Various Types Of Interference Research Articles

Joint Optimization of Relay Communication Rates in Clustered Drones under Interference Conditions

To address the issues of communication failure and inefficiency in clustered drone relay communication due to external malicious interference, this paper proposes a joint optimization method for relay communication rates under interference conditions for clustered drones. This method employs the following two-step processing framework: Firstly, the Discrete Soft Actor-Critic (DSAC) algorithm is used to train the relay drones for dynamic channel selection, effectively avoiding various types of interference. Simultaneously, the Bayesian optimization algorithm is applied to optimize the hyperparameters of the DSAC algorithm, further enhancing its performance. Subsequently, the modulation order, transmission power, trajectory of the relay drones, and power allocation factors of the clustered drones are jointly optimized. This complex problem is transformed into a convex subproblem for determining a solution, aiming to maximize the communication rate of the clustered drones. The simulation’s results demonstrate that the proposed algorithm exhibits excellent performances in terms of anti-interference capability, solution convergence, and stability. It effectively improves the mission efficiency of clustered drones under interference conditions and enhances their adaptability to dynamic environments.

Automating shareable cyber threat intelligence production for closed source software vulnerabilities: a deep learning based detection system

Software can be vulnerable to various types of interference. The production of cyber threat intelligence for closed source software requires significant effort, experience, and many manual steps. The objective of this study is to automate the process of producing cyber threat intelligence, focusing on closed source software vulnerabilities. To achieve our goal, we have developed a system called cti-for-css. Deep learning algorithms were used for detection. To simplify data representation and reduce pre-processing workload, the study proposes the function-as-sentence approach. The MLP, OneDNN, LSTM, and Bi-LSTM algorithms were trained using this approach with the SOSP and NDSS18 binary datasets, and their results were compared. The aforementioned datasets contain buffer error vulnerabilities (CWE-119) and resource management error vulnerabilities (CWE-399). Our results are as successful as the studies in the literature. The system achieved the best performance using Bi-LSTM, with F1 score of 82.4%. Additionally, AUC score of 93.0% was acquired, which is the best in the literature. The study concluded by producing cyber threat intelligence using closed source software. Shareable intelligence was produced in an average of 0.1 s, excluding the detection process. Each record, which was represented using our approach, was classified in under 0.32 s on average.

Envelope Extraction Algorithm for Magnetic Resonance Sounding Signals Based on Adaptive Gaussian Filters

Magnetic resonance sounding is a geophysical method for quantitatively determining the state for groundwater storage that has gained international attention in recent years. However, the practical acquisition of magnetic resonance sounding signals, which are on the nanovolt scale, is susceptible to various types of interference, such as power-line harmonics, random noise, and spike noise. Such interference can degrade the quality of magnetic resonance sounding signals and, in severe cases, be completely drowned out by noise. This paper introduces an adaptive Gaussian filtering algorithm that is well-suited for handling intricate noise signals due to its adaptive solving characteristics and iterative sifting approach. Notably, the algorithm can process signals without relying on prior knowledge. The adaptive Gaussian filtering algorithm is applied for the envelope extraction of noisy magnetic resonance sounding signals, and the reliability and effectiveness of the method are rigorously validated. The simulation results reveal that, even under strong noise interference (with original signal-to-noise ratios ranging from −7 dB to −25 dB), the magnetic resonance sounding signal obtained after algorithmic processing is compared to the ideal signal, with 16 sets of data statistics, and the algorithm ensures an initial amplitude uncertainty within 4nV and restricts the uncertainty of the relaxation time within a 6 ms range. The signal-to-noise ratio can be boosted by up to 53 dB. The comparative assessments with classical algorithms such as empirical mode decomposition and the harmonic modeling method confirm the superior performance of the adaptive Gaussian filtering algorithm. The processing of the field data also fully proved the practical application effects of the algorithm.

