Wireless Transmission Research Articles

High-performance waterproof flexible thermoelectric generators for self-powered electronics

Flexible and wearable thermoelectric generators (TEG) have emerged as promising energy sources for wearable health-monitoring devices. However, common thermoelectric generators are difficult to be applied to a wide range of application scenarios due to their poor durability, low output power, and susceptibility to human sweat or underwater environments. Here, we propose a waterproof wearable TEG with a gap structure. Through structural optimization and full-coverage elastomer encapsulation, the wearable TEG has a maximum power density of 4.38 mW∙cm−2 at a temperature difference (ΔT) of 30 K and exhibits good stability under aqueous environments, which is capable of supplying power to electronic devices even under submerged conditions. The internal resistance of wearable TEG changes by less than 10 % at 50 % stretch or 900 degrees of torsion, showing good flexibility and mechanical stability. Based on this, we designed an energy harvesting and management system to help wearable TEG collect and utilize energy on demand, and successfully implemented wireless transmission of human skin temperature data for underwater environments and real-time electrocardiograms (ECG) tests for health detection in air environments. This research provides a reliable method for powering wearable electronic devices using thermoelectric generators.

Synergetic enhancement of moisture-electric generation through interfacial evaporation and active electrode

Ion migration-based moisture-electric generator holds the open-circuit voltage to power portable electronics, the Internet of Things, and wireless transmission. However, most devices still encounter challenges with the attainment of high-density power generation in continuous mode. Here, we introduce a sustainable and high-power density ion-selective bipolar moisture-electric generator that relies on Au-Al electrodes, capillary water supply, and interfacial evaporation. The device generates electricity by exploiting the salinity gradient between the capillary waterways in the photothermal and waste heat layers. This process is synergized by electrochemical reactions of the electrodes, which propel the migration of cations and anions through ion-selective bipolar hydrogels toward the intermediate waterway. It demonstrates a short-circuit current density of 52.2 A m−2 and a power density of up to 33.8 W m−2 over 0.5 cm × 0.5 cm electrodes. Connecting 13 devices in series in darkness successfully illuminates an LED lamp with a rated power of 1 W together with an operating voltage of 2.0–2.8 V. This work offers an off-grid, environmentally friendly, and affordable solution for high-density moisture power generation.

Resource optimization of multi-UAV assisted communication system based on user scheduling

In order to improve the transmission rate of the multi-user mobile communication downlink wireless transmission system, a resource optimization method for multi-unmanned aerial vehicle (UAV) assisted communication system based on user scheduling and trajectory optimization is proposed. The proposed method establishes an optimization problem with the maximization of the total multi-user throughput as the criterion under the constraints of user scheduling, total energy consumption of UAVs and user service quality requirements. In order to solve this non-convex problem, the original non-convex problem is decomposed into three easy-to-handle non-convex sub-problems by using the block coordinate descent method (BCD). The sub-problems are transformed and solved by introducing slack variables, first-order Taylor expressions, continuous convex approximation (SCA) and other methods, and then alternately iteratively optimized to obtain an approximate suboptimal solution to the original non-convex problem. Simulation results show that the proposed algorithm can effectively improve the total system throughput and has good convergence in both single and multi-UAV communication systems.

A Rapid Adaptation Approach for Dynamic Air-Writing Recognition Using Wearable Wristbands with Self-Supervised Contrastive Learning

HighlightsUtilizing self-supervised learning, the proposed wearable wristband with a four-channel sensing array and wireless transmission module is developed for tracking air-writing and dynamic gestures.The model can learn prior features from unlabeled signals of random wrist movements, significantly reducing the dependency on extensive labeled data for training.The wristband system rapidly adapts to multiple scenarios after fine-tuning using few-shot data, enhancing user interaction through natural and intuitive communication.

