Wireless Systems Research Articles

Calibration-free feedforward temperature compensation for wireless clock synchronisation

Wireless systems are entering the arena of time-critical applications, including industrial controls. This makes clock synchronisation vital. A relevant source of synchronisation errors, especially in heavy-duty applications and harsh environments, is given by temperature variations that affect the quartz oscillators. This paper takes a control theory-based approach and proposes to augment clock synchronisation schemes – that are typically feedback-based – with a feedforward compensation path using temperature measurements to quickly react to temperature change. Unlike previous approaches relying on per-device data, our solution takes advantage of the combined feedforward-feedback nature of the control scheme to perform compensation using only nominal crystal parameters. When implemented in conjunction with the FLOPSYNC-2 feedback-based clock synchronisation scheme and tested both in simulation and experimentally, the approach resulted in a greatly reduced synchronisation error during temperature transients. In detail, Monte Carlo simulations show that the proposed solution can reduce the peak clock synchronisation error on average by 5.3 \(\times\) and in the worst case by 2.2 \(\times\) , thus proving applicable and effective without the need for a costly per-device calibration. When tested experimentally on a network of sensor nodes, a 3.3 \(\times\) peak clock synchronisation error improvement was observed, confirming the simulation predictions.

Adaptive Direction of Arrival Estimation and Beamforming Algorithms for Future Networks and Advancements

Multiuser Multiple Input Multiple Output (MU-MIMO) wireless communication systems significantly enhance mobile cellular networks by employing Direction of Arrival (DOA) algorithms and beamforming (BF) techniques. These technologies enable the prediction of sidelobe signal directions, allowing for redirection toward specific desired targets. This research presents various adaptive DOA algorithms designed to improve wireless network performance. The study thoroughly examines DOA algorithms, including Multi-Signal Classification (MUSIC), Minimum Norm (Min-Norm), Minimum Variance Distortionless Response (MVDR), and Bartlett algorithms, comparing them based on angle estimation and peak power spectrum. The paper also discusses the concept of separating incoming signals into the Signals of Interest (SOI) and Signals Not of Interest (SNOI). Additionally, several BF algorithms, such as Least Mean Square (LMS), Recursive Least Square (RLS), and Constant Modulus Algorithm (CMA), are explored and evaluated. The research assesses the impact of BF algorithms on Bit Error Rate (BER) with varying numbers of antenna elements at the base station (BS). Simulation results indicate that while the algorithms demonstrate similar capabilities for interference cancellation, they differ in peak power values and beam widths. Furthermore, the accuracy of angle scanning and interference reveals that the algorithms have unique effects on directivity and gain, with the RLS algorithm showing slight improvements over the SMI and CMA algorithms. The findings highlight that the selection of beamforming algorithms, along with the number of antenna elements, significantly affects BER performance.

Integrated Electrically Small Monopole and Slotted Array Antenna Design for Next-Generation Microwave and mm-wave Wireless Systems

Abstract This paper presents a novel co-design approach for wireless applications, integrating mm-wave and microwave technologies. The design features two antennas where a slotted waveguide array is fabricated using 3D-printing technology with an AlMg10Si alloy resonating at mm-wave frequency band, while a printed monopole antenna resonating at microwave frequency band shares a common ground plane with the slotted waveguide array. The electrically small printed monopole is realized on an FR4 substrate, is suitable for WLAN bands, and achieves ease of integration with the antenna at the Ka-band owing to the low profile. The co-design approach is particularly advantageous for wireless applications as it enables the seamless integration of different frequency bands, enhancing system versatility and performance. The antenna achieves dual frequency band operation covering the Impedance bandwidth of 15.27% (5.08-5.92) and 14.56% (26.48-30.64) at microwave and Ka-band frequencies, respectively. The innovative use of materials and advanced fabrication techniques also underscores the design's potential for diverse high-performance wireless applications.

Dynamic reconfiguration of application and communication in Industry 4.0 with Digital Twin for enhancing flexibility

Abstract Industry 4.0 emphasizes the flexibility of production systems, requiring dynamic adaptation to varied product requirements. This paper presents a framework for managing production systems by integrating application and communication systems. Central to it is the use of Asset Administration Shell (AAS) to create Digital Twins of assets, enabling continuous adaptation and optimization of production processes through effective resource management. The paper discusses a use case involving negotiation between communication and application systems, proposing a model-based solution leveraging AAS. It details the implementation of the proposed model with AAS components, providing an analysis of the use case and an automation solution. Validation results show how the AAS can improve the performance and dependability of wireless communication systems.