Relative navigation with Bayesian range estimation

The applications of multiple unmanned aerial vehicles (UAVs) require high-precision and reliable relative navigation for flight formation, collision avoidance, and mission performance. Providing high-precision relative navigation is possible by fusing the observations of inertial measurement units, global navigation satellite system receivers, and radio-ranging modules. However, radio-ranging is vulnerable to various types of interference, including additive noise, nonlinear propagation, and multi-user interference. At the same time, UAVs strict energy constraints force us to look for ways to increase interference immunity without increasing the transmitting power of radio-ranging modules. This work is about improving the noise immunity of relative navigation by using a scheme tightly coupled with radio ranging and Bayesian range estimation. We describe the proposed scheme and also carry out a comparative simulation of tightly coupled and conventional, loosely coupled schemes. According to the simulation, a tightly coupled scheme has a quarter smaller RMS error compared to a loosely coupled one at an SNR below -7 dB. The obtained results demonstrate the prospects for further development of the proposed scheme.

Robust battery lifetime prediction with noisy measurements via total-least-squares regression

—Machine learning technologies have gained significant popularity in rechargeable battery research in recent years, and have been extensively adopted to construct data-driven solutions to tackle multiple challenges for energy storage in embedded computing systems. An important application in this area is the machine learning-based battery lifetime prediction, which formulates regression models to estimate the remaining lifetimes of batteries given the measurement data collected from the testing process. Due to the non-idealities in practical operations, these measurements are usually impacted by various types of interference, thereby involving noise on both input variables and regression labels. Therefore, existing works that focus solely on minimizing the regression error on the labels cannot adequately adapt to the practical scenarios with noisy variables. To address this issue, this study adopts total least squares (TLS) to construct a regression model that achieves superior regression accuracy by simultaneously optimizing the estimation of both variables and labels. Furthermore, due to the expensive cost for collecting battery cycling data, the number of labeled data samples used for predictive modeling is often limited. It, in turn, can easily lead to overfitting, especially for TLS, which has a relatively larger set of problem unknowns to solve. To tackle this difficulty, the TLS method is investigated conjoined with stepwise feature selection in this work. Our numerical experiments based on public datasets for commercial Lithium-Ion batteries demonstrate that the proposed method can effectively reduce the modeling error by up to 11.95 %, compared against the classic baselines with consideration of noisy measurements.

Representation of data by their residual images during transmission and reception of messages in wireless information and telecommunication systems under interference conditions

The article is devoted to the development of new methods used in information technologies for monitoring the results of telemetry in conditions of various types of interference, the need for which is most acute in the development of automated systems for monitoring the technical condition of complex complexes and systems. To resolve the contradictions, a new non-traditional approach is proposed that uses diagnostic methods for obtaining estimates of measurement results, the basis of which is the non-traditional representation of measurement data by their residual images during data transmission and reception in wireless information communications.

Influence of the atmosphere on the spread of laser radiation

The article is devoted to the problem of protecting information from being read by an optoelectronic channel by studying the influence of atmospheric parameters on the spread of laser radiation. The paper considers key aspects of radiation attenuation due to scattering and absorption by air gases and aerosol particles. It is shown that the efficiency of the probing laser beam depends on extreme climatic conditions, and due to scattering and absorption, the power of the laser beam will decrease as it spreads through the atmosphere. Taking into account the peculiarities of the passage of a laser beam through the atmosphere and the influence of various types of interference on the probing signal, it is possible to predict its attenuation and blocking, namely, for reading confidential speech information, lasers with radiation located in the parts of the atmospheric spectrum occupied by wide windows of transparency should be taken for the appropriate weather conditions; to protect information from being read by an optoelectronic channel, it is necessary to use parameters of the external environment that prevent direct access of the laser beam to the object of information. The presented author's vision of research into the influence of the atmosphere on the spread of laser radiation will allow us to apply the results, ideas, and proposals summarized in this article to solve current problems in the field of information protection.

