Wireless Transmission Technology Research Articles

Study of data and power transmission based on frequency-shift modulation in wireless charging

To ensure the reliability of the Wireless Power Transfer (WPT), the simultaneous wireless power and data transmission technology has gained more attention to realize real-time information exchange between the transmitter and receiver sides. In this paper, the shared channel technology and 2FSK modulation method are proposed to accomplish data and power transmission simultaneously. The theoretical analysis of the series-series compensation network is established, and the data modulation method through frequency-shifted modulation is analyzed. In order to reduce the bit error rate of transmitted data, a communication data format containing start and stop bits is proposed in this proposed system. Finally, an experimental prototype is constructed to validate the correctness and effectiveness of the proposed design and approach.

Water Conservancy Automation Monitoring System Based on VR Image Video and Internet of Things

With the rapid development of science and technology and the widespread application of automatic control and wireless transmission technology, water conservancy automation monitoring system plays an important role in agricultural water conservancy and the automatic water conservancy monitoring system can conduct automatic water conservancy irrigation and monitor the growth of crop, greatly improving the efficiency of water resources management. However, there is still a certain gap between China and developed countries, mainly reflected in the two aspects of imperfect information resources and low level of data analysis and application, there are still technical deficiencies, and the training of high-end talents is relatively scarce, so there is still a big gap. The purpose of this article is to study the water conservancy automation monitoring system based on VR image video and the Internet of Things. This article first analyzes virtual reality technology and introduces Unity3D, the development engine of virtual reality, then introduces the Internet of Things and its key technologies, studies the classification of existing water conservancy automation systems, and then details the use of C/S Structured water conservancy automatic monitoring system. On this basis, this article combines VR and IoT technologies in the experimental part to design and implement a water conservancy automation monitoring system. Experimental results prove that the system designed in this article has certain theoretical and practical value for the development of water conservancy informatization. In this article, by creating 1000 concurrent users, the performance of the designed system is tested, and the response time of this system is 3.4 seconds.

Structure Design of Quadrilateral Overlapped Wireless Power Transmission Coupling Coil

The application of wireless power transmission technology is becoming more and more extensive. However, in practical applications, the problem of reducing the energy transmission efficiency caused by the offset of the coupling coil needs to be solved urgently. Changing the coil structure is a widely adopted method to deal with this problem. Based on the characteristics of the existing magnetic coupling resonant wireless power transmission system and the principle of the anti-offset coil, this paper innovatively designs a new type of quadrilateral overlapping wireless power transfer coupling coil, which has a strong anti-offset capability. The new type of coil model was built in the simulation and experiment, and the relevant parameters were measured. Experimental results verify that the proposed coil structure has an excellent anti-offset capability.

Charging Wearable Devices Through Natural Interactions with Instrumented Everyday Objects

Recent advancements in semiconductor technologies have stimulated the growth of ultra-low power wearable devices. However, these devices often pose critical constraints in usability and functionality because of the on-device battery as the primary power source [1]. For example, periodic charging of wearable devices hampers the continuous monitoring of users' fitness or health conditions [2], and batteries and charging equipment have been identified as one of the most rapidly growing electronic waste streams [3]. To counteract the above-mentioned complications associated with the management of on-device batteries, wireless power transmission technologies capable of charging wearable devices in a completely unobtrusive and seamless manner have become an emerging topic of research over the past decade [4]. Researchers have instrumented daily objects or the surrounding environment with equipment that can wirelessly transfer energy from a variety of sources, such as Radio Frequency (RF) signals, laser, and electromagnetic fields [5]. However, these solutions require large and costly infrastructure and/or need to transmit a significant amount of power to support reasonable power harvesting at the wearable devices, which conflict with the vision of ubiquitously available and scalable charging support.

DRL based partial offloading for maximizing sum computation rate of FDMA-based wireless powered mobile edge computing

Since most Internet of Things (IoT) nodes are powered by small-capacity batteries and equipped with small computing units, it is difficult for them to process computing-intensive and delay-sensitive tasks. To address these two limitations, a feasible approach is to use both wireless power transmission (WPT) and mobile edge computing (MEC) technologies. Wireless edge devices (EDs) have stable energy supply by capturing radio frequency (RF) energy transmitted by the energy source and offloading computation workload to edge computing servers (ECSs) to enhance the computation rate. In this paper, an FDMA-based wireless-powered MEC network is considered, which consists of an ECS, an RF energy source and multiple EDs. The research goal is to maximize the sum computation rate (SCR) by jointly optimizing the WPT duration, energy allocation for local computation, and computation offloading, and bandwidth allocation among EDs. We first formulate this as a non-convex optimization problem that is hard to address. Then, we decompose it into a top-problem for optimizing the WPT duration and a sub-problem for optimizing the energy allocation and bandwidth allocation under a given WPT duration. An online offloading algorithm based on deep reinforcement learning (DRL) is proposed to quickly obtain the near-optimal WPT duration. For the sub-problem, we design an efficient two-stage algorithm to obtain the optimal solution. The simulation results show that the proposed algorithm can obtain the near-optimal solutions with low computation complexity.

