppler velocity measurement (DWAIDVM) system, and a single baseline angle measurement system. Next, we analyze the physical characteristics of the radar chaff and establish a dynamic model of spherical chaff cloud clusters based on free diffusion. Additionally, we provide the optimal strategy for deploying chaff cloud. Finally, the emergency IC&T application based on the radar chaff cloud relay is simulated, and the results show that for severe interference, taking drones as an example, under a measurement baseline of 100 km, the emergency IC&T solution proposed in this paper can achieve an accuracy range of approximately 100 m, a velocity accuracy of 0.1 m/s, and an angle accuracy of 0.1°. In comparison with existing TT&C system solutions, the proposed system possesses unique and potential advantages that the others do not have. It can serve as an emergency IC&T reference solution in denial environments, offering significant value for both civilian and military applications.

A compact tri-notched flexible UWB antenna based on an inkjet-printable and plasma-activated silver nano ink

The rapid development of ultrawideband (UWB) communication systems has resulted in increasing performance requirements for the antenna system. In addition to a wide bandwidth, fast propagation rates and compact dimensions, flexibility, wearability or portability are also desirable for UWB antennas, as are excellent notch characteristics. Although progress has been made in the development of flexible/wearable antennas desired notch properties are still rather limited. Moreover, most presently available flexible UWB antennas are fabricated using environmentally not attractive subtractive etching-based processes. The usage of facile additive sustainably inkjet printing processes also utilizing low temperature plasma-activated conductive inks is rarely reported. In addition, the currently used tri-notched flexible UWB antenna designs have a relatively large footprint, which poses difficulties when integrated into miniaturized and compact communication devices. In this work, a silver nano ink is used to fabricate the antenna via inkjet printing and an efficient plasma sintering procedure. For the targeted UWB applications miniaturized tri-notched flexible antenna is realized on a flexible polyethylene terephthalate (PET) substrate with a compact size of 17.6 mm × 16 mm × 0.12 mm. The antenna operates in the UWB frequency band (2.9–10.61 GHz), and can shield interferences from WiMAX (3.3–3.6 GHz), WLAN (5.150–5.825 GHz) and X-uplink (7.9–8.4 GHz) bands, as well as exhibits a certain of bendability. Three nested "C" slots of different sizes were adopted to achieve notch features. The simulation and test results demonstrate that the proposed antenna can generate signal radiation in the desired UWB frequency band while retaining the desired notch properties and having acceptable SAR values on-body, making it a viable candidate for usage in flexible or wearable communication transmission devices. The research provides a facile and highly efficient method for fabricating flexible/wearable UWB antennas, that is, the effective combination of inkjet printing processing, flexible substrates, low temperature-activated conductive ink and antenna structure design.

Reverse optimization design of OAM sound barrier based on acoustic metamaterials

An optimized acoustic metamaterial (OAM) railway sound barrier has been designed to address the growing noise problem in railway construction. The low-frequency broadband noise attenuation is realized by an reverse design method relying on genetic algorithm-neural network (GA-NN). Simulation results show that the OAM can perfectly cover the target frequency band from 400 Hz to 1000 Hz with a bandgap ranging from 210 Hz to 1253 Hz. Compared with the initial acoustic metamaterial (IAM), the bandgap of the OAM is widened by 1295 Hz, and the sound transmission loss is improved by 15 dB. The noise reduction performance of the OAM is verified by the experiments of the fully-enclosed impedance tube and the simulation of the acoustic field modes. The acoustic experiments of the semi-enclosed OAM sound barriers show that the noise reduction of OAM sound barriers has a low-frequency broadband noise reduction effect. Compared with the existing sound barriers, the average noise reductions of OAM sound barriers in the target frequency band and bandgap range are improved to 15.9 dB and 7.8 dB, respectively.

A Wide-Band Circularly Polarized Euler Spiral Dielectric Resonator Antenna for X/Ku-Band Applications

This paper puts forward a low-profile, circularly polarized (CP), wideband Euler’s Spiral Dielectric Resonator Antenna (ES-DRA) having a footprint of 0.68 λ × 0.68 λ × 0.096 λ and operating in X and Ku-band (8.26–14 GHz). A cross-shaped aperture is used to couple the power from 50 Ω walking stick-shaped microstrip line to the ES-DRA. The antenna generates circular polarization radiation in the frequency band 10.47–11.69 GHz and has a peak gain of 8.1 dBic. There is a good matching between radiation and total efficiency in the operating band. The antenna can be put to use in weather mapping and detecting, long-range tracking radar and missile applications. The prototype has been fabricated and tested for experimental validation and the results are in good coherence with the simulated ones.