AUTOMATIC DETECTION AND RECOGNITION OF DIGITAL MODULATED SIGNALS USING A NEURAL NETWORK

Issues on automatic detection and recognition of digital modulated signals are becoming increasingly relevant in modern communication systems. These processes play a key role in ensuring reliable and efficient communication in a wide range of areas, from mobile communication to broadcasting and satellite systems. The importance of these processes continues to grow with the increase in the amount of data transmitted through these systems and with the development of new communication technologies. Accurate detection and classification of signals allow communication systems to correctly interpret the transmitted information, which, in turn, ensures the reliability and efficiency of data transmission. This is especially important in conditions when signals are subject to various types of interference and distortions. Therefore, the development and improvement of the methods for automatic detection and recognition are becoming increasingly important for ensuring high-quality communication. The present article presents a neural network-based system capable of automatically detecting signals with a single carrier frequency in the range up to 6 GHz and classifying four types of digitally modulated signals: BPSK, QPSK, 16-QAM, and 64-QAM. The system is capable of operating in the presence of additive white Gaussian noise, phase and frequency offset in the received signal. The algorithms for detection and recognition of signals, developed in the LabVIEW software environment are presented. The architecture and hyperparameters of the neural network allowing quick and efficient training of the network are described. These algorithms and training methods can be applied and adapted for other systems and applications, making them very useful for a wide range of tasks. The system was tested both on simulated signals and in a real communication channel. The results obtained confirm the effectiveness of the proposed methods and emphasise their potential for further application and research.

Особенности функционирования СВЧ-радиометров в условиях внешних помех.

The influence of external disturbances on the sensitivity and dynamic range of the microwave radiothermograph is considered. The results of an experimental study of the interference situation in the range up to 3 GHz are presented. The diagram of the spectral density of interference adjacent to radio astronomy windows is analyzed. The features of real observed disturbances are investigated. The classification of possible disturbances according to their characteristics is given. Algorithms for discrimination of various types of interference are considered. The sensitivity and dynamic range of the microwave radiometer are evaluated using the pulse noise suppression algorithm.

Application of Incoherent Multi-Frequency Signals for Information Transmission in a Nonstationary Hydroacoustic Environment

A class of digital incoherent methods of information transmission based on multi-frequency signals for mobile underwater complexes is presented, which does not require regular and accurate estimation of channel parameters and is a priori resistant to various types of interference in nonstationary hydroacoustic communication channels, and is oriented to solving communication and navigation problems for underwater robotic complexes. The limitation of spectral efficiency of such multi-frequency systems of information transmission by the value of 0.5 bits/s/Hz in various frequency ranges, nonstationary hydrological conditions, with achievement of the maximum range at acceptable levels of error probability during information decoding is shown. The operability of the proposed class of multi-frequency multiplexing methods was confirmed by numerical and in situ sea experiments on the shelf at distances from 2.5 to 7 km with the mutual drifting of ships and with sea waves of up to 3 points.

Gesture Detection and Recognition Based on Object Detection in Complex Background

In practical human–computer interaction, a hand gesture recognition method based on improved YOLOv5 is proposed to address the problem of low recognition accuracy and slow speed with complex backgrounds. By replacing the CSP1_x module in the YOLOv5 backbone network with an efficient layer aggregation network, a richer combination of gradient paths can be obtained to improve the network’s learning and expressive capabilities and enhance recognition speed. The CBAM attention mechanism is introduced to filtering gesture features in channel and spatial dimensions, reducing various types of interference in complex background gesture images and enhancing the network’s robustness against complex backgrounds. Experimental verification was conducted on two complex background gesture datasets, EgoHands and TinyHGR, with recognition accuracies of mAP0.5:0.95 at 75.6% and 66.8%, respectively, and a recognition speed of 64 FPS for 640 × 640 input images. The results show that the proposed method can recognize gestures quickly and accurately with complex backgrounds, and has higher recognition accuracy and stronger robustness compared to YOLOv5l, YOLOv7, and other comparative algorithms.