PELP: Accounting for Missing Data in Neural Time Series by Periodic Estimation of Lost Packets.

Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as “bidirectional devices”, are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets (PELP). PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential (LFP) recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission—a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders.

Ground-based investigation of a directional, flexible, and wireless concentrated solar energy transmission system

Solar energy in space is more intensive and continuous compared to that on the Earth, and thus, is encouraged by governments across the world to be utilized for human beings. The continuity of the space sunlight has a great potential to overcome the bottleneck of the variability and intermittency in time and space for ground-based solar energy applications. Space solar power station (SSPS) is known as intermedia that can harvest the space solar energy and transmit it wirelessly to the end-user. However, the current wireless energy transmission via microwave or laser suffers from low energy transmission efficiency because of excessive energy conversion processes. Wireless energy transmission via sunlight without any intermediate energy conversion process was proposed previously theoretically for high energy transmission efficiency, but it also lacks practicability due to heavyweight and inflexibility. Therefore, although promising, practical sunlight-based wireless energy transmission proposals have not ever been presented. Here, through component and structure optimizations in theoretical and experimental approaches, a novel and more practical concentrated solar energy wireless transmission system that transmits the harvested sunlight via lightweight optical fibers is proposed in this paper. It uses a Fresnel lens to collect concentrated solar energy and then, the utilized optical fiber can steer the collected energy to the collimator flexibly. At last, a parallel sunlight beam can be emitted from the collimator to the target end-user. Results show that the transmitter efficiency versus optical fiber length exhibited a linear relationship from both theoretical and experimental approaches. the cloud effect harmed the energy transmission. A maximum transmitter energy transmission efficiency of 52.0% could be attained experimentally. Compared with the performance in the no-cloud condition, the gained voltage could be declined by 37% ∼ 48%. The bending of the optical fiber seemed to not affect much on the energy transmission performance, which guarantees a flexible energy transmission. Besides, the power/weight ratio was increased by 17.0% compared to its counterpart. The innovation of this paper is to reduce the gap between theoretical and practical feasibilities for the proposed system. This paper experimentally demonstrates the feasibility of a wireless concentrated solar energy transmission technology, which promotes the application of SSPS and related aerospace applications.

Mode on Power Distribution of a Dynamic Dual Pickup Wireless Charging System for Electric Vehicles

Power distribution is critical for the dynamic dual receiver coil wireless charging system of electric vehicles. The power distribution method of the existing wireless power transmission technology mainly distributes the power to the load according to the requirements of different resonant frequencies. However, the existing methods have the problems of low accuracy and low power consumption, so it is difficult to implement in practice. This paper presents a new power distribution method, which can dynamically and accurately distribute power to loads. This method can improve the control speed of the receiving circuit without additional circuit on the receiving side, and realize constant power output and efficiency optimization at the same time when there is no communication connection with the transmitter. Therefore, it is easy to realize in the wireless charging system of electric vehicle with dual receiver coil. The experimental results show that the load-side output power of the dynamic radio energy transmission system can be kept constant when moving, and the maximum efficiency of the output system reaches 91.38%. The experimental results prove the effectiveness of the proposed control method.

Hypergraph-Based Active Minimum Delay Data Aggregation Scheduling in Wireless-Powered IoT

Thanks to the promising wireless power transmission (WPT) technology, wireless-powered Internet of Things (WPIoT) can significantly improve the sustainable service ability of Internet of Things (IoT) with low personnel maintenance costs, and thus, shows remarkable and broad prospects in many applications, especially under the abominable and dangerous environment. Minimum delay data aggregation scheduling (MAS) is a problem of cardinal significance in WPIoT with the objective of timely collecting the data of IoT devices. However, due to the residual energy limitation of IoT devices, WPIoT shows the special feature of adopting the store-charge-and-forward communication mode, which brings new research challenges on designing efficient solutions to the MAS problem. We show that the MAS problem under the physical interference model in WPIoT is NP-hard. To tackle this problem, we propose a delay-efficient data aggregation scheduling algorithm called HADA based on an active data aggregation tree construction method and a novel hypergraph-based link scheduling method. Extensive numerical experiments are conducted to evaluate the performance of our proposed algorithm. The results demonstrate that our HADA algorithm can efficiently improve the performance compared with the existing baseline algorithms.

