Synchronization Accuracy Research Articles

Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks

Power Line Communications-Artificial Intelligence of Things (PLC-AIoT) combines the low cost and high coverage of PLC with the learning ability of AI to provide data collection and transmission capabilities for PLC-AIoT devices in smart parks. With the development of smart parks, their emerging services require secure and accurate time synchronization of PLC-AIoT devices. However, the impact of attackers on the accuracy of time synchronization cannot be ignored. To solve the aforementioned problems, we propose a tampering attack-aware Deep Q-Network (DQN)-based time synchronization algorithm. First, we construct an abnormal clock source detection model. Then, the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway. Finally, the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIoT in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights. Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.

Timing Synchronization Based on Supervised Learning of Spectrogram for OFDM Systems

This paper proposes a supervised convolutional neural network (CNN) based symbol timing synchronization method using the spectrogram image for preamble-less orthogonal frequency division multiplexing (OFDM) systems. With the development of mobile terminals, OFDM has become an increasingly widespread fundamental technology for wireless communications. While OFDM can achieve high-speed transmission, it is sensitive to synchronization timing for decoding. Thus, the accurate synchronization timing estimation method has become essential for reliable communication. Conventional synchronization timing estimation methods without the preamble lack investigations of estimation accuracy under varying environments, comprehensive performance evaluation, and robustness to Doppler shift. Focusing on the spectrum fluctuations observed when synchronization errors occur, our proposed approach is to train the CNN using spectrogram images to find accurate synchronization points even in noisy and fluctuating environments. The simulation results show that the proposed method achieves better synchronization accuracy than other existing methods. Furthermore, it shows the near-optimal bit error rate (BER) characteristics and superior processing time for BER in an environment close to realistic settings, such as broader synchronization timing and various Doppler shifts.

Development of SDR-based network positioning technology. LTE reference signals reception and processing validation

Introduction. The positioning of devices according to the base stations reference signals of LTE cellular radio networks deployed everywhere is an important area of research and development that is in demand due to dense urban development with unreliable signal reception from global navigation satellite systems. The instrument for experimental approbation of technical solutions is the software and hardware of the SDR software defined radio technology. This work continues the study on the use of SDR technology for network positioning problems in terms of the experimental testing of the device for receiving reference signals of the LTE standard.Materials and methods. The correctness of the software implementation of the LTE reference signal processing procedures was verified in the course of laboratory tests that showed the accuracy of primary measurements in units of meters allowing us to speak about the satisfactory performance of the implemented SDR layout of the user device that receives the LTE reference signals.Results. Insufficient synchronization accuracy of SDR models of base stations for navigation tasks confirmed the need for hardware-software implementation of the subsystem for generating LTE reference signals in HDL for FPGAs.Discussion and conclusions. The next stage of research in the field of SDR network positioning technology is field testing of the implemented sub-system for generating LTE reference signals with sufficient synchronization accuracy of eNB models for navigation tasks.

Learning-based sliding mode synchronization for fractional-order Hindmarsh-Rose neuronal models with deterministic learning.

In recent years, extensive research has been conducted on the synchronous behavior of neural networks. It is found that the synchronization ability of neurons is related to the performance of signal reception and transmission between neurons, which in turn affects the function of the organism. However, most of the existing synchronization methods are faced with two difficulties, one is the structural parameter dependency, which limits the promotion and application of synchronous methods in practical problems. The other is the limited adaptability, that is, even when faced with the same control tasks, for most of the existing control methods, the control parameters still need to be retrained. To this end, the present study investigates the synchronization problem of the fractional-order HindmarshRose (FOHR) neuronal models in unknown dynamic environment. Inspired by the human experience of knowledge acquiring, memorizing, and application, a learning-based sliding mode control algorithm is proposed by using the deterministic learning (DL) mechanism. Firstly, the unknown dynamics of the FOHR system under unknown dynamic environment is locally accurately identified and stored in the form of constant weight neural networks through deterministic learning without dependency of the system parameters. Then, based on the identified and stored system dynamics, the model-based and relearning-based sliding mode controller are designed for similar as well as new synchronization tasks, respectively. The synchronization process can be started quickly by recalling the empirical dynamics of neurons. Therefore, fast synchronization effect is achieved by reducing the online computing time. In addition, because of the convergence of the identification and synchronization process, the control experience can be constantly replenished and stored for reutilization, so as to improve the synchronization speed and accuracy continuously. The thought of this article will also bring inspiration to the related research in other fields.

