Wireless Systems Research Articles

Antagonistic strategy for enhanced performance polyimide-based triboelectric nanogenerators and wireless self-powered sensors in extremely harsh environments

Triboelectric nanogenerators (TENGs) offer promising green energy solutions for portable microelectronics in the Internet of Everything era. However, their practical applications are limited by low electrical output and stability in harsh environments. This study introduces an innovative antagonistic strategy to enhance TENG performance and stability using thermo-stable polyimide with customizable porous structures (ip-PI). By employing antagonistic solubility, we create ip-PI using chloroform as a solvent for PI and acetone as a solvent for the Poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) template, whereas they both act as nonsolvents for their respective counterparts. Additionally, microbeads-patterned chitosan (mb-CS) is rationally designed and fabricated as morphologically and electrically antagonistic counter surfaces for ip-PI. The resulting antagonist-inspired TENG (AI-TENG) constructed from ip-PI and mb-CS achieves a remarkable average power density of 4 W·m−2, presenting an outstanding 200-fold increase in power compared to TENG made from unstructured flat surfaces. Furthermore, the ip-PI demonstrates excellent temperature resistance, enabling the TENG to operate at extremely high temperatures up to 250 °C, with promising durability of over 10,000 contact-separation cycles. Applications include self-powered machinery condition monitoring sensors and a wireless communication fire forest pre-warning system, showcasing significant advancements in flexible, high-performance TENGs suitable for industrial use in extreme environments.

Optimizing energy harvesting with diversity in cooperative simultaneous wireless information and power transfer systems

Optimizing energy harvesting with diversity in cooperative simultaneous wireless information and power transfer systems

Deep Learning-Based Hybrid Precoding Approach in the Massive Multiple-Input Multiple-Output System

Precoding is a critical signal processing technique used in wireless communication systems to enhance transmission performance. This paper initially provides a brief overview of various conventional precoding algorithms. The exploration includes various nonlinear precoding algorithms which outperform linear techniques in high signal-to-noise ratio (SNR) scenarios. Moreover, the paper delves into practical considerations and provides insights into selecting the most suitable technique for specific communication scenarios. The deep learning-based hybrid precoder is designed using the MDL-AltMin algorithm and simulated results show a spectral efficiency of (SE) 40.96 dB compared with different precoding algorithms. The precoder model is modified with a Hybrid Precoding Net algorithm with a spectral efficiency of 21.07 dB for high values of SNR such as −30 and again compared with deep learning precoders. The HPNet model is proposed with a spectral efficiency of 23.04 dB with and without CSI (Channel State Information) at the transmitter. Furthermore, the HPNet model is compared with optimal digital precoders.

Portable multi-focal visual evoked potential diagnostics for multiple sclerosis/optic neuritis patients

PurposeMultiple sclerosis (MS) is a neuro-inflammatory disease affecting the central nervous system (CNS), where the immune system targets and damages the protective myelin sheath surrounding nerve fibers, inhibiting axonal signal transmission. Demyelinating optic neuritis (ON), a common MS symptom, involves optic nerve damage. We’ve developed NeuroVEP, a portable, wireless diagnostic system that delivers visual stimuli through a smartphone in a headset and measures evoked potentials at the visual cortex from the scalp using custom electroencephalography electrodes.MethodsSubject vision is evaluated using a short 2.5-min full-field visual evoked potentials (ffVEP) test, followed by a 12.5-min multifocal VEP (mfVEP) test. The ffVEP evaluates the integrity of the visual pathway by analyzing the P100 component from each eye, while the mfVEP evaluates 36 individual regions of the visual field for abnormalities. Extensive signal processing, feature extraction methods, and machine learning algorithms were explored for analyzing the mfVEPs. Key metrics from patients’ ffVEP results were statistically evaluated against data collected from a group of subjects with normal vision. Custom visual stimuli with simulated defects were used to validate the mfVEP results which yielded 91% accuracy of classification.Results20 subjects, 10 controls and 10 with MS and/or ON were tested with the NeuroVEP device and a standard-of-care (SOC) VEP testing device which delivers only ffVEP stimuli. In 91% of the cases, the ffVEP results agreed between NeuroVEP and SOC device. Where available, the NeuroVEP mfVEP results were in good agreement with Humphrey Automated Perimetry visual field analysis. The lesion locations deduced from the mfVEP data were consistent with Magnetic Resonance Imaging and Optical Coherence Tomography findings.ConclusionThis pilot study indicates that NeuroVEP has the potential to be a reliable, portable, and objective diagnostic device for electrophysiology and visual field analysis for neuro-visual disorders.

