Wireless Systems Research Articles

A Cross-Layer Approach to Analyzing Energy Consumption and Lifetime of a Wireless Sensor Node

Several wireless communication technologies, including Wireless Sensor Networks (WSNs), are essential for Internet of Things (IoT) applications. WSNs employ a layered framework to govern data exchanges between sender and recipient, which facilitates the establishment of rules and standards. However, in this conventional framework, network data sharing is limited to directly stacked layers, allowing manufacturers to develop proprietary protocols while impeding WSN optimization, such as energy consumption minimization, due to non-directly stacked layer effects on network performance. A Cross-Layer (CL) framework addresses implementation, modeling, and design challenges in IoT systems by allowing unrestricted data and parameter sharing between non-stacked layers. This holistic approach captures system dynamics, enabling network design optimization to address IoT network challenges. This paper introduces a novel CL modeling methodology for wireless communication systems, which is applied in two case studies to develop models for estimating energy consumption metrics, including node and network lifetime. Each case study validates the resulting model through experimental tests, demonstrating high accuracy with less than 3% error.

Optimal demodulation domain for microwave SQUID multiplexers in presence of readout system noise

The Microwave SQUID Multiplexer (μMUX) is the device of choice for the readout of a large number of low-temperature detectors in a wide variety of experiments within the fields of astronomy and particle physics. While it offers large multiplexing factors, the system noise performance is highly dependent on the cold- and warm-readout electronic systems used to read it out, as well as the demodulation domain and parameters chosen. In order to understand the impact of the readout systems in the overall detection system noise performance, first, we extended the available μMUX simulation frameworks, including additive and multiplicative noise sources in the probing tones (i.e., phase and amplitude noise), along with the capability of demodulating the scientific data, either in the resonator’s phase or the scattering amplitude. Then, considering the additive noise as a dominant noise source, the optimum readout parameters to achieve minimum system noise were found for both open-loop and flux-ramp demodulation schemes in the aforementioned domains. Later, we evaluated the system noise sensitivity to multiplicative noise sources under the optimum readout parameters. Finally, as a case study, we evaluated the optimal demodulation domain and the expected system noise level for a typical software-defined radio readout system. This work leads to an improved system performance prediction and noise engineering based on the available readout electronics and the selected demodulation domain.

Energy‐efficient channel selection algorithm with reduced collision probability in cognitive radio networks

AbstractThe growing demand for radio spectrum, driven by widespread communication devices, has led to spectrum congestion. Cognitive radio networks (CRNs) offer a solution by allowing secondary users (SUs) to access primary users' (PUs) channels without causing interference. This paper presents an energy‐efficient channel selection algorithm aimed at reducing collision probability and energy consumption during spectrum sensing. A prediction‐based model forecasts PU channel availability, enabling selective sensing. The results show a significant reduction in energy consumption, with the proposed method consuming 57.9% energy compared to 63.7% for a recent existing method. The proposed approach enhances spectrum management in next‐generation wireless systems by minimizing interference and optimizing energy use.

Copper abietate/polyvinyl acetate composite film for enhanced humidity sensing in Chinese herbal medicine monitoring systems

Sensing materials derived from natural and biodegradable sources are increasingly being developed and applied to realize environmentally friendly technologies. In this paper, we present the synthesis, characterization, and application of a novel copper abietate/polyvinyl acetate (CuA/PVAc) composite film, specifically engineered to enhance the humidity-sensing capabilities of Chinese herbal medicine monitoring systems. The sensing material was synthesized by strategically melding copper abietate, a natural renewable material, with PVAc to exploit their combined synergistic properties for optimal humidity-sensing performance. Comprehensive characterization techniques, including inductively coupled plasma optical emission spectrometry (ICP-OES), field-emission scanning electron microscopy (FESEM), water contact angle measurements, and Fourier transform infrared (FT-IR) spectroscopy, were employed to confirm the formation of CuA/PVAc composites. These analyses confirmed the homogeneity and intended chemical composition of the composite films.The resultant CuA-1/PVAc-4 (0.4 μg/μL) composite film exhibited a good logarithmic relation (0.9988) with relative humidity (RH) over a wide range (11 %–97 %) and high sensitivity (24.55 Hz/%RH). Moreover, this study introduces a novel, eco-friendly approach by integrating the CuA/PVAc composite with a quartz crystal microbalance (QCM) sensor and a sophisticated wireless circuit that enables real-time, Wi-Fi-based humidity monitoring tailored for the preservation of Chinese herbal medicines. The implementation of this wireless humidity detection system represents a significant advancement in the application of environmentally friendly materials in sensor technology and offers a practical and scalable approach for precise environmental monitoring.