5G network performance using novel MIMO mixed FSO/MMW communication systems under pointing errors effect: test analysis using image transmission

Abstract Millimeter waves (MMW) enable high data rates over short distances; free-space optical (FSO) provides high-capacity optical wireless transmissions; and multiple-input multiple-output (MIMO) maximizes antenna utilization. These are the three leading technologies that work harmoniously to deliver 5G’s superior performance. This collaborative effort results in 5G’s ability to offer high connection capacities, low latency, and rapid speeds, creating new opportunities for industrial and internet of things applications. In this paper, the proposed system combines FSO links and MMW radio frequency (RF) links to enhance the performance of mixed FSO/RF systems. FSO experiences turbulence and pointing errors (PE), while MMW undergoes fading. Using both FSO and MMW provides diversity against channel fading. Furthermore, both the FSO and MMW links utilize MIMO technology to combat fading through spatial diversity. The FSO link is modeled with a Gamma-Gamma Turbulence model and PE. The MMW link is modeled with Rayleigh fading. By combining these two types of links with MIMO, the system can achieve improved performance compared to using either FSO or MMW alone. The dual nature of the system provides robustness against different types of channels fading effects. Overall, the goal is to enhance performance by capitalizing on the complementary channel characteristics of optical and RF links and exploiting MIMO’s spatial diversity benefits. In the present work, closed-form formulas accounting for the influence of PE are generated for the bit error rate (BER). This article also explores the MIMO mixed FSO/MMW system with multiple modulation techniques under various turbulence situations. The suggested system is ultimately verified by transmitting images with suitable fixed BER.

RFID Occupied Advanced Framework for Specialized Vehicle Access, Operating System, and Wireless Data Transmission Without Human Intervention

RFID tags are tiny electronic devices that include a distinctive code that can be detected by a reader that supports RFID. The string of characters is used for recognizing and monitoring the object to which the tag is connected. RFID tags interact with RFID readers using radio frequency. While the tag comes into close proximity to the scanner, that device sends a radio signal that triggers the tag. The tag then responds by sending its unique identity. RFID pinpointing ability is verified experimentally in two different techniques, one utilizing radar and the other a photosensitive transition. The initial phase is intended to test if the continuously changing location provided from RFID tags equals the precise position recorded by sonar. It is also excellent for getting into parking lots, private spaces, professional parking spots, and offices quickly and easily. The implementation of RFID will bring a revolutionary transformation in the authorization, administration, correspondence, computerization, and security systems for specialized vehicle Access, Operating System, and Wireless Data Transmission without Human Intervention using an internet based wireless communication system. RFID vehicular registration is an authentication system which employs RFID readers to give authorization for automobiles. The technique normally consists of installing a reader with RFID technology at the entrance/exit entrance to an enclosed or a limited region. RFID scanning can deliver efficient techniques for transportation administration, making the process straightforward, dependable, as well as secure.

Effect of cell structures on electrical degradation of GaAs laser power convertors after 1 MeV electron irradiation and structure-optimization for improving radiation resistance

Laser wireless power transfer (LWPT) technology holds significant promise for wireless power transmission in space, necessitating that high-efficiency GaAs laser power convertors (LPCs) have strong tolerance to high-energy particle radiation. Therefore, the degradation characteristics of GaAs LPCs with different architectures under 1 MeV electron irradiation were investigated. Experimental and simulation results demonstrate that LPCs with thicker bottom cells suffer from significantly more electrical degradation. The degradation is primarily due to a reduction in electron concentrations in the base of the bottom cells, which is considerably less pronounced as the thickness of the bottom cells decreases. Based on these analyses, thinning the thickness and optimizing the doping profile for the bottom cells are proposed to improve the radiation resistance of the LPCs. Simulations show that the electrical degradation of the optimized four-junction LPCs is notably less than that of the original four-junction LPCs under the same irradiation conditions, indicating that the proposed strategies effectively enhance the radiation resistance of the LPCs.

Identifying Tampered Radio-Frequency Transmissions in LoRa Networks Using Machine Learning.

