Wireless Communication Technology Research Articles

Embedded Water-lubricated Bearing Temperature Wireless Monitoring System

For the ship lubrication system, different water temperatures not only affect the viscosity coefficient of the water, but also cause additional thermal deformation of the rubber bearing, and in serious cases, it also affects the normal operation of the ship lubrication system. However, the water film has a closed area, various bearing structures, complex operating conditions, and limited existing monitoring methods, resulting in accurate temperature data that is not easy to obtain. In order to solve the above problems, a thin-film temperature sensor was proposed to be embedded in the water-lubricated bearing and wireless communication technology was applied, and a monitoring system was developed to achieve real-time monitoring of the bearing temperature signal. Firstly, the temperature monitoring system and bearing system are described, then the temperature sensor is calibrated, and finally the system is designed and tested through software and hardware. The results show that the method of the wireless temperature monitoring system in this paper is feasible.

Programmable beam steering and quasi-continuous phase shift on a 2-bit terahertz coding metasurface with HEMT-switched multimodal modulation.

Terahertz reconfigurable intelligent surfaces (RIS) stand out from conventional phased arrays thanks to their unique electromagnetic properties and intelligent interconnect paradigms. They are a vital technology for terahertz wireless communication and radar detection systems. Compared with 1-bit coding metasurfaces, 2-bit coding metasurfaces offer significant advantages such as single beam steering and reduced quantization errors. Electrically controlled switchable coding metasurfaces have been restricted by the switch performance and integration technology, limiting reported devices to 1-bit coding. Additionally, metasurfaces that offer quasi-continuous phase modulation across a 2π range have garnered extensive attention for their higher phase shift precision and regulation freedom. This paper proposes a 2-bit multimodal THz quasi-continuous phase shift coding metasurface based on asymmetrically configured high electron mobility transistor (HEMT)-dipoles. The meta-device consists of two asymmetrically combined HEMT-dipole resonant structures, wherein the versatile density variations of two-dimensional electron gas (2DEG) introduce subtly local-field modulation under different external voltage combinations, rendering the quasi-continuous phase shift of 0° to 350° at 0.376 THz with a minimum incremental step of 6°. Moreover, selecting optimal 2-bit coding states within the quasi-continuous phase shift loop constructed different array phase gradients based on Snell's law, enabling real-time beam steering from 21° to 48° within the 0.365-0.385 THz frequency range. The simulation results align closely with the experimental findings, marking the first achievement of real-time programmable phase shift control and 2-bit beam steering using electrically controlled switches in the terahertz domain. This research provides a practical approach for real-time quasi-optical continuous phase modulation control and programmable single-beam electronic steering, with promising applications in terahertz wireless communication, radar detecting, and computational imaging, among other fields.

Application analysis of wireless communication technology in China's smart grid

With the rapid advancement of China's economy and technological innovation, wireless communication technology has seen considerable development. Concurrently, global energy and environmental challenges have intensified, heightening the demand for efficient and sustainable energy management solutions. In response to evolving energy demands, China has introduced new standards for digital power grid construction, prioritizing the use of wireless communication technologies to improve energy efficiency and develop smarter grid systems. These technologies facilitate real-time data transmission, remote monitoring of equipment, and network interconnectivity, thereby improving operational efficiency and monitoring capabilities. This paper reviews recent applications of wireless communication technologies within smart grids, aiming to provide valuable insights for future developments based on existing literature and data. Wireless communication technology in smart grids mainly enhances the intelligence and efficiency of the grid by enabling real-time data transmission, remote device management, and optimized energy distribution. Technologies such as Wi-Fi, 5G, and LoRa facilitate key functions like smart meter monitoring, equipment status management, and demand response, driving the automation and intelligent development of power systems. Future research should focus on optimizing the integration of these technologies, strengthening network security, and leveraging big data and artificial intelligence to advance the intelligence of power systems, thereby addressing critical energy challenges and fostering sustainable development

Multiscale Convolution-Based Efficient Channel Estimation Techniques for OFDM Systems