Numerical Investigation of Rotor and Stator Matching Mode on the Complex Flow Field and Pressure Pulsation of a Vaned Centrifugal Pump

The match of rotor and stator blades significantly affects the flow field structure and flow-induced pressure pulsation characteristics inside the pump. In order to study the effects of the rotor and stator matching mode on the complex flow field and pressure pulsation of a centrifugal pump with a vaned diffuser, this paper designs three different vaned diffusers (DY5, DY8 and DY9) and uses the DDES (Delayed Detached Eddy Simulation) numerical method combined with structured grids to simulate the unsteady flow phenomena of the model pump under rated conditions. The results show that, under different rotor and stator matching modes, the pressure pulsation spectrum is dominated by the blade passing frequency and its harmonics. The matching mode of the rotor and stator significantly affects the time–frequency domain characteristics of the pressure pulsation inside the pump, and it is observed that the pressure pulsation energy of vaned diffusers with more blades is significantly smaller than that of fewer-blade vaned diffusers in comparison to the energy of the pressure pulsation at the blade passing frequency and within the 10–1500 Hz frequency band. Combined with the distribution characteristics of the complex flow field inside the pump, it can be found that increasing the number of vaned diffuser blades can reduce the energy of flow-induced pressure pulsation, improve the distribution of high-energy vortices in the interaction zone and stabilize the flow inside the centrifugal pump effectively.

Recent Advances in Electromagnetic Metamaterials and Metasurfaces for Polarization Manipulation

Abstract Polarization is an important characteristic of electromagnetic waves that has been exploited in many areas of wave manipulations. While effective control of polarization is highly demanded in various applications, traditional polarization converters have drawbacks such as large volume, narrow operating frequency band, low efficiency, and high losses, hindering themselves from practical applications. Metamaterials and metasurfaces are recently developed artificially structured electromagnetic materials constructed by three- or two-dimensional arrays of meta-atoms with tailored electromagnetic responses, exhibit great potential in controlling the propagation of electromagnetic waves and are highly suitable for flexible control of polarization. Here, we review the recent developments in the field of electromagnetic metamaterials and metasurface for polarization manipulation, focusing on their operation principles and practical applications. We discussed the research progress of chiral metamaterials and anisotropic metasurfaces, and also summarized the achievements of metasurfaces for comprehensive manipulation polarization and phase in recent years. We further summarize the recent achievements on the diversified polarization manipulation functions of metasurfaces. Finally, we discuss reconfigurable metasurfaces that can dynamically control the polarizaiton and wavefronts of electromagnetic waves, including not only electrically reconfigurable metasurfaces with constitutional meta-atoms locally tuned by external stimuli, but also time-modulated metasurfaces exploiting the temporal dimension by applying dynamic switching of the coding sequences. Finally, we look forward to the possible future directions and existing challenges in this rapidly developing field.

Miniaturized Vivaldi antenna with multiband and high-gain for millimeter-wave applications

ABSTRACT A novel miniaturised quad-band printed Vivaldi antenna is proposed for millimetre-wave applications. It can be seen as a two-arm antenna where the antenna arms bound the tapered Vivaldi slot. The antenna arms are printed on the opposite sides of a flexible millimetre-wave substrate. Three periodic structures are added to the antenna geometry and printed in the area surrounding the radiating slot structure to improve the impedance matching over the antenna’s four operational frequency bands and enhance the gain. These periodic structures are parasitic ring array loaded to the antenna arms, ring-array reflector inserted between the antenna arms and the ground plane, and metamaterial director printed in front of the antenna arms. A prototype of the proposed antenna is fabricated for experimental assessment of the antenna performance. The experimental measurements show good agreement with the simulation results. The proposed antenna impedance is matched over the four frequency bands centred at 25 , 35 , 45 , and 55 GHz . The bandwidth of each operational band is about 5 GHz with percent bandwidths of 20 % , 15 % , 11 % , and 9 % , respectively. The corresponding values of the maximum gain are 7.5 , 10.5 , 12 , and 13 dBi , respectively. The radiation efficiency is maintained above 93 % over the entire frequency band (20–60 GHz).

Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation

IntroductionTranscranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain.MethodsMEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05).ResultsThe 8-min tPBM enabled significant increases in alpha (8–12 Hz) and beta (13–30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side.DiscussionMEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.

A Data Recovery Method for Extra-Long-Span Railway Bridge Health Monitoring Based on TVFEMD and CNN-GRU

Abstract Structure health monitoring (SHM) systems play a crucial role in understanding the condition of structures. However, owing to various uncertain factors, sensor data may be missing, which poses a great challenge to capture the real-time dynamic characteristics of the bridge. To address this problem, this paper proposes a model that integrates time varying filtering based empirical mode decomposition (TVFEMD), convolutional neural network (CNN), and gated recurrent unit (GRU) to forecast and fill in the missing data. The proposed model initially employs TVFEMD to decompose the signal into several intrinsic mode functions (IMFs) of different frequency bands. Subsequently, CNN is utilized to extract data features for each IMF, followed by prediction through GRU. The model linearly combines the prediction results obtained from each IMF to obtain the actual prediction result. Simulation data and measured data from the large railway bridge are utilized in this research to validate the model’s efficacy. The analysis results demonstrate a significant improvement in prediction performance compared to traditional models, showcasing strong generalization ability and robustness. In conclusion, the model proposed in this paper has a high utilization value in health monitoring data recovery.