Long-range networks, renowned for their long-range, low-power communication capabilities, form the backbone of many Internet of Things systems, enabling efficient and reliable data transmission. However, detecting tampered frequency signals poses a considerable challenge due to the vulnerability of LoRa devices to radio-frequency interference and signal manipulation, which can undermine both data integrity and security. This paper presents an innovative method for identifying tampered radio frequency transmissions by employing five sophisticated anomaly detection algorithms-Local Outlier Factor, Isolation Forest, Variational Autoencoder, traditional Autoencoder, and Principal Component Analysis within the framework of a LoRa-based Internet of Things network structure. The novelty of this work lies in applying image-based tampered frequency techniques with these algorithms, offering a new perspective on securing LoRa transmissions. We generated a dataset of over 26,000 images derived from real-world experiments with both normal and manipulated frequency signals by splitting video recordings of LoRa transmissions into frames to thoroughly assess the performance of each algorithm. Our results demonstrate that Local Outlier Factor achieved the highest accuracy of 97.78%, followed by Variational Autoencoder, traditional Autoencoder and Principal Component Analysis at 97.27%, and Isolation Forest at 84.49%. These findings highlight the effectiveness of these methods in detecting tampered frequencies, underscoring their potential for enhancing the reliability and security of LoRa networks.

Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis.

Nowadays, the mHealth market is flooded with smartphone applications (apps) lacking validation for blood pressure (BP)-lowering effects and BP measurement accuracy. This systematic review for Guidelines for BP control using digital technologies of the Japanese Society of Hypertension aimed to assess the validation studies of apps. We searched eligible studies in Ovid MEDLINE, Cochrane Library, and Ichushi, focusing on randomized controlled trials and observational studies comparing the effects of smartphone app-based interventions with non-digital healthcare. Random effects models of meta-analysis were employed to estimate the pooled effects of mean BP change and 95% confidence intervals (CIs). Out of 7385 studies screened, 76 studies with 46,459 participants were included. The interventions were significantly associated with a reduction in office systolic and diastolic BP at six months (systolic BP, -2.76 mmHg, 95% CI: -3.94 to -1.58; diastolic BP, -1.23 mmHg, -1.80 to -0.67). Normotensives saw a significant reduction in office systolic BP at three-month (-4.44 mmHg, -6.96 to -1.92), diminishing afterward (six-month, 0.86 mmHg, -2.81 to 4.52; twelve-month, 0.86 mmHg, -2.81 to 4.52). Conversely, hypertensive participants experienced a significant reduction in office systolic BP at both three- and six-month (three-month, -7.71 mmHg, -10.63 to -4.79; six-month, -1.88 mmHg, -3.41 to -0.35), albeit with limited evidence thereafter. A larger BP reduction was observed among participants using apps with wireless transmission of BP measurements (P = 0.047 for interaction), while there was no clear difference in BP reduction according to the presence of other functions. Smartphone app-based interventions may hold the potential to improve BP levels.

Summary of Wireless Charging Technology for Electric Vehicles

The rapid popularity of electric vehicles has promoted the rapid development of wireless charging technology. This paper reviews the current research progress and application status of wireless charging technology for electric vehicles. Inductive coupling, magnetic resonance coupling and non-directional radiofrequency radiation, three main wireless power transmission methods, including their principles and advantages, are introduced. In addition, the practical application of the technique, such as near field application and far field application, is also discussed. Finally, the development direction of wireless charging technology for electric vehicles in the future is looked forward, including the key technical paths of optimizing system design, improving energy transmission efficiency and reducing system cost. In summary, this paper aims to provide comprehensive theoretical support and practical guidance for the research and practice of wireless charging technology for electric vehicles.