Simultaneous Wireless Power and Information Transmission Based on Harmonic Characteristic of Soft-Switching Inverter

The existing simultaneous wireless power and information transmission (SWPIT) technology used for wireless power transfer (WPT) systems is seriously plagued by the interference between the power and information transmission and the complex design of the information transmission and receiving circuits. To combat these problems, this article proposes a novel SWPIT method, which does not need additional information transmitting or receiving coils. The stroboscopic mapping model of the WPT system is established first, and the soft-switching points of the dc–ac inverter are derived and compared for better utilizing deviation frequency enlargement effect (DFEE) to transfer power and information simultaneously. Subsequently, the information detection circuit is designed based on DFEE. The impacts caused by the detection circuit on the power and information transmission are analyzed in detail. Then, the parameters of the detection circuit are optimized for minimizing the mutual interference between the power and information transmission. Finally, a 50 W experimental platform is established to verify the correctness and effectiveness of the proposed SWPIT strategy. The experimental results show that the information transmission rate can reach up to 16 kbps, the load voltage fluctuation can be controlled below 3%, and the efficiency of the whole system can be maintained at 90%.

System Resource Allocation and Rural Industry Revitalization Based on Max-Min Algorithm.

At this stage, the research hotspots on wireless multimedia sensor networks mainly include MAC protocol, network security, and node positioning. Research on resource allocation is scarce. Due to the lack of an effective wireless resource allocation strategy, even the most advanced transmission technology will not be able to fully utilize its unique advantages due to unreasonable resource allocation. Therefore, in-depth research on wireless resource allocation strategies is of great significance for the better application of wireless transmission technology. The entire network uses OFDMA mechanism to divide time slots. According to this method, resource allocation can be divided into intercluster and intracluster, and then the Max-Min subcarrier allocation algorithm is innovated and perfected to ensure maximum information transmission speed and throughput and promote information data efficient transmission. Based on the research of wireless sensor system resource allocation technology, China has emphasized industrial prosperity as the key point in its rural revitalization strategy, and doing a good job in technological innovation and industrial innovation is of great significance to economic development. At this stage, the capacity of rural industrial economic development is poor, and the economic level of most rural areas is not high. This situation is inseparable from problems such as limited industrial development and insufficient technological innovation capabilities. In order to promote the prosperity of rural industries and achieve the goal of rural revitalization, we must proceed from the fundamentals and give priority to solving the outstanding problems encountered in the process of rural industrial revitalization. Promoting the revitalization of rural industries can effectively solve the current plight of agricultural development and is an inherent requirement for rural prosperity and the country's prosperity. Aiming at the problems in the process of restricting the revitalization of rural industries, this article adheres to the principle of integrating theory with practice and puts forward practical and feasible measures to solve the problem in a targeted manner.

Compression Reconstruction and Fault Diagnosis of Diesel Engine Vibration Signal Based on Optimizing Block Sparse Bayesian Learning.

It is critical to deploy wireless data transmission technologies remotely, in real-time, to monitor the health state of diesel engines dynamically. The usual approach to data compression is to collect data first, then compress it; however, we cannot ensure the correctness and efficiency of the data. Based on sparse Bayesian optimization block learning, this research provides a method for compression reconstruction and fault diagnostics of diesel engine vibration data. This method’s essential contribution is combining compressive sensing technology with fault diagnosis. To achieve a better diagnosis effect, we can effectively improve the wireless transmission efficiency of the vibration signal. First, the dictionary is dynamically updated by learning the dictionary using singular value decomposition to produce the ideal sparse form. Second, a block sparse Bayesian learning boundary optimization approach is utilized to recover structured non-sparse signals rapidly. A detailed assessment index of the data compression effect is created. Finally, the experimental findings reveal that the approach provided in this study outperforms standard compression methods in terms of compression efficiency and accuracy and its ability to produce the desired fault diagnostic effect, proving the usefulness of the proposed method.