Self-decoupled coupler based dual-coupled LCC-LCC rotating wireless power transfer system with enhanced output power

Self-decoupled coupler based dual-coupled LCC-LCC rotating wireless power transfer system with enhanced output power

High efficiency three‐dimensional wireless power transfer system using cylindrical transmitting coil

AbstractThree‐dimensional (3D) wireless power transfer (WPT) is an attractive methodology to improve the charging safety and flexibility of portable electronic equipment and to meet the charging demand brought by the increase of electronic equipment. Herein a 3D WPT system using a cylindrical transmitting coil excited by a single power source is proposed to improve flexibility and efficiency. Specifically, the coil size is designed and the circuit model is analyzed. A method for determining inductor parameters of Inductor‐Capacity‐Capacity compensation is designed to achieve high efficiency. The power transmission performance of the WPT system is validated through an experimental platform. The measured maximum power is more than 50 W, and the maximum DC‐DC efficiency is up to 82.3%. The system can simultaneously charge multiple loads with different receiving coils at different positions. The proposed WPT system can improve the flexibility of equipment charging without control, and provide a reference for the design of portable equipment high efficiency wireless chargers.

Fingerprint localisation for fine‐scale wildlife tracking using automated radio telemetry

Abstract Automated radio telemetry systems are one of the most widely applicable methods for tracking wildlife at fine spatiotemporal scales. A growing trend is for these systems to apply large networks of receivers to detect radio signal strength (RSS) from radio‐tagged individuals. Analytical methods to derive position estimates using RSS localisation, however, are relatively underdeveloped in the field of wildlife tracking. Here, we apply approaches from indoor positioning systems to develop a new method, radio fingerprinting, for localising radio‐tagged animals in structurally complex, outdoor environments. This method characterises the RSS patterns at known locations to generate a radio map of the study area, which is then used to predict the location of new RSS patterns. We conducted field tests to evaluate the localisation accuracy of radio fingerprinting relative to multilateration, a commonly used method for RSS localisation. To do so, we established an experimental receiver network covering multiple habitat types and compared the localisation accuracy of radio fingerprinting to multilateration. Additionally, we evaluated how a variety of features characteristic of typical tracking data sets affected the accuracy of both methods. While both methods had a similar median error under ideal conditions (~30 m), radio fingerprint localisation method offered several advantages over multilateration. Multilateration localisation estimates were highly affected by missed detections from the nearest receiver to the test point, which occurred in 30% of cases. In these cases, the median error was 103 m, over a 3.5‐fold increase. Distance to the nearest receiver also biased multilateration estimates with error increasing as the distance increased. Additionally, errors from multilateration estimates were higher in more densely vegetated areas. In contrast, fingerprinting position estimates were largely robust to each of these scenarios. Automated radio telemetry enables the fine‐scale, continuous tracking of range‐resident animals. We present radio fingerprinting as a localisation method in outdoor environments where standard localisation methods are error‐prone due to habitat heterogeneity and missed detections. This approach can be applied to any automated radio telemetry hardware and to any study system where a radio map can be generated.

Transverse resonance technique for analysis of a symmetrical open stub in a microstrip transmission line

Open stubs in a strip (microstrip) transmission line are one of the most common elements of planar circuits used in numerous devices in the various types of wireless systems. Therefore, the urgent problem is to develop an analyzing method for discontinuities in the form of the open stub in a microstrip transmission line at frequencies at which the high-frequency effects must be considered. In the paper, a technique of scattering characteristics calculating on a symmetrical microstrip open stub by transverse resonance method is presented. Boundary value problems for a rectangular volume resonator based on a microstrip transmission line with a symmetric open stub are solved for the three options boundary conditions in the symmetry plane and on the longitudinal boundaries. The intersection of the spectral curves obtained by the numerical solution of the “electric” and “magnetic” boundary value problems determines the minima of a reflection or transmission coefficients of fundamental wave on discontinuities. To algebraize the boundary value problems for the eigen frequencies of volume resonator with discontinuity, the corresponding two-dimensional functions of the magnetic potential are constructed, through which the components of the current density on the strip are determined. The functions of magnetic potential were defined by decomposing them into expansion by Fourier series, which ensures stable convergence of the series and numerical calculation algorithm. The developed technique has been tested by calculating the eigenfrequency spectra of an open microstrip stub using the transverse resonance method on the example of an open stub in a microstrip transmission line with a resonant frequency of about 3.0 GHz. Also, a technique for numerical solutions of “electric” and “magnetic” boundary-value problems for resonators with two electrodynamically coupled symmetric open stubs in a microstrip transmission line is developed.