With the advancement of wireless communication technology, the significance of efficient and accurate channel estimation methods has grown substantially. Recently, deep learning-based methods are being adopted to estimate channels with higher precision than traditional methods, even in the absence of prior channel statistics. In this paper, we propose two deep learning-based channel estimation models, CAMPNet and MSResNet, which are designed to consider channel characteristics from a multiscale perspective. The convolutional attention and multiscale parallel network (CAMPNet) accentuates critical channel characteristics by utilizing parallel multiscale features and convolutional attention, while the multiscale residual network (MSResNet) integrates information across various scales through cross-connected multiscale convolutional structures. Both models are designed to perform robustly in environments with complex frequency domain information and various Doppler shifts. Experimental results demonstrate that CAMPNet and MSResNet achieve superior performance compared to existing channel estimation methods within various channel models. Notably, the proposed models show exceptional performance in high signal-to-noise ratio (SNR) environments, achieving up to a 48.98% reduction in mean squared error(MSE) compared to existing methods at an SNR of 25dB. In experiments evaluating the generalization capabilities of the proposed models, they show greater stability and robustness compared to existing methods. These results suggest that deep learning-based channel estimation models have the potential to overcome the limitations of existing methods, offering high performance and efficiency in real-world communication environments.

Machine Learning Approach to Energy Detection Based Spectrum Sensing for Cognitive Radio Networks

AbstractCognitive radio is an intelligent technology for wireless communication that optimizes the use of available frequency bands. Machine learning techniques can play an important role in spectrum sensing for cognitive radio networks to meet the rising traffic demand of wireless communication systems. The reliability of spectrum sensing methods depends on the prior knowledge of the noise to set a threshold. On the other hand, the success of a machine learning model relies on both the datasets and the accuracy of its learning algorithms. In this paper, we propose a spectrum sensing method for cognitive radio based on a machine learning algorithm in the conventional energy detection technique that removes the requirement to calculate the threshold. Initially, we introduce a method to build the dataset using the general concept of spectrum sensing based on the energy detection technique. The Naive Bayes supervised machine learning classification algorithm is implemented on the generated dataset for training, validation, and testing to sense the available spectrum. The proposed method is evaluated and tested using performance metrics such as confusion matrix, accuracy, precision, recall, F1 score, probability of detection, and probability of false alarm. In the simulation, the quadrature phase‐shift keying (QPSK) modulation scheme over the additive white Gaussian noise (AWGN) channel is considered. The experimental outcomes of the proposed method provide satisfactory and acceptable performance for spectrum sensing in cognitive radio networks. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Adaptive Filtering for Channel Estimation in RIS-Assisted mmWave Systems.

The advent of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, coupled with reconfigurable intelligent surfaces (RISs), presents a significant opportunity for advancing wireless communication technologies. This integration enhances data transmission rates and broadens coverage areas, but challenges in channel estimation (CE) remain due to the limitations of the signal processing capabilities of RIS. To address this, we propose an adaptive channel estimation framework comprising two algorithms: log-sum normalized least mean squares (Log-Sum NLMS) and hybrid normalized least mean squares-normalized least mean fourth (Hybrid NLMS-NLMF). These algorithms leverage the sparse nature of mmWave channels to improve estimation accuracy. The Log-Sum NLMS algorithm incorporates a log-sum penalty in its cost function for faster convergence, while the Hybrid NLMS-NLMF employs a mixed error function for better performance across varying signal-to-noise ratio (SNR) conditions. Our analysis also reveals that both algorithms have lower computational complexity compared to existing methods. Extensive simulations validate our findings, with results illustrating the performance of the proposed algorithms under different parameters, demonstrating significant improvements in channel estimation accuracy and convergence speed over established methods, including NLMS, sparse exponential forgetting window least mean square (SEFWLMS), and sparse hybrid adaptive filtering algorithms (SHAFA).

Gesture-controlled reconfigurable metasurface system based on surface electromyography for real-time electromagnetic wave manipulation.

Gesture recognition plays a significant role in human-machine interaction (HMI) system. This paper proposes a gesture-controlled reconfigurable metasurface system based on surface electromyography (sEMG) for real-time beam deflection and polarization conversion. By recognizing the sEMG signals of user gestures through a pre-trained convolutional neural network (CNN) model, the system dynamically modulates the metasurface, enabling precise control of the deflection direction and polarization state of electromagnetic waves. Experimental results demonstrate that the proposed system achieves high-precision electromagnetic wave manipulation, in response to different gestures. This system has significant potential applications in intelligent device control, virtual reality systems, and wireless communication technology, and is expected to contribute to the advancement and innovation of HMI technology by integration of more advanced metasurfaces and sEMG processing technologies.

Overview of 5G and 6G wireless communication technology

Overview of 5G and 6G wireless communication technology

Radiofrequency Induced Time-Dependent Alterations in Gene Expression and Apoptosis in Glioblastoma Cell Line.