Performance Analysis and Prediction of 5G Round-Trip Time Based on the VMD-LSTM Method

With the increasing level of industrial informatization, massive industrial data require real-time and high-fidelity wireless transmission. Although some industrial wireless network protocols have been designed over the last few decades, most of them have limited coverage and narrow bandwidth. They cannot always ensure the certainty of information transmission, making it especially difficult to meet the requirements of low latency in industrial manufacturing fields. The 5G technology is characterized by a high transmission rate and low latency; therefore, it has good prospects in industrial applications. To apply 5G technology to factory environments with low latency requirements for data transmission, in this study, we analyze the statistical performance of the round-trip time (RTT) in a 5G-R15 communication system. The results indicate that the average value of 5G RTT is about 11 ms, which is less than the 25 ms of WIA-FA. We then consider 5G RTT data as a group of time series, utilizing the augmented Dickey–Fuller (ADF) test method to analyze the stability of the RTT data. We conclude that the RTT data are non-stationary. Therefore, firstly, the original 5G RTT series are subjected to first-order differencing to obtain differential sequences with stronger stationarity. Then, a time series analysis-based variational mode decomposition–long short-term memory (VMD-LSTM) method is proposed to separately predict each differential sequence. Finally, the predicted results are subjected to inverse difference to obtain the predicted value of 5G RTT, and a predictive error of 4.481% indicates that the method performs better than LSTM and other methods. The prediction results could be used to evaluate network performance based on business requirements, reduce the impact of instruction packet loss, and improve the robustness of control algorithms. The proposed early warning accuracy metrics for control issues can also be used to indicate when to retrain the model and to indicate the setting of the control cycle. The field of industrial control, especially in the manufacturing industry, which requires low latency, will benefit from this analysis. It should be noted that the above analysis and prediction methods are also applicable to the R16 and R17 versions.

Application and Research of Intelligent Multi-source Information Fusion Technology in Firefighting Equipment

As modern firefighting environments become increasingly complex, traditional firefighter equipment and operational methods are no longer adequate to address the high-risk challenges of fire rescue operations. Fire scenes are characterized by complex and hazardous environmental factors, with firefighters facing multiple threats such as extreme temperatures, dense smoke, and toxic gases. Therefore, ensuring the safety and efficiency of firefighters is of paramount importance. This study integrates multiple sensor technologies to enable real-time monitoring of firefighters' physiological status, posture changes, and fire scene conditions. The system incorporates ErgoLAB wireless ECG and PPG sensors, the BWT61CL posture sensor, and the MAG14mini infrared camera, which are capable of simultaneously capturing key physiological data and heat distribution in the fire scene. To ensure data accuracy and real-time performance, the study employs efficient signal preprocessing techniques, including noise reduction, baseline correction, and time synchronization. In addition, wireless transmission technology and multimodal data fusion algorithms are utilized to comprehensively analyze the firefighters' status and fire scene conditions. This approach significantly enhances the precision of firefighter safety monitoring and operational efficiency, demonstrating substantial innovation and practical value.

Enhanced Performance Analysis of 120 Gbps Single‐Channel IQ Modulation Based PDM‐FSO Transmission System Using 64‐QAM Signals

ABSTRACTThe ever‐augmenting demand of data channel‐bandwidth by the end users has resulted in the exploration of new transmission techniques for wireless transmission networks. In this work, we have demonstrated the modeling of a single‐channel free space optics (FSO) transmission system by employing polarization‐division‐multiplexing (PDM) technique. Further, in‐phase‐quadrature modulation (IQM) has been used to increase the transmission efficiency of the system. To decrease the baud‐rate of the system, we have proposed the use of 64‐level quadrature amplitude modulation (QAM) signals. The net transmission rate of the system is 120 Gbps with a baud‐rate of 10 Gbps. Furthermore, the overcome the signal degradation of the 120 Gbps signal propagating through atmospheric channel, we have reported the use of advanced digital signal processing (DSP) algorithms. The system's performance is investigated for adverse external climate weather conditions and the results reported show reliable 120 Gbps data transmission along range between 870 m and 16.25 km with good performance of BER and EVM 7.5%.