Controllable Amplified Photonic Topological Insulators for New-Architecture Wireless Systems

Controllable Amplified Photonic Topological Insulators for New-Architecture Wireless Systems

Examining the efficiency of D2D communication employing DF-enabled multiple relay systems amid co-channel interference

Device-to-device (D2D) communication is emerging as a potential paradigm in contemporary wireless communication systems. Enabling D2D communication in the mmWave range has numerous challenges that must be overcome. The biggest concern is the introduction of interference from several sources. This study investigates the impact of co-channel interference (CCI) on D2D communication when energy harvesting (EH) and decode-and-forward (DF) techniques are used across several relay nodes. It includes mathematical equations for the cumulative distribution function (CDF) of the Signal-to-Interference-Plus-Noise ratio (SINR), as well as formulas for calculating the network's outage probability (OP), throughput (TP), and availability rate (AR). Furthermore, it produces an asymptotic expression for analyzing the probability density function (PDF) of the instantaneous SINR, providing a simple and complete approach to understanding its OP, TP, and AR properties. The analytical results are supported by Monte Carlo simulations and MATLAB implementation.

Optimized multi-head self-attention and gated-dilated convolutional neural network for quantum key distribution and error rate reduction

ABSTRACT Quantum key distribution (QKD) is a secure communication method that enables two parties to securely exchange a secret key. The secure key rate is a crucial metric for assessing the efficiency and practical viability of a QKD system. There are several approaches that are utilized in practice to calculate the secure key rate. In this manuscript, QKD and error rate optimization based on optimized multi-head self-attention and gated-dilated convolutional neural network (QKD-ERO-MSGCNN) is proposed. Initially, the input signals are gathered from 6G wireless networks which face obstacles to channel. For extending maximum transmission distances and improving secret key rates, the signals are fed to the variable velocity strategy particle swarm optimization algorithm, then the signals are fed to MSGCNN for analysing the quantum bit error rate reduction. The MSGCNN is optimized by intensified sand cat swarm optimization. The performance of the QKD-ERO-MSGCNN approach attains 15.57%, 23.89%, and 31.75% higher accuracy when analysed with existing techniques, like device-independent QKD utilizing random quantum states, practical continuous-variable QKD and feasible optimization parameters, entanglement and teleportation in QKD for secure wireless systems, and QKD for large scale networks methods, respectively.

An ultra lightweight neural network for automatic modulation classification in drone communications

Unmanned aerial vehicle (UAV)-assisted communication based on automatic modulation classification (AMC) technology is considered an effective solution to improve the transmission efficiency of wireless communication systems, as it can adaptively select the most suitable modulation method according to the current communication environment. However, many existing deep learning (DL)-based AMC methods cannot be directly applied to UAV platform with limited computing power and storage space, because of the contradiction between accuracy and efficiency. This paper mainly studies the lightweight of DL-based AMC networks to improve adaptability in resource-constrained scenarios. To address this challenge, we propose an ultra-lightweight neural network (ULNN). This network incorporates a lightweight convolutional structure, attention mechanism, and cross-channel feature fusion technique. Additionally, we introduce data augmentation (DA) based on signal phase offsets during the model training process, aimed at improving the model’s generalization ability and preventing overfitting. Through experimental validation on the public dataset RML2016.10 A, the ULNN we proposed achieves an average precision of 62.83% with only 8815 parameters and reaches a peak classification accuracy of 92.11% at SNR = 10 dB. The experimental results show that ULNN can achieve high recognition accuracy while keeping the model lightweight, and is suitable for UAV platform with limited resources.

Advances in EV wireless charging technology – A systematic review and future trends

Current advancements in wireless power transfer systems have improved the viability of enhancing the scope of the driving journey of an Electric Vehicle. This paper addresses the prime aspects of wireless charging infrastructure using a systematic approach, such as compensation topologies, power converter circuit design, and power transfer methods. The exclusive wireless charging track on the road minimizes the size of the battery device and the charging duration of energy storage during driving. The ability to transmit high power through a coil placed on the road to the Electric Vehicle requires an appropriate design for the complete wireless power transmission module. This paper also presents advancements in the domain of wireless technologies and recommends upcoming opportunities and future research trends.

Performance-constrained multi-objective optimization of antennas for miniaturization design

The miniaturization of antennas is crucial as it improves the integration of wireless communication system. In order to achieve miniaturization of antennas, a performance-constrained multi-objective optimization method (PCMOM) considering the size and return loss is proposed. In the PCMOM method, an optimization strategy based on a multi-port network model is introduced, enabling the formation of antennas with various structures. Furthermore, we integrate the constraint of return loss performance into the non-dominated sorting genetic algorithm II (NSGA-II), eliminating solutions that do not meet performance requirements. Three pixel antennas are designed using the PCMOM method and two of them are fabricated. Experimental results demonstrate that the proposed PCMOM method can effectively address the complex trade-off issues in antenna miniaturization design.