On the Application of a Sparse Data Observers (SDOs) Outlier Detection Algorithm to Mitigate Poisoning Attacks in UltraWideBand (UWB) Line-of-Sight (LOS)/Non-Line-of-Sight (NLOS) Classification

The classification of the wireless propagation channel between Line-of-Sight (LOS) or Non-Line-of-Sight (NLOS) is useful in the operation of wireless communication systems. The research community has increasingly investigated the application of machine learning (ML) to LOS/NLOS classification and this paper is part of this trend, but not all the different aspects of ML have been analyzed. In the general ML domain, poisoning and adversarial attacks and the related mitigation techniques are an active area of research. Such attacks aim to hamper the ML classification process by poisoning the data set. Mitigation techniques are designed to counter this threat using different approaches. Poisoning attacks in LOS/NLOS classification have not received significant attention by the wireless communication community and this paper aims to address this gap by proposing the application of a specific mitigation technique based on outlier detection algorithms. The rationale is that poisoned samples can be identified as outliers from legitimate samples. In particular, the study described in this paper proposes a recent outlier detection algorithm, which has low computing complexity: the sparse data observers (SDOs) algorithm. The study proposes a comprehensive analysis of both conventional and novel types of attacks and related mitigation techniques based on outlier detection algorithms for UltraWideBand (UWB) channel classification. The proposed techniques are applied to two data sets: the public eWINE data set with seven different UWB LOS/NLOS different environments and a radar data set with the LOS/NLOS condition. The results show that the SDO algorithm outperforms other outlier detection algorithms for attack detection like the isolation forest (iForest) algorithm and the one-class support vector machine (OCSVM) in most of the scenarios and attacks, and it is quite competitive in the task of increasing the UWB LOS/NLOS classification accuracy through sanitation in comparison to the poisoned model.

Enhancing 5G Performance: A Study of an MIMO Antenna with Elliptical Ring Polarization

This paper discusses the design and evaluation of a four-element Multiple-Input, Multiple-Output (MIMO) antenna array with Circular Polarization (CP), tailored explicitly for sub-6 GHz 5G wireless systems. The proposed antenna utilizes an elliptical ring slot with a variable width in the ground plane and an asymmetric feed line layout to achieve orthogonal CP radiation in both the forward and backward directions. Three interconnected strip lines are incorporated into the ground plane for enhanced performance, increasing isolation and ensuring effective linkage between the antenna components and their respective grounds. The antenna exhibits strong isolation, a low Envelope Correlation Coefficient (ECC), and minimal Channel Capacity Loss (CCL), making it ideal for MIMO applications. The analysis confirms the antenna's stable CP gain and operational efficiency throughout the sub-6 GHz band, meeting the rigorous standards of contemporary 5G networks.

Detection of Beyond 5G Signal Detection Using Hybrid Method

ABSTRACTNonorthogonal Multiple Access (NOMA) is a promising fifth‐generation (5G) radio system candidate. NOMA's performance is further increased when integrated with Multiple inputs and Multiple Outputs (MIMO). The complexity of detecting NOMA signals also increases the utilization of numerous antennas, which upsurges the system's latency. In this article, we projected a hybrid signal detection algorithm combining zero forcing equalizer (ZFE) and minimum mean square error (MMSE) for the NOMA‐MIMO structure with the Rician and Rayleigh channel. For 16 × 16 and 64 × 64 MIMO‐NOMA, the Bit error rate (BER) is evaluated and compared for ZFE, MMSE, and Maximum likelihood (ML) detection and proposed ZFE‐MMSE algorithms. The simulation outcomes reveal that the projected ZFE‐MMSE detects the signal at low BER, outperforming the contemporary algorithms at complexity similar to MMSE and ZFE.

Robust Direction-of-Arrival Estimation using improved Coprime Array for Wireless Communication Applications

In wireless communication systems, robust and accurate Direction-of-Arrival (DOA) estimation is essential for tasks such as beamforming and interference suppression. This research presents advancements in the Multiple Signal Classification (MUSIC) algorithm leveraging enhanced coprime sensor arrays for DOA estimation. Coprime arrays, characterized by their non-uniform spacing derived from coprime integers, offer superior angular resolution compared to traditional uniform arrays. By exploiting this unique array geometry, the proposed method enhances the spatial localization capabilities of the MUSIC algorithm, thereby improving signal detection and mitigation of interference. Experimental validation demonstrates the efficacy of the approach in various signal environments, highlighting its potential to enhance the performance and reliability of wireless communication systems.