The widespread use of wireless communication technologies has increased human exposure to radiofrequency electromagnetic fields (RF-EMFs). Considering the brain's close proximity to mobile phones and its entirely electrical transmission network, it emerges as the organ most profoundly impacted by the RF field. This study aims to investigate the potential effects of RF radiation on cell viability, apoptosis, and gene expressions in glioblastoma cells (U118-MG) at different exposure times (1, 24, and 48 h). To achieve this, we designed and implemented an in vitro RF exposure system operating at a frequency of 2.1 GHz, specifically for cell culture studies, with an average specific absorption rate (SAR) of 1.12 ± 0.18 W/kg determined through numerical dosimetry calculations. Results reveal a significant influence of a 48 h exposure to a 2.1 GHz RF field on U118-MG cell viability, gene expression, and the induction of caspase (CASP) dependent apoptosis. Notably, increased CASP3, CASP8, and CASP9 mRNA levels were observed after 24 and 48 h of RF treatment. However, only the 48 h RF exposure resulted in apoptotic cell death and a significant elevation in the BAX/BCL-2 ratio. This observed effect may be influenced by extended exposure durations surpassing the cell's doubling time. The increased BAX/BCL-2 ratio, which acts as a key switch for apoptosis, and the heterogeneous morphology of the astrocyte-derived U118-MG cell line may also play a role in this effect.

Application of WiMAX technology in difficult geographical conditions: Perspectives for mountain environment

WiMAX (Worldwide Interoperability for Microwave Access) is a telecommunications technology designed to provide universal wireless communication over long distances for a wide range of devices (from workstations and notebook computers to mobile phones). It is based on IEEE 802.16 standard called Wireless MAN. The name “WiMAX” was coined by the WiMAX Forum, which was established in June 2001 to promote and develop WiMAX technology. The forum describes WiMAX as “a standards- based technology that provides high-speed wireless network access as an alternative to leased lines and DSL.” WiMAX allows you to access the wireless Internet at high speed with a wider coverage than Wi-Fi networks. This allows the technology to be used as “backbones”, a continuation of traditional DSL and leased lines, as well as local networks. As a result, this approach makes it possible to create high-speed networks that expand across cities. In recent years, the development of network technologies has led to a significant expansion of the list of possible ways of connecting personal computers to the network and the types of connections to the global Internet. From a server to a pocket computer, almost any personal device that has enough computing power to process text and graphic information is equipped with one or another network interface, from a modem to WiMAX. This article examines the application of WiMAX technology in mountainous conditions, and analyzes the technical solutions used to create a continuous and high-quality connection despite topographical and environmental challenges. The advantages of wireless communication technologies are shown in mountainous areas where the population is small and the infrastructure is limited. The article presents strategies for configuring WiMAX networks, installing base stations, and expanding network coverage. As a result, WiMAX is proving to be an effective solution for meeting broadband communication needs in mountain environments.

Wideband Microstrip Patch Antenna Design At 2.4 Ghz Frequency for Wireless Communication

The ever-increasing development of wireless and mobile communications, along with the rising volume of data and data traffic in wireless networks, requires these communications to be fast and uninterrupted. This can be achieved through the development of antennas with low return loss, high bandwidth, and compact size. In this study, an antenna design operating at a 2.4 GHz frequency was created using the CST Microwave Studio program to meet the need for broadband microstrip patch antenna designs. FR-4 material, which is 1.6 mm high, has a dielectric constant of 4.3 and a rectangular geometry with a loss tangent of 0.019, was used as the substrate material. At a resonance frequency of 2.4 GHz, the antenna was found to have a maximum gain of 2.27 dB and a maximum directivity of 7.28 dB in the same direction. Selection of new microstrip patch antenna configurations and development of accurate and versatile analytical models are of great importance in wireless communication technology.

Performance Analysis of fso Communication system with Different Modulation Schemes

Free-space optical communication (FSO) is a technology which use optical signals to transmit data wirelessly, providing a viable alternative to conventional wired systems. The Free Space Optical (FSO) communication system has emerged as an attractive option due to its large license free bandwidth, high security and low cost It is one of the very promising technologies for wireless communication. However, the sensitivity to weather conditions is one of the major disadvantage of FSO systems. Weather factors, such as rain, fog, snow, and dust, can significantly attenuate the optical signals, which can lead to a reduction in signal strength and it can affect potentially data transmission reliability. Present work focusses on two key performance parameters Average Bit Error Rate (ABER) and Outage Probability (OP) which is of much importance due to the adverse impact of weather factors on FSO communication system. For the present study the OP and ABER performance are analysed over Gamma- Gamma (G-G) fading for FSO links in the presence weak and moderate atmospheric turbulence with four different modulation schemes. The CDF functions for the channel model has been derived and MATLAB codes are used to predict the OP and ABER performance for the FSO communication system.