SEP Optimization of Power System Location and Timing Module Based on MLE-KNN Synthesis Algorithm

To ensure the safe operation of the power system, it is necessary to monitor and manage all kinds of power facilities. Real-time power monitoring can play a role in the early warning of geographical disasters. At the transmission end, the state detection and fault location of transmission lines are related to the normal operation of the power system. The precise time synchronization of the power system can be guaranteed through the satellite positioning time service, so that the time of various power operation actions is consistent. The accuracy can reach several microseconds, which provides a basis for the analysis of power grid operation. In this paper, by installing BeiDou functional modules in power equipment and developing the BeiDou operation platform for the distribution network, the precise management of power timing and positioning is realized by docking with the geographic information systems platform of the power grid. The three-dimensional sphere error probability (SEP) algorithm is selected to evaluate the positioning error data. Based on the three traditional SEP calculation methods, the maximum likelihood estimation algorithm is optimized and improved, which can achieve nanosecond synchronization accuracy. It can also be applied to other precision of synchronization scenarios of the power system to meet the development needs of the future clock system of the power system. Through the simulation of experimental data and comparison with other algorithms, the accuracy is verified and the reliable estimation of parameters is realized. Considering the information loss caused by dimension reduction evaluation, the simulation analysis in this paper is compared with other methods, and the accuracy is significantly improved. The power system positioning and timing module developed in this paper can not only be used in the power system but also has a certain reference and application value for other devices in the same industry that need timing and positioning services.

A feasibility study of 5G positioning with current cellular network deployment

This research examines the feasibility of using synchronization signals broadcasted by currently deployed fifth generation (5G) cellular networks to determine the position of a static receiver. The main focus lies on the analysis of synchronization among the base stations of a real 5G network in Milan, Italy, as this has a major impact on the accuracy of localization based on time of arrival measurements. Understanding such properties, indeed, is fundamental to characterize the clock drifts and implement compensation strategies as well as to identify the direct communication beam. The paper shows how the clock errors, i.e., inaccurate synchronization, among 5G base stations exhibit a significant bias, which is detrimental for precise cellular positioning. By compensating the synchronization errors of devices’ clocks, we demonstrate that it is in principle possible to localize a static user with an accuracy of approximately 8–10 m in non-obstructed visibility conditions, for urban and rural scenarios, using the deployed 5G network operating at 3.68 GHz and relying on broadcast signals as defined by 5G Release 15 standard. This work has been funded by the European Space Agency (ESA) Navigation Innovation and Support Program (NAVISP) Element 2 pillar which aims at improving the competitiveness of the industry of the participating States in the global Positioning, Navigation and Timing (PNT) market.

Smart Pill Box with Voice Announcement and Wrist Band Accessory

A project has been developed to address the challenges faced by individuals in managing complex medication regimens independently. The solution incorporates various components, including the NodeMCU ESP32 Wroom, RTC module, GSM module, Smart Pill Box dispenser, and a wristband. The NodeMCU ESP32 Wroom module enables seamless communication and synchronization between the Smart Pill Box Dispenser and the wristband accessory. By leveraging its Wi-Fi capabilities, the NodeMCU ESP32 Wroom ensures that the dispenser and wristband stay connected, facilitating real-time notifications related to medication schedules and reminders. To ensure accurate timekeeping and synchronization, an RTC (Real-Time Clock) module is integrated into the system. The GSM module is utilized for the SMS alert functionality of the system. In the event that a patient neglects to take their medication, the GSM module sends an alert message to a designated person, notifying them of the situation. A wristband accessory is a piece of equipment that the patient wears constantly. It includes LCD display, MAX30102 sensor, body temperature sensor, and vibrator, among other things. The MAX30102 sensor measures the patient's heart rate, SpO2, and temperature, while the temperature sensor measures the patient's body temperature. These values are all shown on an LCD screen. By leveraging IoT technology, the solution enhances medication adherence, improves safety, and reduces the need for constant medical supervision, thereby promoting the well-being and independence of the users.

ECG Matching: An Approach to Synchronize ECG Datasets for Data Quality Comparisons.

Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.