Automatic Generation of Interference-Free and Posture-Smooth Toolpath for Robotic Belt Grinding of Complex Workpieces

Robotic belt grinding has shown great potential to achieve automatic machining of high-precision parts. However, its productivity in machining complex parts has been greatly limited by the problem that interference-free and posture-smooth toolpath planning is still a time-consuming and labor-intensive job. Therefore, this work presents a fully automatic and practical approach to facilitate interference-free and posture-smooth toolpath planning for robotic belt grinding of complex parts. With this approach, the interference correction spaces in two common belt grinding modes, namely, wheel face grinding and wheel edge grinding, are first established, where various types of interferences and their corresponding correction strategies are modeled. Then, two B-spline posture curves, which represent the rotational motion and translational motion of the workpiece for correcting interference throughout the entire cutter contact curve, are presented. With the two B-spline curves, a toolpath planning algorithm for robotic belt grinding of complex parts is further developed based on surface partitioning and iteratively correcting interference and smoothing grinding postures. The effectiveness and practicability of the proposed approach are validated by simulations and experimental studies, which demonstrates that the authors’ approach can significantly improve the toolpath planning efficiency and ground surface quality for complex parts as compared with the leading commercial computer-aided manufacturing (CAM) software.

Measures for attenuation of interference at the level of design of the measuring system of spacecraft

One of the primary tasks in the development of temperature control interface modules used as part of onboard equipment for measuring systems on spacecraft for various purposes is to justify a set of measures to ensure their noise immunity, taken at the levels design of the measuring system, measuring device and temperature control interface module. Such a justification involves an assessment of the effectiveness of possible methods for attenuating various types of interference affecting the measuring system, which determine the electromagnetic environment on the spacecraft. The article is devoted to the consideration of interference mitigation measures at the design level of the measuring system, which should be taken to ensure the required noise immunity of the temperature control interface module in combination with measures taken at other design levels. It is shown that in order to ensure the required noise immunity of the temperature control interface modules, it is necessary at the level of the measuring system design to provide for measures to mitigate interference in the power cable and in the measuring cables. In the power cable, it is possible to attenuate interference by reducing the impedance of the common electrostatic shield and the resistance of the connection of the wires of the on-board power buses, as well as by twisting the wires in the form of a twisted pair. In measuring cables, it is possible to attenuate interference by reducing the impedance of the common electrostatic shield and the resistance of communication wires of communication lines, introducing an additional electrostatic shield for individual groups of wires of communication lines, and using pair or quadruple twist in individual groups of wires.

Sapphire Fiber High-Temperature Sensor Based on Colorimetric Method

A colorimetric high temperature sensor based on a sapphire fiber bundle is reported in this work. The radiation voltage ratio of two neighboring wavelengths is used to detect the temperature. The sapphire fiber bundle can increase the efficiency of radiation light collection. To improve mechanical properties and structural stability, the sensor probe is encased in a ceramic tube. Experimental results show that the sensor can be used in a wide temperature range of 648 K-1800 K with a measuring accuracy range from 0.4 to 1.8 percent. The sapphire fiber colorimetric high temperature sensor effectively reduces the effects of various types of interferences in the measurement process thanks to the calibration procedure. In the field of high temperature sensing, the proposed colorimetric sapphire fiber high temperature sensor offers various application potentials.

Toxicity of Carbon Nanomaterials-Towards Reliable Viability Assessment via New Approach in Flow Cytometry.