An innovative conditional self-attention generative adversarial network with fennec fox optimization approach for resource allocation in cognitive radio wireless communication systems

An innovative conditional self-attention generative adversarial network with fennec fox optimization approach for resource allocation in cognitive radio wireless communication systems

An NB-IoT Monitoring System for Digital Mobile Radio With Industrial IoT Performance and Reliability Evaluation

An NB-IoT Monitoring System for Digital Mobile Radio With Industrial IoT Performance and Reliability Evaluation

2-D deployment of aerial base stations: A simulation model to provide voice communication

Unmanned aerial vehicles (UAVs) offer a potential alternative for providing voice services in areas where communication is disrupted due to natural disasters. These UAVs can be configured as aerial base stations (ABSs), enabling the deployment of a temporary communications network. However, communication networks based on ABSs pose several significant challenges. One of these challenges involves addressing interruptions or limitations in network coverage caused by natural disasters. In such situations, there is a high likelihood that users within the affected area may be unable to communicate due to a lack of coverage. This is a complex problem because it depends on factors, such as the mobile user locations, the characteristics of the air-to-ground channel, and geographical details of the area. In this work, we propose an optimization model to determine the placement of a set of ABSs within a limited disaster area that maximizes the probability of successful voice services (PSVSs). This optimization model integrates a network evaluation model that analyzes the wireless environment at a specific time. The network evaluation model utilizes two-ray and Rayleigh channel models, enabling the simulation of a worst-case scenario for wireless communication systems. We evaluate the proposed optimization model using the (1+1)-evolution strategy with a one-fifth success rule. We explore various parameter configurations to understand their impact on algorithm performance. This analysis helps identify the configuration of the optimization model that yields the maximum PSVSs. Simulation results indicate that by appropriately configuring the evolution strategy algorithm and comparing random ABS locations with those determined ABS locations by the evolution strategy algorithm, the PSVS can be enhanced by an average of 60%.

Guest Editorial: 6G Wireless Technologies and Systems: Industrial Perspectives

Guest Editorial: 6G Wireless Technologies and Systems: Industrial Perspectives

A real-time seed spacing wireless remote online measurement system: Investigating factors influencing measurement accuracy, determining the optimal installation position for seed sensors to improve measurement precision

A real-time seed spacing wireless remote online measurement system: Investigating factors influencing measurement accuracy, determining the optimal installation position for seed sensors to improve measurement precision

Phosphine oxide functionalized porous aromatic frameworks enabled wireless bionic olfactory system with preconcentration capability for trace ammonia monitoring

Phosphine oxide functionalized porous aromatic frameworks enabled wireless bionic olfactory system with preconcentration capability for trace ammonia monitoring

E2R2D2: energy-efficient robust routing and data distribution protocol in wireless air pollution monitoring system

E2R2D2: energy-efficient robust routing and data distribution protocol in wireless air pollution monitoring system

A study of the magnetic field emissions from a vehicle-mounted wireless power transfer system for safe operation when charging EV batteries

A study of the magnetic field emissions from a vehicle-mounted wireless power transfer system for safe operation when charging EV batteries

Wireless NIR Four-Quadrant Detector System Based on PbS Collodial Quantum Dots

Wireless NIR Four-Quadrant Detector System Based on PbS Collodial Quantum Dots

Enzyme inactivation in broccoli of different sizes and densities using a pilot-scale 27.12 MHz radio frequency heating system

Enzyme inactivation in broccoli of different sizes and densities using a pilot-scale 27.12 MHz radio frequency heating system

A design method to optimize GaN-based class E resonant inductive wireless power transfer systems – application to non-mating connectors

A design method to optimize GaN-based class E resonant inductive wireless power transfer systems – application to non-mating connectors

IoT-Based Metal Detector Robot with Wireless Surveillance

Abstract: This project presents the design and development of an IoT-based metal detector robot equipped with wireless surveillance capabilities. The robot is designed to autonomously navigate its environment while detecting metallic objects underground, with real-time monitoring provided through a wireless camera system. The core components of the system include a metal detector sensor, an ESP8266 NodeMCU for wireless communication, an L298 motor driver for controlling the robot’s movement, and a surveillance camera for live video streaming. The system is powered by 3.7V battery cells, ensuring mobility and operational autonomy.The metal detector sensor scans for metallic objects, and upon detection, an alert is generated. Simultaneously, a wireless camera transmits real-time footage, allowing remote monitoring and control via a web interface or mobile device. The robot's movement is controlled through a second ESP8266 module, enabling wireless command inputs for navigation.This robot is envisioned for use in security applications, such as detecting landmines or hazardous metallic objects in sensitive areas, as well as for archaeological and construction projects. The integration of IoT technology enhances the robot’s operational range and effectiveness, providing a scalable solution for remote metal detection and surveillance.The integration of IoT technology significantly enhances the system's operational efficiency and range, enabling seamless remote control and monitoring. This innovation not only improves safety in hazardous conditions but also increases the effectiveness of metal detection and surveillance tasks in diverse environments