Initial Study of the Onsite Measurement of Flow Sensors on Turbine Blades (SOTB)

This paper presents a new framework using MEMS flow sensors on turbine blades (SOTB) to investigate unsteady flow features of a rotating wind turbine. Self-heating flow sensors were implemented by the U18 complementary metal-oxide semiconductor (CMOS) MEMS foundry provided by Taiwan Semiconductor Research Institute (TSRI). Flow sensor chips with a size of 1.5 mm × 1.5 mm were parylene-coated, output via a wireless data acquisition system (WDAQ), and mounted at the root, middle and tip of a 1.2 m diameter semi-rigid turbine blade of a 400 W horizontal axis wind turbine (HAWT). The instantaneous angles of attack (AOAs) of the SOTB were found to be 46~62°, much higher than the general stall AOA of 15°, but were accurate considering the normal detection of the flow sensors. The computational fluid dynamics (CFD) simulation of the HAWT was also compared with the SOTB output. The onsite measurement herein revealed that the 3D secondary flow increment, mostly obvious near the middle part of the turbine blades, degraded both the sensor and the turbine performance and initially justified the onsite measurement application.

High‐Performance Textile‐Based Capacitive Strain Sensors via Enhanced Vapor Phase Polymerization of Pyrrole and Their Application to Machine Learning‐Assisted Hand Gesture Recognition

Sensors based on everyday textiles are extremely promising for wearable applications. The present work focuses on high‐performance textile‐based capacitive strain sensors. Specifically, a conductive textile is obtained via vapor‐phase polymerization of pyrrole, in which the usage of methanol co‐vapor and the addition of imidazole to the iron chloride oxidant solution are shown to maximize conductivity. A technique to provide insulation and mechanical resistance using thermoplastic polyurethane and polystyrene‐block‐polyisoprene‐block‐polystyrene/barium titanate composite is developed. Such insulated conductive elastics are then used to fabricate highly sensitive twisted yarn capacitive sensors. A textile glove is subsequently embedded with such sensors. The wireless measurement and transmission system demonstrate efficacy in capturing capacitance variations upon strain and monitoring hand motions. A machine learning model to recognize 12 gestures is implemented—100% classification accuracy is obtained.

Deep Learning-Based Hybrid Precoding Approach in the Massive Multiple-Input Multiple-Output System

Precoding is a critical signal processing technique used in wireless communication systems to enhance transmission performance. This paper initially provides a brief overview of various conventional precoding algorithms. The exploration includes various nonlinear precoding algorithms which outperform linear techniques in high signal-to-noise ratio (SNR) scenarios. Moreover, the paper delves into practical considerations and provides insights into selecting the most suitable technique for specific communication scenarios. The deep learning-based hybrid precoder is designed using the MDL-AltMin algorithm and simulated results show a spectral efficiency of (SE) 40.96 dB compared with different precoding algorithms. The precoder model is modified with a Hybrid Precoding Net algorithm with a spectral efficiency of 21.07 dB for high values of SNR such as −30 and again compared with deep learning precoders. The HPNet model is proposed with a spectral efficiency of 23.04 dB with and without CSI (Channel State Information) at the transmitter. Furthermore, the HPNet model is compared with optimal digital precoders.

Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Abstract. Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the abovementioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

Testing Time Optimization Method for IEEE 802.15.4z Ultra-wideband Integrated Circuits

IEEE 802.15.4z-compliant ultra-wideband (UWB) devices are becoming ever more popular in contemporary radio engineering systems. Such systems are capable of precisely measuring distances (with their accuracy expressed in centimeters), are immune to interference, offer low latency and transmit data in an energy-efficient manner. Widespread adoption of UWB technology has triggered significant demand for testing integrated circuits these systems rely on, prompting the development of new testing methods to meet the ever increasing requirements in terms of testing speed and reliability. The same applies to sensitivity tests, in the course of which up to 2000 different packets may be received. The process of generating and analyzing such a large number of packets is time consuming. Furthermore, if multiple devices need to be tested simultaneously, the duration of the test will be multiplied accordingly. In such a context, the article investigates the lead time required to generate 2000 UWB packets using conventional methods and proposes a novel approach to significantly reduce packet generation time and improve testing efficiency.

Frequency reconfigurable microstrip patch antenna for multiband applications

Wireless communication technology is well-established, and several antennas have been developed and produced specifically for this purpose. However, antenna performance and communication system development need to be enhanced in order to adapt to the present era. The performance of the antenna is significantly influenced by its design. Thus, this work produced a novel wideband antenna design via the use of a frequency reconfigurable approach. In the recommended study, microstrip patch antennas (MPAs) were used in wideband applications to switch frequencies using shunt-series microelectromechanical systems (MEMS). The suggested antenna, which has two switches built into it, is tested in ON-ON, OFF-ON, and OFF-OFF switching scenarios. Radiation pattern, voltage standing wave ratio (VSWR), gain, bandwidth, and return loss are among the antenna performance metrics used to assess the suggested antenna's performance in each switching situation. The simulation findings suggest that the optimal antenna design for usage in wireless communication systems is one that works well with a shunt-series MEMS switch.