Cathodal high-definition transcranial direct current stimulation (HD-tDCS) of the left ventral prefrontal cortex (vPFC) interferes with conscious error correction

Precise motor timing requires the ability to flexibly adapt one’s own movements with respect to changes in the environment. Previous studies suggest that the correction of perceived as compared to non-perceived timing errors involves at least partially distinct brain networks. The dorsolateral prefrontal cortex (dPFC) has been linked to the correction of perceived timing errors and evidence for a contribution of the ventrolateral PFC (vPFC) specifically to the correction of non-perceived errors exists. The present study aimed at clarifying the functional contribution of the left vPFC for the correction of timing errors by adopting high-definition transcranial direct current stimulation (HD-tDCS). Twenty-one young healthy volunteers synchronized their right index finger taps with respect to an isochronous auditory pacing signal. Perceivable and non-perceivable step-changes of the metronome were interspersed, and error correction was analyzed by means of the phase-correction response (PCR). In subsequent sessions anodal and cathodal HD-tDCS was applied to the left vPFC to establish a brain-behavior relationship. Sham stimulation served as control condition. Synchronization accuracy as well as error correction were determined immediately prior to and after HD-tDCS. The analysis suggests a detrimental effect of cathodal HD-tDCS distinctively on error correction in trials with perceived timing errors. The data support the significance of the left vPFC for error correction in the temporal domain but contradicts the view of a role in the correction of non-perceived errors.

Joint Synchronization and Range Estimation With Correlated Arrival Times in Molecular Communication Networks

Time synchronization is needed in information exchange and collaboration among nanomachines for molecular communication networks. The time of arrival-based synchronization method requires the range information between the transmitter nanomachine (TN) and the receiver nanomachine (RN) in order to improve the accuracy of clock synchronization. The range information between the nanomachines helps to choose the optimal transmission rate. In contrast to the existing methods, this article proposes a joint clock offset and range estimation with correlated arrival times based on the maximum likelihood estimator. The RN uses the molecules' transmission and correlated arrival times to estimate the clock offset and range between the TN and RN. Even with correlated arrival times, the individual clock offset estimation performance is comparable to independent arrival times performance. Notably, the joint estimation problem with correlated arrival times is generic and realistic for molecular applications.

Unsupervised Deep-Learning for Distributed Clock Synchronization in Wireless Networks

One of the major factors which limits the throughput in wireless communications networks is the accuracy of time synchronization between the nodes in the network. Synchronization methods based on pulse-coupled oscillators (PCOs) have the advantage of simple implementation and achieve high accuracy when the nodes are closely located. However, such schemes tend to have poor synchronization performance for distant nodes, as well as in the presence of clock frequency offsets between the nodes. In this paper we present a novel PCO-based Deep neural network (DDN)-Aided Synchronization Algorithm coined DASA. We design DASA as a novel low-complexity and interpretable architecture by converting classic PCO-based synchronization into <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a trainable discriminative model</i> . To enable DASA to operate in dynamic settings, we propose a novel, unsupervised, distributed, fast <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">online</i> training scheme which is able to train DASA <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">within a few sampling instances, locally</i> , thereby avoiding the need for information exchange between the nodes or for a central node for coordination. DASDA is demonstrated to achieve an improvement by a factor greater than ten compared to the classic reference scheme. Lastly, we propose another novel, distributed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">offline</i> training scheme for DASA, which is demonstrated to offer a tradeoff between performance and simplicity of deployment compared to the online training scheme, yet, at the same time, DASA with offline training still achieves superior performance compared to the classic reference scheme.

Precise GNSS Time Synchronization With Experimental Validation in Vehicular Networks

Time synchronization utilizing the Global Navigation Satellite System (GNSS) is being increasingly investigated for vehicular networks. Due to GNSS signal blockages, the availability and accuracy of GNSS timing solutions in various road settings is a recognized challenge. With the recent improvement of Multi-GNSS technology and the increased capacity of consumer-grade receivers, the application of GNSS in vehicular environments has brightened up. This paper systematically analyzes the required time synchronization of vehicular networks and presents a GNSS-based time synchronization solution. It also experimentally demonstrates the availability and capabilities of GNSS time synchronization using commercial-grade GNSS receivers and off-the-shelf communication devices. Our experiments show that the timing accuracy of an individual vehicular node can be as good as ±2 microseconds, resulting in synchronization accuracy of sub-10 microseconds among nodes. A momentary complete outage of the GNSS time solution due to signal blockage on the road adds clock error, leading to synchronization inaccuracy of up to sub-20 microseconds. This level of inaccuracy still meets the desired requirement for most applications in vehicular communication.