High-speed 0.22 THz communication system with 84 Gbps for real-time uncompressed 8K video transmission of live events

Terahertz frequency band (0.1 ~ 10 THz) can provide ultra-high transmitting rates for massive emerging applications. However, due to the radio frequency impairments and limited signal processing property of baseband devices, it is difficult for the current terahertz communication systems to be used in real applications. In this work, we report a 0.22 THz communication system, which can provide 84 Gbps air interface rate over 1.26 kilometers distance. Such a system is underpinned by three breakthroughs, namely, integrating the reported terahertz wireless communication system, redesigning the signal processing in baseband devices, and increasing the cut-off frequency and transmitting power of radio frequency component by parameter optimizing. Being applied to realize the real-time transmission of the uncompressed 8K ultra high-definition video in the 31st International University Sports Federation in Chengdu, China, this work is a leaping advancement to enable terahertz systems from experiment to promising applications.

Early wildfire detection using different machine learning algorithms

Early detection of wildfires is essential for mitigating their impact on forests and surrounding areas. In this study, we propose a wireless sensor node system that combines multiple low-cost sensors with an artificial intelligence-based detection method for early wildfire detection. The system architecture includes temperature, humidity, and smoke sensors, as well as a wireless communication module. Four machine learning classifiers, including decision trees, random forests, support vector machines, and k-nearest neighbors, were evaluated for their effectiveness in predicting wildfire detection using a dataset collected in a forest area. The results showed that the random forest algorithm with optimum hyperparameters had the highest accuracy in classifying fire and non-fire samples (77.95% correctly classified). The proposed system provides an effective and cost-efficient solution for early wildfire detection in large forest areas.

Multi-Parameter Control Anti-Jamming Algorithm for Wireless Communication Systems Based on Linear–Quadratic Regulator

Multi-Parameter Control Anti-Jamming Algorithm for Wireless Communication Systems Based on Linear–Quadratic Regulator

Electrical and fluorescence in situ monitoring of tumor microenvironment-based pH-responsive polymer dot coated surface

A boronate-ester structure forming a pH-responsive polymer dot (Plu-PD) coated biosensor between carbonized-sp2 rich dopamine-alginate [PD(Alg)] and boronic acid-grafted Pluronic (BA-Pluronic) was developed for the electrochemical and fluorescence detection of cancer cells. The reduced fluorescence (FL) resulting from fluorescence resonance energy transfer (FRET) mediated by π-π interactions within Plu-PD was successfully reinvigorated through the specific cleavage of the boronate-ester bond, triggered by the acidic conditions prevailing in the cancer microenvironment. The anomalous variations in extracellular pH levels observed in cancer (pH ∼6.8), as opposed to the normal cellular pH range of approximately 7.4, serve as robust indicators for discerning cancer cells from their healthy counterparts. Moreover, the Plu-PD coated surface demonstrated remarkable adaptability in modulating its surface structure, concurrently exhibiting tunable electroconductivity under reduced pH conditions, thereby imparting selective responsiveness to cancer cells. The pH-modulated conductivity change was validated by a reduction in resistance from 211 ± 9.7 kΩ at pH 7.4 to 73.9 ± 9.4 kΩ and 61.5 ± 11.5 kΩ at pH 6.8 and 6.0, respectively. The controllable electrochemical characteristics were corroborated through in vitro treatment of cancer cells (HeLa, B16F10, and SNU-C2A) via LED experiments and wireless output analysis. In contrast, identical treatments yielded a limited response in normal cell line (CHO–K1). Notably, the Plu-PD coated surface can be seamlessly integrated with a wireless system to facilitate real-time monitoring of the sensing performance in the presence of cancer and normal cells, enabling rapid and accurate cancer diagnosis using a smartphone.

Microwave-assisted in-situ synthesis of low-dimensional perovskites within metal-organic frameworks for optoelectronic applications

Halide perovskites are renowned for their remarkable optoelectronic properties, yet their application is hindered by stability challenges. Metal-organic frameworks (MOFs) have emerged as promising matrices for enhancing perovskite durability. In this study, we achieved the in-situ synthesis of a series of perovskites within the MOF-5 matrix, spanning three-dimensional, quasi two-dimensional, and two-dimensional structures, via microwave-assisted reaction techniques. This microwave synthesis method has proven to be a rapid and efficient approach for the high-yield production of perovskite materials. These MOF-5⊃perovskites exhibited superior optical properties, positioning them as promising candidates for various optoelectronic applications, including white light-emitting diodes and optical wireless communication (OWC) systems. Significantly, our perovskites demonstrated high and consistent communication rates, making them suitable for both space and underwater OWC deployments. Overall, our study underscores the potential of microwave-assisted synthesis in advancing high-performance perovskite materials, offering valuable insights for the development of future optoelectronic devices.

A series-parallel-compensated fractional-order wireless power transfer system with coupling independence and detuning insensitivity

A series-parallel-compensated fractional-order wireless power transfer system with coupling independence and detuning insensitivity