Digital Notice Board using Bluetooth and Arduino

In this project, Bluetooth and Arduino microcontrollers are used to build and operate a wireless noticeboard system. To disseminate real-time information across many contexts, a cutting-edge, interactive platform is now being developed. On conventional noticeboards, there are just physical notes and human modifications, both of which can be tedious and time-consuming. This solution makes use of Bluetooth connectivity and the adaptability of Arduino to let users send messages wirelessly from their cell phones or laptops. The Bluetooth-enabled devices used in the wireless noticeboard system allow users to enter messages. An Arduino microcontroller with a Bluetooth module collects the messages, processes them, and displays the results on a display device. Users can rapidly post messages to the noticeboard from their mobile devices using Bluetooth technology without having to engage with it physically. The system's core processing unit, the Arduino microcontroller, which also activates the display unit, receives and processes incoming messages before displaying them.

Efficient high‐fidelity deep convolutional generative adversarial network model for received signal strength reconstruction in indoor environments

AbstractWith the rapid development of wireless communication systems, particularly in the era of 5G and the Internet of Things, deploying wireless communication networks in indoor environments has become crucial. Indoor infrastructure deployment necessitates innovative approaches for efficiently and accurately obtaining received signal strength (RSS) maps. However, traditional methods for acquiring RSS maps, such as empirical and deterministic models, are limited by significant inaccuracies and high computational demands. Empirical models often fail to capture the complex dynamics of indoor environments, resulting in deviations from actual signal behaviours. On the other hand, deterministic models, while more accurate, are computationally intensive due to their reliance on detailed physical modelling of wave propagation. This study introduces a machine learning approach based on deep convolutional generative adversarial networks (DCGAN) aimed at reconstructing indoor RSS maps with minimal RSS measurements. By leveraging DCGAN's generative and adversarial training capabilities, the method not only surpasses traditional interpolation methods in efficiency and precision but also offers new possibilities for the rapid deployment and optimization of wireless communication systems in indoor environments.

Wireless charging system design based on ICPT topology

Wireless charging system design based on ICPT topology

Wireless Charging System With Dual Switchable Constant Voltage and Constant Current Outputs Based on Intermediate Coils

Wireless Charging System With Dual Switchable Constant Voltage and Constant Current Outputs Based on Intermediate Coils

Model-Free Composite Disturbance Rejection Control for Dynamic Wireless Charging System Based on Online Parameter Identification

Model-Free Composite Disturbance Rejection Control for Dynamic Wireless Charging System Based on Online Parameter Identification

Research on Maximum Power Point Tracking Control in Omnidirectional Wireless Power Transfer System

Research on Maximum Power Point Tracking Control in Omnidirectional Wireless Power Transfer System

Performance analysis of microstrip patch antenna for wireless communication systems

<p>An antenna may be thought of as a temporary tool that directs radio waves for transmission or reception. Aside from being inexpensive, small, easy to manufacture, and compatible with integrated electronics, the microstrip patch antenna (MPA) offers several other benefits as well. These two methods are often seen as low-cost, adaptable, dependable, high-speed data connection choices that promote user mobility. An overview of how MPA have been used throughout the last several decades is provided in this article. It has been suggested that there are many approaches to enhance the performance of MPA, including the use of composite antennas, highly integrated antenna/array and feeding networks, operating at relatively high frequencies, and using cutting-edge manufacturing methods. Dual or multiband antennas are essential for meeting the demands of wireless services in this rapidly evolving wireless communication environment. Here is an overview of the patch antenna literature for wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) applications.</p>

An I/Q Phase Detection-Based Harmonic- Insensitive Phase Synchronization Method for Bidirectional Wireless Power Transfer System

An I/Q Phase Detection-Based Harmonic- Insensitive Phase Synchronization Method for Bidirectional Wireless Power Transfer System

The Impact of Rectifier Filter Capacitance on Buck Converter Output Voltage in Wireless Power Receiver System With Input Current Source

The Impact of Rectifier Filter Capacitance on Buck Converter Output Voltage in Wireless Power Receiver System With Input Current Source

A shared-link type wireless power and data simultaneous transfer system based on a series–parallel resonant network

Wireless Power Transmission (WPT) is widely used. In practical engineering applications, the transmitter and receiver of a stable and reliable WPT system need to establish not only a power transmission channel but also a data transmission channel to realize closed-loop control and information interaction. In this paper, a novel simultaneous wireless power and data transfer system based on a series–parallel (SP) resonant network is proposed. The system integrates an SP higher-order resonant network with series carrier injection, which makes power transmission and data transmission share a magnetic coupling channel. The isolation between power and data is realized by exploiting the frequency characteristics of the compensation network, thus realizing efficient power transmission and data transmission. In this paper, accurate and detailed mathematical modeling of the system is conducted, and the gain characteristics of the power transmission channel and the data transmission channel are demonstrated. Meanwhile, the mutual interference between the two channels is analyzed, and a feasible and effective parameter design method is developed. Finally, an experimental prototype with an output power of 16 W and a backward data rate of 100 Kbps is constructed to verify the feasibility of the proposed system and the correctness of the parameter design.