Disaster-Resilient Telecommunication with Optical Technologies

Telecommunication services enable transmission of data, voice, video, and other forms of communication over long distances through various technologies such as telephone lines, satellites, fiber optics, and wireless systems. These services are fundamental in enabling communication across different sectors, including healthcare. In disaster scenarios, the rapid and reliable delivery of healthcare services is critical for saving lives and ensuring the well-being of affected populations. Telemedicine, enabled by advanced telecommunication systems, plays a pivotal role in providing remote healthcare services when traditional medical facilities are inaccessible. This paper explores the integration of optical communication technologies, such Free Space Optics (FSO), into telemedicine systems to enhance their effectiveness in disaster response. Optical wireless communication (OWC) technologies offer high-speed, secure, and resilient communication channels, making them ideal for transmitting large volumes of medical data, real-time video consultations, and remote patient monitoring in challenging environments. By leveraging the bandwidth, low latency, and reliability of optical communication, telemedicine can support critical care operations, including remote diagnostics, emergency triage, and real-time collaboration between healthcare providers. This paper examines the potential of optical communication technologies to strengthen telemedicine services in disaster scenarios, ensuring that healthcare remains accessible, efficient, and secure, even under the most adverse conditions

Self-Powered Sensing and Wireless Communication Synergic Systems Enabled by Triboelectric Nanogenerators

With the rapid advancement of the Internet of Things (IoT) era, the demand for wireless sensing and communication is increasingly prominent. Tens of thousands of sensing and communication nodes have presented new challenges to distributed energy. As a green energy harvesting technology, the triboelectric nanogenerator (TENG), with its outstanding characteristics of simple configuration, low cost, and high compatibility, demonstrates significant advantages in self-powered sensing systems and great application potential in the fields of human–machine interaction and wearable devices in the IoT era. More importantly, the electric displacement field and modulated electromagnetic waves that TENG triggers have opened a new paradigm for self-powered wireless communication, making up for the disadvantages of power supply by traditional distributed power sources. This review comprehensively discusses the latest scientific and technological progress in wireless communication technology prompted by TENG and further discusses its potential applications in various promising fields. Finally, a summary and outlook of TENG-based self-powered sensing and wireless communication synergic systems are presented, aiming to stimulate future innovation in the field and accelerating the paradigm shift to a fully self-powered IoT era.

Secure Healthcare Monitoring and Attack Detection Framework using ELUS-BILSTM and STECAES

The patterns of providing health-centric services have transformed extremely with the enhancement along with innovations in mobile and wireless communication technologies subsuming the Internet of Things (IoT). Due to the rapidly increasing attack, the doctors were not provided with an accurate alerting mechanism by the prevailing health monitoring system. Thus, by utilizing the Exponential Linear activation Units-centred Bidirectional Long Short Term Memory (ELUS-BiLSTM) technique, a novel healthcare monitoring along with an attack detection system is proposed in this work. Attack detection, Data security, and Patient health monitoring are the three primary phases incorporated in the proposed methodology. Initially, from the patient, the data are collected, and then the features are extracted in the attack detection phase. Next, the features being extracted are inputted to the ELUS-BiLSTM classifier where the data is classified as attacked or non-attacked data. After that, by utilizing Skew Tent Elliptic Curve Advanced Encryption Standard (STECAES), the non-attacked data is encrypted whereas the attacked data is stored in the log file. Lastly, to generate the fuzzy rules, the encrypted data is utilized; subsequently, the alert message is sent to the doctor. The experiential outcomes displayed that when analogized with the prevailing methodologies, the proposed model obtained better outcomes.