Startup Process Optimization of Hydropower Unit Based on Stress Measurement of Francis Turbine Runner

The energy efficiency characteristics of the turbine, cavitation performance of the runner, and operation stability of the unit are the three major concerns of a hydropower field, the latter two factors leading to the units’ cavitation and stability problems under some operation conditions and fatigue failure of the runner blades, which are the main causes of structural and mechanical failure for the hydropower units. In this article, three conventional unit startup processes are introduced, and combined with the optimal impulse control strategy, an optimized unit startup method is proposed. As the optimal guide vane opening adjustment setting value is obtained by solving the planned startup control strategy, 3D modeling and CFD simulation are carried out, then the equivalent stress characteristics are obtained by finite element calculation when the unit is running from startup to no load at a rated speed on three different startup modes. At last, the dynamic stress tests of the runner blade are performed at the hydropower station by using wireless acquisition and transmission technology, and the peak value and characteristics of the dynamic and static stresses of the blade under different startup processes are obtained. In this, the validity of the model analysis is proved by the comparison between the simulation calculation and the measured results, and the effectiveness of the startup control strategy is proved by combining the runner blade dynamic stress simulation, calculation, and the field dynamic stress test results. The optimization method of the startup process proposed in the article can alleviate the abnormal vibration of the unit and provide a basis for long-term stable operation of the hydropower unit.

Technological Requirements and Challenges in Wireless Body Area Networks for Health Monitoring: A Comprehensive Survey.

With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors in or around the patient’s body to realize real-time continuous remote monitoring. Compared to other wireless transmission technologies, a WBAN has more stringent technical requirements and challenges in terms of power efficiency, security and privacy, quality of service and other specifications. In this paper, we review the recent WBAN medical applications, existing requirements and challenges and their solutions. We conducted a comprehensive investigation of WBANs, from the sensor technology for the collection to the wireless transmission technology for the transmission process, such as frequency bands, channel models, medium access control (MAC) and networking protocols. Then we reviewed its unique safety and energy consumption issues. In particular, an application-specific integrated circuit (ASIC)-based WBAN scheme is presented to improve its security and privacy and achieve ultra-low energy consumption.

Pest incidence forecasting based on Internet of Things and Long Short-Term Memory Network

The infestation of litchi stink bugs (Tessaratoma papillosa) has always had a significant impact on the yield of longan plantations. Pest control is critical for farmers to detect and timely suppress the occurrence of pests while effectively reducing damages. Environmental factors, climate change in particular, have contributed to the growing population of pests whereas weather can vary in different terrains, locations, and time. Due to the geographical and topographical conditions of Taiwan, this study focuses on investigating fruit plantations on sloping land in subtropics with distinct seasonal changes. The article aims at forecasting meteorological data based on Long short-term memory network (LSTM) and identifying the correlation between pest infestation and environmental factors through Machine Learning (ML). In this section, the structure and experimental process of the research will be outlined. At the first stage, meteorological information of the experimented site is obtained through the self-designed IoT (Internet of Things) system and wireless long-distance transmission technology. Since meteorological information forecasted is displayed in time series, multi-layer LSTM and bidirectional LSTM are used to solve the problem. Finally, environmental data and field surveys conducted for pest surveillance will be employed to forecast the severity of pest infestation through KNN, SVM, and random forest models. The result of the experiment shows that LSTM performs well in weather forecasting with 96% R-Squared values whereas the accuracy rate of pest prediction conducted by Machine Learning (ML) is 85%. The study verifies that meteorological factors do affect pest incidence. For example, the population of litchi stink bugs increase easily under suitable temperature, humidity, and sunlight. LSTM is superior in providing solutions for long-range dependence in statistics. This article shall present regions with shifting weather patterns, meteorological conditions and time length forecasted corresponding to the oceanic climate, as well as the correlation between pest population and environmental factors.

Telehealth Technology Application in Enhancing Continuous Positive Airway Pressure Adherence in Obstructive Sleep Apnea Patients: A Review of Current Evidence.

Obstructive sleep apnea (OSA) is a common type of sleep-disordered breathing associated with multiple comorbidities. Continuous positive airway pressure (CPAP) is the first choice for moderate-severe OSA but poor compliance brings a great challenge to its effectiveness. Telehealth interventions ease the follow-up process and allow healthcare facilities to provide consistent care. Fifth-generation wireless transmission technology has also greatly rationalized the wide use of telemedicine. Herein, we review the efficacy of the telehealth system in enhancing CPAP adherence. We recommend applying telemonitoring in clinical practice and advocate the development of a biopsychosocial telemedicine model with the integration of several interventions. Big databases and promising artificial intelligent technologies make clinical decision support systems and predictive models based on these databases possible.

Improved Winding and Compensation Methods for the Multilayer Coil in IPT System

Wireless power transmission technology is used to transmit energy without contact in the field of electric vehicles, consumer electronics, and other industries. Among them, there are some applications with very low coupling coefficient where multilayer coil needs to be wound. Influenced by the parasitic capacitor between layers, the loss of the multilayer coil increases. The improved coil winding method and compensation method are proposed in this letter. Winding coils following the same sequence from outside to inside in each layer and connecting capacitors in series between layers of the coil can significantly reduce the voltage of the layers’ parasitic capacitor, which will decrease the coil loss. Compared with traditional method, the improved method increases the system efficiency at heavy load and light load by 0.74% and 2.48%, respectively. A 1-kW prototype was built with the maximum efficiency of 93.58%.