Virtual Antenna Arrays with Frequency Diversity for Radar Systems in Fifth-Generation Flying Ad Hoc Networks

This paper proposes the design of virtual antenna arrays with frequency diversity for radar systems in fifth-generation flying ad hoc networks. These virtual arrays permit us to detect targets from the sky with flying drones. Each array element is composed of a microstrip antenna mounted on quadcopter drones and is virtually connected with the other elements. The antennas are tuned to work at the lower fifth-generation frequency band of 3.5 GHz. The design process considers the optimization of frequency offsets and positions for each element to obtain a side lobe level reduction. This methodology is carried out by particle swarm optimization. Several design examples are presented with random frequency offsets and non-uniform positions. These designs are compared to uniform-spaced arrays excited with Hamming frequency offsets. The simulation results show that using random frequency offsets and non-uniform positions provides a minor side lobe level reduction. This research demonstrates the feasibility of using virtual arrays for radar systems in fifth-generation flying ad hoc networks.

Enhancing touch sensibility with sensory electrical stimulation and sensory retraining

A large proportion of stroke survivors suffer from sensory loss, negatively impacting their independence, quality of life, and neurorehabilitation prognosis. Despite the high prevalence of somatosensory impairments, our understanding of somatosensory interventions such as sensory electrical stimulation (SES) in neurorehabilitation is limited. We aimed to study the effectiveness of SES combined with a sensory discrimination task in a well-controlled virtual environment in healthy participants, setting a foundation for its potential application in stroke rehabilitation. We employed electroencephalography (EEG) to gain a better understanding of the underlying neural mechanisms and dynamics associated with sensory training and SES. We conducted a single-session experiment with 26 healthy participants who explored a set of three visually identical virtual textures—haptically rendered by a robotic device and that differed in their spatial period—while physically guided by the robot to identify the odd texture. The experiment consisted of three phases: pre-intervention, intervention, and post-intervention. Half the participants received subthreshold whole-hand SES during the intervention, while the other half received sham stimulation. We evaluated changes in task performance—assessed by the probability of correct responses—before and after intervention and between groups. We also evaluated differences in the exploration behavior, e.g., scanning speed. EEG was employed to examine the effects of the intervention on brain activity, particularly in the alpha frequency band (8–13 Hz) associated with sensory processing. We found that participants in the SES group improved their task performance after intervention and their scanning speed during and after intervention, while the sham group did not improve their task performance. However, the differences in task performance improvements between groups only approached significance. Furthermore, we found that alpha power was sensitive to the effects of SES; participants in the stimulation group exhibited enhanced brain signals associated with improved touch sensitivity likely due to the effects of SES on the central nervous system, while the increase in alpha power for the sham group was less pronounced. Our findings suggest that SES enhances texture discrimination after training and has a positive effect on sensory-related brain areas. Further research involving brain-injured patients is needed to confirm the potential benefit of our solution in neurorehabilitation.

Frequency-extended inverse design of transmission-type linear-to-circular polarization control metasurface based on deep learning

Due to the parameter range limitations of the training dataset, traditional inverse prediction network models can only predict structure parameters of the metasurface within a limited frequency range. When the given design targets exceed the prediction range of network models, the predicted results will not match the actual results. This paper proposes a frequency-extended inverse design method (FEIDM) based on deep learning to address the problem. The method can automatically collect the required data and train the network model based on the center working frequency of the design targets, thereby achieving accurate prediction of metasurface structural parameters and effectively reducing labor and computational costs. Taking the transmission-type linear-to-circular polarization control metasurface as an example, the unit cell of the metasurface is first established in the paper. The structural parameters and corresponding electromagnetic parameters are collected without changing the unit size of the metasurface, and an initial inverse prediction network model (IIPNM) is constructed. The research results indicate that its predictable center working frequency range is 3–5.5 GHz. Using the design concept proposed in this paper, a program is constructed, it can automatically achieve data collection, target extraction, network model training, and prediction. Four given design targets are predicted. Among them, the center working frequencies of the three design targets are outside the initial predictable range. The predicted results meet the requirements of the given target, verifying the effectiveness of the proposed scheme. Finally, a set of parameters is selected to fabricate, and the experimental results are consistent with the simulation results. The research results can provide a reference for the efficient prediction of metasurface structural parameters over a wide frequency band.