Stretchable wireless optoelectronic synergistic patches for effective wound healing

Physiotherapies play a crucial role in noninvasive tissue engineering for wound healing. However, challenges such as the implementation of complex interventions and unsatisfactory treatment outcomes impede widespread application. Here, we proposed a stretchable and wirelessly-powered optoelectronic synergistic patch with a dual-layer serpentine wireless receiver circuit to drive the optoelectronic modulation component. Optimized structure and impedance matching enable the patch to seamlessly attach to irregular skin surfaces and operate robustly over a 30% tensile strain range. Based on Sprague-Dawley rat wound model. The wound closure rate of the optoelectronic synergistic group significantly outperformed both monointervention and blank control groups. Mechanistically, optoelectronic synergistic intervention enhances the secretion of vascular endothelial marker proteins and growth factors, and stabilizes mitochondrial function during oxidative stress. Overall, the scalable amalgamation of flexible electronics, wireless transmission, and synergistic interventions promise to improve wound care.

Measurement Campaign of Radio Frequency Interference in a Portion of the C-Band (4-5.8 GHz) for the Sardinia Radio Telescope.

Radio frequency interference (RFI) analysis is crucial for ensuring the proper functioning of a radio telescope and the quality of astronomical observations, as human-generated interference can compromise scientific data collection. The aim of this study is to present the results of an RFI measurement campaign in the frequency range of 4-5.8 GHz, a portion of the well-known C-band, for the Sardinia Radio Telescope (SRT), conducted in October-November 2023. In fact, this Italian telescope, managed by the Astronomical Observatory of Cagliari (OAC), a branch of the Italian National Institute for Astrophysics (INAF), was recently equipped with a new C-band receiver that operates from 4.2 GHz to 5.6 GHz. The measurements were carried out at three strategically chosen locations around the telescope using the INAF mobile laboratory, providing comprehensive coverage of all possible antenna pointing directions. The results revealed several sources of RFI, including emissions from radar, terrestrial and satellite communications, and wireless transmissions. Characterizing these sources and assessing their frequency band occupation are essential for understanding the impact of RFI on scientific observations. This work provides a significant contribution to astronomers who will use the SRT for scientific observations, offering a suggestion for the development of mitigation strategies and safeguarding the radio astronomical environment for future observational campaigns.

Intelligent-Reflecting-Surface-Assisted Single-Input Single-Output Secure Transmission: A Joint Multiplicative Perturbation and Constructive Reflection Perspective.

Due to the inherent broadcasting nature and openness of wireless transmission channels, wireless communication systems are vulnerable to the eavesdropping of malicious attackers and usually encounter undesirable situations of information leakage. The problem may be more serious when a passive eavesdropping device is directly connected to the transmitter of a single-input single-output (SISO) system. To deal with this urgent situation, a novel IRS-assisted physical-layer secure transmission scheme based on joint transmitter perturbation and IRS reflection (JPR) is proposed, such that the secrecy of wireless SISO systems can be comprehensively guaranteed regardless of whether the reflection-based jamming from the IRS to the eavesdropper is blocked or not. Moreover, to develop a trade-off between the achievable performance and implementation complexity, we propose both element-wise and group-wise reflected perturbation alignment (ERPA/GRPA)-based IRS reflection strategies, respectively. In order to evaluate the achievable performance, we analyze the ergodic secrecy rate (ESR) and secrecy outage probability (SOP) of the SISO secure systems with the ERPA/GRPA-based JPRs, respectively. Finally, by characterizing the simulated and numerical ESR and SOP performance results, our proposed scheme is compared with the benchmark scheme of random phase-based reflection, which strongly demonstrates the effectiveness of our proposed scheme.

Wave Propagation Models for Optimization in Wireless Communication

To understand and build radio transmission systems, you need to know how waves travel. These models show how electromagnetic waves move through different settings, considering things like distance, obstacles, and the material the waves move through. A lot of what makes radio transmission work is being able to correctly guess how waves will spread in different situations. Wave propagation models come in many forms, such as open space, ground reflection (two-ray), and more complicated models such as the Hata, Okumura, and Rayleigh models. Each model is used for a different thing. For example, free space models are good at showing simple line-of-sight (LOS) situations, while empirical models like Hata are better at showing more complicated urban and residential settings. For example, the free space model believes that there are no hurdles between the sender and listener. This makes it perfect for situations like open fields or satellite communications. The Hata and Okumura models, on the other hand, are made for cities and suburbs, taking into account how buildings and geography affect signal power. Rayleigh and Rician models are scientific and are often used to describe situations where multipath transmission happens, like in crowded cities where signals bounce off many objects. These models help us understand things like fading, where the signal strength changes because of interference from different routes. Wave propagation models are important for making sure that wireless communication systems work well, whether they are simple field sets or complicated networks in cities. They help experts guess how signals will behave, find the best places to put antennas, and make the whole network work better. These models make sure that communication systems can stay connected and provide high-quality service in a wide range of settings by considering different transmission scenarios.