Sensor Design Based on Wireless Measurement of Corrosion Monitoring of Reinforced Concrete Structure

Reinforced concrete structures are widely used in modern buildings such as buildings, bridges, and tunnels. However, the structural damage caused by reinforcement corrosion seriously affects the service life of the buildings. Because the corrosion of reinforcement in concrete is a very slow process, the continuous detection of reinforcement corrosion is very important. In view of the slow development of steel corrosion detection equipment in China, which cannot meet the application requirements of concrete structures in China, wireless monitoring technology has more advantages than traditional monitoring technology. In this paper, combined with wireless transmission technology, a concrete reinforcement corrosion detection system based on wireless sensor network is designed. Embedded sensors based on the principle of electromagnetic coupling are used to collect steel corrosion information. It is determined that the 16-bit ultralow power consumption microcontroller MSP430F149 is the main control chip, the AD9850 based on DDS technology is the signal generation chip, and the nRF905 is the detection circuit scheme of the wireless transceiver chip. The star network is determined by polling the entire network topology and MAC protocol. The embedded sensor is designed through simulation. This article discusses the principle of using embedded sensors to detect steel corrosion and determines the feasibility of its low-cost implementation. The embedded sensor and steel corrosion detection system were tested. The simulation method of the embedded sensor is verified through actual measurement. The test results show that the system network is normal and all parts work stably, which can meet the requirements of the project.

Bank Green Credit Risk Assessment and Management by Mobile Computing and Machine Learning Neural Network under the Efficient Wireless Communication

The study is aimed at assessing and managing the green credit risk of banks, reduces the systemic risk in the financial industry, and improves the efficiency of the use of bank funds. With the development and evolution of efficient wireless data communication and transmission technology, the study combines theoretical and empirical green credit analysis to analyze listed companies in different industries quantitatively. The index system of credit risk assessment is established through wireless data transmission technology combined with mobile computing and machine learning neural networks. A back-propagation neural network (BPNN) model is confirmed by principal component analysis and factor analysis, and the performance of the model is verified with example data. The results show that the BPNN-based credit risk assessment model can provide 95% accuracy. In addition, 99% of the sample companies have low risk and no green credit risk. However, most companies in the coal industry are at greater risk. Overall, medium and high-risk companies accounted for 11.5%. Compared with other state-of-the-art models, the machine learning neural network adopted here has better data fitting and prediction accuracy, higher learning efficiency, and higher accuracy. The model established inefficient wireless communication is suitable for bank credit risk assessment and has good reference value and practical significance for bank credit risk assessment and management in different industries.

Optimization of Electric Vehicle Wireless Power Transmission Efficiency Based on Ant Lion Optimizer

<div class="section abstract"><div class="htmlview paragraph">Magnetically coupled resonance wireless power transmission technology (MCR-WPT), as a technological innovation in the electric vehicle industry, is of great significance to promote the development of the electric vehicle industry chain. The current wireless charging technology is affected by the design of the vehicle itself, the distance between the vehicle-mounted part of the wireless charging and the ground is not fixed. And the changeable parking attitude will cause the projection of the transmitting coil and the receiving coil to deviate. Therefore, reasonable matching of transmission frequency, matching impedance and other parameters is of great significance for optimizing power transmission efficiency. This paper establishes a mathematical model of transmission frequency, matching impedance, distance between two coils and wireless power transmission efficiency. Based on the preliminary analysis of 10 experimental data of wireless charging in the laboratory under different coil spacings, the relationship between various parameters and wireless charging efficiency is obtained. In view of the problem of coil offset under actual charging conditions, a nonlinear optimization model for maximizing the efficiency of the MCR-WPT system is proposed. The selected optimization parameters are parameters such as transmission frequency and matching impedance. The goal is to ensure the maximum value of automotive coil offset under high transmission efficiency. In this paper, the optimization model is solved based on the Ant lion optimizer, and the optimal parameter values under the specified working conditions are obtained, and the relative error is less than 3%. When the coil spacing is 10mm, the maximum offset of the coil with a transmission efficiency higher than 80% is 0.3423m, and the RMSE between theoretical and experimental results is less than 0.015. Algorithm optimizes the power transmission efficiency and improved the fault tolerance rate of wireless charging system during parking.</div></div>