The scope of application of carbon nanomaterials in biomedical, environmental and industrial fields is recently substantially increasing. Since in vitro toxicity testing is the first essential step for any commercial usage, it is crucial to have a reliable method to analyze the potentially harmful effects of carbon nanomaterials. Even though researchers already reported the interference of carbon nanomaterials with common toxicity assays, there is still, unfortunately, a large number of studies that neglect this fact. In this study, we investigated interference of four bio-promising carbon nanomaterials (graphene acid (GA), cyanographene (GCN), graphitic carbon nitride (g-C3N4) and carbon dots (QCDs)) in commonly used LIVE/DEAD assay. When a standard procedure was applied, materials caused various types of interference. While positively charged g-C3N4 and QCDs induced false results through the creation of free agglomerates and intrinsic fluorescence properties, negatively charged GA and GCN led to false signals due to the complex quenching effect of the fluorescent dye of a LIVE/DEAD kit. Thus, we developed a new approach using a specific gating strategy based on additional controls that successfully overcame all types of interference and lead to reliable results in LIVE/DEAD assay. We suggest that the newly developed procedure should be a mandatory tool for all in vitro flow cytometry assays of any class of carbon nanomaterials.

Features of ensuring noise immunity of interface modules for temperature control in measuring instruments of spacecraft

An important stage in the development of temperature control interface modules for measuring instruments, implemented according to the main-modular principle of construction on the basis of a central instrument module and used as part of a measuring system on spacecraft for various purposes, is to ensure their noise-immune operation when the measuring system is exposed to a combination of various types of interference which determine the electromagnetic environment on the spacecraft. The article is devoted to the analysis of the characteristics of various types of interference affecting the measuring system, identifying the ways of their penetration into the temperature control interface module and determining the influence of the characteristics of these interference on the choice of measures to ensure the required noise immunity of the temperature control interface module as part of the measuring device. It is shown that the paths of interference penetration into the interface temperature control module depend on the frequency and time characteristics of the interference affecting the measuring system. Measures to mitigate these interference must be determined after assessing the danger of their penetration into the interface temperature control module for each path separately in the entire frequency range of their impact. Based on the results of such assessments, a set of reasonable measures should be determined to ensure the noise immunity of the interface temperature control module as part of the measuring device, implemented in combination at the design levels of the measuring system, the measuring device and the interface temperature control module.

Investigation and Analysis of the Impact of Interference on Wireless Communication Systems

Wireless communication systems are widely used in modern society, and their reliability is paramount to ensure effective communication. The aim of this investigation is to analyze the effects of interference on wireless communication systems. Interference is a major issue in wireless communication systems and can significantly degrade the system's performance. This paper presents a survey of investigations into the effect of interference on wireless communication systems. It provides an overview of the various types of interference and their effects on wireless communication systems, as well as techniques used to mitigate interference in wireless communication systems. It also reviews recent research on interference in wireless communication systems, which has shown that interference can significantly degrade the performance of wireless communication systems. The paper also discusses the challenges and future directions in the investigation of interference in wireless communication systems, such as the development of interference models that accurately capture the complex nature of interference, the design of interference mitigation techniques that can adapt to changing interference conditions, and the optimization of wireless communication systems to minimize the impact of interference. Finally, the survey highlights the importance of investigating the effect of interference on wireless communication systems and provides a comprehensive overview of the various techniques used to mitigate interference.

ECG Enhancement and R-Peak Detection Based on Window Variability.

In ECG applications, the correct recognition of R-peaks is extremely important for detecting abnormalities, such as arrhythmia and ventricular hypertrophy. In this work, a novel ECG enhancement and R-peak detection method based on window variability is presented, and abbreviated as SQRS. Firstly, the ECG signal corrupted by various high or low-frequency noises is denoised by moving-average filtering. Secondly, the window variance transform technique is used to enhance the QRS complex and suppress the other components in the ECG, such as P/T waves and noise. Finally, the signal, converted by window variance transform, is applied to generate the R-peaks candidates, and the decision rules, including amplitude and kurtosis adaptive thresholds, are applied to determine the R-peaks. A special squared window variance transform (SWVT) is proposed to measure the signal variability in a certain time window, and this technique reduces false detection rate caused by the various types of interference presented in ECG signals. For the MIT-BIH arrhythmia database, the sensitivity of R-peak detection can reach 99.6% using the proposed method.