A survey of integrating wireless technology into active noise control

Active Noise Control (ANC) is a widely adopted technology for reducing environmental noise across various scenarios. This paper focuses on enhancing noise reduction performance, particularly through the refinement of signal quality fed into ANC systems. We discuss the main wireless technique integrated into the ANC system equipped with some innovative algorithms in diverse environments. Instead of using microphone arrays, which increase the computation complexity of the ANC system, to isolate multiple noise sources to improve noise reduction performance, the application of the wireless technique avoids extra computation demand. Wireless transmissions of reference, error, and control signals are also applied to improve the convergence performance of the ANC system. Furthermore, this paper lists some wireless ANC applications, such as earbuds, headphones, windows, and headrests, underscoring their adaptability and efficiency in various settings.

Optimization of Coreless PCB Coils Based on a Modified Taguchi Tuning Method for WPT of Pedelec

The printed circuit board (PCB) winding coil offers advantages such as small size, high precision, high repeatability, and low cost, making it conducive to the miniaturization of electronic equipment and a popular choice in wireless power transmission systems. This paper aims to clarify the correlation between induction parameters and inductive capabilities using the orthogonal array of the modified Taguchi method for Pedelec applications. The conventional Taguchi method typically achieves only local optimization; however, this paper considers practical application conditions and combines experimental data to establish the initial values of the orthogonal array, thereby achieving global optimization. Additionally, the tuning process of the Taguchi method replaces physical experiments with simulations, enhancing optimization speed and reducing hardware implementation costs. The performance index for the proposed modified Taguchi tuning method is selected as a combination of the quality factor (Q) and coupling coefficient (k) to minimize AC resistance and improve system efficiency. To validate the proposed method, the designed coils were implemented and tested in a WPT system based on S–S compensation with a half-bridge topology. The experimental results demonstrate that the optimized PCB coil parameters derived from the proposed tuning method accurately validate the method’s effectiveness and accuracy. From the measured results with the proposed modified tuning method, the system efficiency is increased by 43.87% and the system transmitting power is increased by 28.51%.

Integrated RES With Intelligent MPPT For Efficient Power Generation & Wireless Transmission for PV Applications

The increasing global energy demand and the urgent need to shift to sustainable practices have made the integration of renewable energy sources (RESs) into distribution power systems imperative. This project's main objective is to implement rooftop photovoltaic (PV) systems as an essential part of low-voltage (LV) DC networks' building-integrated centralized generation Maximum Power Point Tracking (MPPT) using Artificial Neural Networks (ANNs) is used to maximize power extraction from photovoltaic (PV) panels and boost power generation efficiency, particularly in partially shaded circumstances. After that, the PV system's generated power is sent to a Luo converter, which effectively tracks and optimizes the power production. For wireless power transmission, the Luo converter's output is then fed into a high-frequency converter. This wireless power transmission improves the system's adaptability and scalability by facilitating smooth energy transfer without the requirement for physical connections. An isolation transformer is attached to the high-frequency converter's output in order to guarantee the system's dependability and safety. The high-frequency converter is isolated from the downstream components by the isolation transformer, which also offers protection against electrical risks. Finally, a battery made especially for use in electric vehicle (EV) applications receives the transformer's isolated output, which is also supplied to DC loads. Finally, we will use the MATLAB 2021a / Simulink program to do a number of numerical simulations in order to validate the suggested controls. The output voltage of 130v is stored in the battery if a voltage of 65 v is taken as output from the photovoltaic system.