Modeling and feedforward control of filament advancement and retraction in material extrusion additive manufacturing

Material extrusion (MatEx) is the predominant of the available additive manufacturing (AM) methods. High-quality MatEx AM process demands accurate synchronization between motion control and extrusion control. However, the synchronization is challenging due to nonlinearities of the flow inside the nozzle. One of the most common synchronization defects is the inaccuracies at extrusion starts and stops. To address this, material retraction and advancement processes must be applied and controlled accurately. However, feedback extrusion control is limited by the difficulties in sensing the real-time extrusion rate, and existing feedforward (FF) extrusion control methods only rely on models that are developed and identified under continuous extrusion thus do not account for the retraction and advancement processes. Besides, another method that commercial printers commonly employ to address the extrusion problem is to find the optimal printing parameter set through sequential printing tests. However, this method does not generalize well for different materials and extruders, and it could be time and material-consuming. To address these problems in adopting FF control, this paper presents a control-oriented phenomenological model (P-model) that characterizes the extrusion dynamics during the retraction and advancement processes mathematically and a model-based FF control method to compensate the dynamics by altering both the motion and extrusion command. To validate the proposed model, a novel experimental setup (Setup 1) is proposed by retrofitting a MatEx standard printer with a servo motor on its material feeding gear to reveal the extrusion force during the process. The proposed model is validated on Setup 1 by demonstrating an accurate mathematical characterization of the extrusion dynamics and in the meantime revealing the consistency between the extrusion (external) and force (internal) behavior. Additionally, the practicality and effectiveness of the P-model and the P-model-based control method are demonstrated on an unmodified commercial printer (Setup 2). By using Setup 1, the proposed control method demonstrated up to 36.61% and 90.55% reduction in deposition error during advancement and retraction, respectively when compared to a standard FF extrusion control approach. Moreover, up to 39.34% and 35.26% reductions in deposition error during advancement and retractions are observed with the proposed controller when compared to using the standard extrusion profile with a well-tuned retraction and advancement parameters set from a commercial slicer software on Setup 2. Lastly, the potential of the proposed method for enhancing printing accuracy in real-world printing is demonstrated through a practical printing application.

Enhancement of Precise Underwater Object Localization

AbstractUnderwater communication applications extensively use localization services for object identification. Because of their significant impact on ocean exploration and monitoring, underwater wireless sensor networks (UWSN) are becoming increasingly popular, and acoustic communications have largely overtaken radio frequency broadcasts as the dominant means of communication. The two localization methods that are most frequently employed are those that estimate the angle of arrival and the time difference of arrival. The military and civilian sectors rely heavily on UWSN for object identification in the underwater environment. As a result, there is a need in UWSN for an accurate localization technique that accounts for dynamic nature of the underwater environment. Time and position data are the two key parameters to accurately define the position of an object. Moreover, due to climate change there is now a need to constrain energy consumption by UWSN to limit carbon emission to meet net‐zero target by 2050. To meet these challenges, we have developed an efficient localization algorithm for determining an object position based on the angle and distance of arrival of beacon signals. We have considered the factors like sensor nodes not being in time sync with each other and the fact that the speed of sound varies in water. Our simulation results show that the proposed approach can achieve great localization accuracy while accounting for temporal synchronization inaccuracies. When compared to existing localization approaches, the mean estimation error (MEE) (MEE) and energy consumption figures, the proposed approach outperforms them. The MEEs is shown to vary between 84.2154 and 93.8275 m for four trials, 61.2256 and 92.7956 m for eight trials, and 42.6584 and 119.5228 m for 12 trials. Comparatively, the distance‐based measurements show higher accuracy than the angle‐based measurements.

Design of a Large-Format Low-Light Imaging System Based on the RGB Filter Wheel

In order to capture true-color information of distant targets under extremely low light, a large-format low-light imaging system is designed based on an RGB filter wheel. By decomposing the system indicators, this study proposes a method for acquiring low-light true-color images using a large-aperture, low-distortion optical lens combined with an RGB filter wheel capable of multi-line sequential exposure. The optical field segmentation is achieved using a four-panel optical reflective prism, and the images from four high-sensitivity SCOMS detectors are stitched together to form a composite image. The working principle of the system is explained, and the low-light imaging capability is thoroughly evaluated. The dimensions and rotation speed of the filter wheel are then calculated in detail, ensuring accurate synchronization of the filter wheel’s speed and exposure time. The calculation method for the parameters of the four-panel reflective prism structure is investigated, mathematical expressions for the geometric parameters of the prism assembly are provided, and a prism assembly suitable for four-way spectral separation is designed. Based on the research and design results, a large-swath-width, low-light true-color imaging system is developed that is suitable for an environmental illuminance of 0.01 lux. The system achieves a ground pixel resolution of 0.5 m (at an altitude of 5 km) and an effective image resolution of 4 K × 4 K, and is capable of accurately reproducing target color information. Laboratory and field flight tests verified that the large-swath-width images obtained by the imaging system are clear, with high contrast and resolution. After image fusion and spectral registration, the color images exhibit full saturation and high fidelity, meeting the requirements of low-light true-color imaging under airborne conditions. The design methodology of this low-light imaging system can serve as a reference for the development of airborne low-light imaging equipment.