Band Correlation‐Based Multichannel Multiscale Convolution Network for Intelligent Interference Recognition

AbstractIn recent years, with the development and extensive application of wireless communication technology, the communication system should have stronger anti‐Jamming ability. Therefore, interference recognition is particularly important as a prerequisite for anti‐interference. However, the existing traditional and intelligent interference recognition algorithms have problems such as complicated feature extraction and low recognition accuracy under low interference‐to‐noise ratio. In order to solve the above problems, this paper introduces parallel multi‐channel multi‐scale convolution to improve the speed and accuracy of network recognition. In addition, combined with frequency band correlation and long‐short‐term memory network (LSTM), an innovative wireless communication interference identification model based on frequency band correlation is proposed, which uses LSTM to detect the frequency band correlation of interference signals and improve the accuracy of interference identification under low Jamming noise ratio (JNR). Experiments prove that the model proposed in this article has faster recognition speed and better generalization. The introduction of frequency band correlation increases the recognition accuracy to more than 99% with low JNR. Therefore, the model proposed in this paper is an effective and available model in complex electromagnetic environments. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

LI-FI Performance Analysis in Various Aquatic Environments for Reliable Underwater Communication

The ability to communicate reliably and quickly underwater has been one of the driving forces behind the development of alternative technologies to conventional radio frequency systems. This study explores the performance of Light Fidelity (Li-Fi), a high-speed optical wireless communication technology, in diverse aquatic environments like fresh water, salt water, and turbid water. It evaluates key parameters like signal attenuation, data rate, bit error rate, and transmission range. Results show that Li-Fi offers significant advantages in bandwidth and data rate over traditional methods, but its efficiency is highly dependent on environmental conditions. The study recommends optimizing Li-Fi systems for reliable underwater communication, paving the way for enhanced underwater networking and data transmission applications.

Multimedia Transmission Technique for Smart Ambulance with multi-carrier OFDM in a V2V and V2I Channel model using Software Defined Radio Technology

This research explores the implementation of a cutting-edge Software Defined Radio (SDR) framework to transmit multimedia files that can be assumed to be medical data in smart ambulances. The system utilizes multi-carrier Orthogonal Frequency-Division Multiplexing (OFDM) across V2V and V2I channels. The research is based on the notion that adaptive real-time communication is essential for the uninterrupted supply of key patient data to medical facilities and vehicles in transit, in order to address the problems posed by high mobility and dynamic environmental conditions. A comprehensive SDR system has been constructed and assessed in comparison to conventional communication mechanisms, demonstrating notable advancements in data accuracy and uninterrupted transmission. Our system successfully established stable connections in V2I channels, even in the presence of environmental obstacles. It maintained average power levels of approximately 32.074 dBm and a Peak-to-Average Power Ratio (PAPR) of 1.037 dB. These results indicate a constant signal envelope that promotes optimal signal transmission with excellent fidelity. In V2V scenarios, we successfully maintained data integrity with a low Peak-to-Average Power Ratio (PAPR) of 3.316 dB, even while vehicles were moving at a speed of 20 km/h. Additionally, we secured a high likelihood (94.5%) that the signal power remained close to the average, showing the robustness of our system against Doppler effects and signal dispersion. Text transmissions experienced errors when subjected to a Doppler shift of 20 km/h, which impacted the decoding of the received text. Similarly, image transmissions revealed limitations in bandwidth, as a transmitted image of 3640 KB was received with a degraded 4 KB. This emphasizes the importance of implementing effective error handling and recovery mechanisms. The results illustrate the efficacy of the suggested system in maintaining a high Quality of Service (QoS), offering proof of the effectiveness of contemporary wireless communication technologies in improving emergency medical services and setting new standards in smart ambulance capabilities.

6G Wireless Communication Technology Operating at Frequencies beyond 200 GHz With Massive Internet of Things (IoT)

6G Wireless Communication Technology Operating at Frequencies beyond 200 GHz With Massive Internet of Things (IoT)

Dual-band polarization-controlled metasurface with independent amplitude-phase coding for versatile beam forming.

Digital coding metasurfaces have gained considerable attention for their potential to bridge physical and information sciences. However, existing metasurfaces are often restricted to either phase-only or amplitude-only control and typically operate within a single frequency band or polarization, limiting their functionality in advanced electromagnetic applications. This study proposes a dual-band metasurface with independent amplitude-phase coding for polarization-controlled beam manipulation, addressing these limitations. The designed metasurface features a three-layer structure that integrates resistive films and optimized geometries, allowing simultaneous and independent control of amplitude and phase for linearly polarized (LP) waves in the X-band and circularly polarized (CP) waves in the Ku-band. Through digital coding, it achieves simultaneous 1-bit control over amplitude and phase, facilitating flexible beam steering and complex wavefront manipulation across distinct polarizations and frequencies. A functional prototype was designed, simulated, fabricated, and experimentally tested. The results show close alignment between simulations and experimental measurements, confirming the metasurface's versatile modulation capabilities. This advancement provides a robust platform for applications in wireless communication, radar systems, and adaptive electromagnetic wave engineering, offering significant improvements in design flexibility and operational bandwidth.