Interference Management in 5G and Beyond Network: Requirements, Challenges and Future Directions

In the modern technological world, wireless communication has taken a massive leap from the conventional communication system to a new radio communication network. The novel concept of Fifth Generation (5G) cellular networks brings a combination of a diversified set of devices and machines with great improvement in a unique way compared to previous technologies. To broaden the user’s experience, 5G technology provides the opportunity to meet the people’s potential necessities for efficient communication. Specifically, researchers have designed a network of small cells with unfamiliar technologies that have never been introduced before. The new network design is an amalgamation of various schemes such as Heterogeneous Network (HetNet), Device-to-Device (D2D) communication, Internet of Things (IoT), Relay Node (RN), Beamforming, Massive Multiple Input Multiple Output (M-MIMO), millimeter-wave (mm-wave), and so on. Also, enhancement in predecessor’s techniques is required so that new radio is compatible with a traditional network. However, the disparate technological models’ design and concurrent practice have created an unacceptable intervention in each other’s signals. These vulnerable interferences have significantly degraded the overall network performance. This review article scrutinizes the issues of interferences observed and studied in different structures and techniques of the 5G and beyond network. The study focuses on the various interference effect in HetNet, RN, D2D, and IoT. Furthermore, as an in-depth literature review, we discuss various types of interferences related to each method by studying the state-of-the-art relevant research in the literature. To provide new insight into interference issue management for the next-generation network, we address and explore various relevant topics in each section that help make the system more robust. Overall, this review article’s goal is to guide all the stakeholders, including students, operators, engineers, and researchers, aiming to explore this promising research theme, comprehend interferences and their types, and related techniques to mitigate them. We also state methodologies proposed by the $3^{\mathrm {rd}}$ Generation Partnership Project (3GPP) and present the promising and feasible research directions toward this challenging topic for the realization of 5G and beyond network.

Гарантованные среднеквадратические оценки линейных преобразований матриц в условиях статистической неопределенности

Линейная оценка наблюдений в условиях погрешностей разного вида с целью получения несмещаемых оценок является предметом исследования многочисленных научных публикаций. Задача линейного регрессионного анализа в условиях, когда элементами векторных наблюдений являются известные матрицы, допускающие малые отклонения от расчетных, исследовались в предыдущих публикациях авторов. С использованием технологии псевдообращенных операторов, а также метода возмущения задача была решена при условии, что мало возмущенными были линейно независимые матрицы наблюдений. Параметры линейных отметок были представлены в виде расписаний по малому параметру. Решения задач линейной оценки в условиях неопределенности в течение последних десятилетий осуществляются в рамках известного метода минимаксной оценки. Формально задачи, которые возникают в этом направлении решаются при наличии некоторых пространств для неизвестных параметров наблюдения, а также пространств, которым могут принадлежать погрешности наблюдений. Коэффициенты линейных оценок определяются в процессе оптимизации гарантированной среднеквадратичной погрешности искомой оценки. Таким образом, предметом научных исследований могут быть задачи линейного оценивания неизвестных прямоугольных матриц по наблюдениям с погрешностями с неизвестными корреляционными матрицами: неизвестные матрицы принадлежат какому-либо ограниченному пространству, корреляционные матрицы случайных возмущений вектора наблюдений неизвестны, но можно предположить случайно. ограниченном пространстве. Некоторые постановки задач линейной оценки наблюдений исследованы в предлагаемой публикации. Рассмотрена задача линейной оценки для вектора наблюдений специального вида, компоненты которого известны прямоугольные матрицы, которые подаются с малыми возмущениями. Предложены варианты постановки задачи, позволяющие получить в первом приближении малого параметра аналитическое решение. Приведен тестовый пример.