Clock synchronization based on pulse with propagation delay eliminated in wireless sensor networks

AbstractClock synchronization is indispensable for numerous applications of wireless sensor networks (WSNs). When no common reference clock is available, the nodes must employ distributed synchronization techniques. This paper proposes, a distributed pulse‐based clock synchronisation approach, wherein the propagation delay is eliminated through signal ping‐pongs between neighbouring nodes. Such an approach can jointly estimate the clock skew and offset without requiring any reference clock. The whole synchronization process is completed at the physical (PHY) layer, effectively avoiding the random delay caused by packet queuing and retransmission. Simulation results show that the proposed approach can achieve higher synchronization accuracy compared with other existing methods.

Timing synchronization based on Radon–Wigner transform of chirp signals for OTFS systems

Accurate timing synchronization is fundamental for the orthogonal time frequency space (OTFS) system to work properly, but the severe Doppler effect makes it a challenging task in high-mobility environments and high carrier frequency systems. To tackle this challenge, we propose a timing synchronization algorithm based on the Radon-Wigner transform (RWT) of chirp signals for OTFS modulation systems in high-mobility environments, which makes full use of the anti-Doppler performance of chirp signals and the energy aggregation characteristics of RWT to achieve accurate timing synchronization in high-Doppler conditions. Firstly, a training sequence consisting of a dual-chirp signal is transformed from the time domain to the delay-Doppler domain and then superimposed on the user data at the transmitter side. Subsequently, the timing synchronization of the OTFS system is implemented by detecting the peak value of the chirp signal after RWT and computing the difference in peak position between the transmitted and received chirp signals. Simulation results demonstrate that the proposed scheme offers a superior performance gain in low signal-to-noise ratio and high-Doppler conditions.

A high-precision synchronization system based on custom benchmarks

In order to meet the requirements of high synchronization of information flow for the cooperation among subsystems of spacecraft and of autonomous operation and management of spacecraft, this article proposes a synchronization system design based on a custom synchronization benchmark. This plan provides a custom synchronization benchmark design method and design constraints and proposes synchronization strategies for different system requirements. On this basis, a high-precision synchronization system design scheme is proposed. By conducting tests, the synchronization error compliance of the synchronization system is verified based on custom benchmarks. This design does not rely on the availability of GPS signals, and the synchronization system design is triggered by the requirement for synchronization accuracy. This method can be applied to spacecraft onboard systems and ground testing systems with extensive application value.

Adaptive backstepping fuzzy synchronization control of fractional-order chaotic systems with input saturation and external disturbances

In this paper, an adaptive backstepping command filtered controller is proposed for a class of uncertain strict feedback fractional-order chaotic systems with input saturation and external disturbances. A command filter is designed to avoid the “explosion of complexity” problem in the conventional backstepping technique. To tackle with filter error and improve synchronization accuracy, a compensation mechanism is provided. Meanwhile, fuzzy logic systems are utilized to approximate unknown functions, and disturbance observers are constructed to reduce the impact of unknown disturbances. In particular, to reduce the chattering phenomenon, a smooth function rather than the sign function is used in the controller design, and the stability of the closed-loop system can be guaranteed by the proposed synchronization controller. A simulation study is provided to confirm the practicality and validity of the proposed method.

Off-Board Bidirectional Electric Vehicle Charger Featuring Reactive Power Compensation and Reduced Total Harmonic Distortion for Enhanced Efficiency and Power Quality

The purpose of this study is to explain a recently developed off-board battery charger system for electric vehicles (EVs) that is capable of supporting grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations, in addition to adjusting for reactive power. A utility-connected AC-DC cascaded H-bridge (CHB) converter is included into the system design. This converter is responsible for controlling the power exchange that occurs between the grid and the battery while a bidirectional DC-DC converter is located at the rear end of the system. There is galvanic separation between the grid and the user end of the charger, which is included for the purpose of increasing safety. In order to manage electric vehicle power and battery current, the suggested system makes use of an ANFIS controller. This controller adheres to active power orders for both G2V and V2G modes, and it also provides reactive power adjustment when it is necessary. Furthermore, a control algorithm that is based on an adaptive notch filter has been developed in order to estimate network phases and achieve accurate current synchronization without the need for phase-locked loops (PLLs). This has resulted in the simplification of controller design and an improvement in both the steady-state and dynamic performance of the system. The efficiency of the suggested system in regulating reactive power in V2G and G2V scenarios is shown by the experimental results that were achieved in a MATLAB environment.