Noise In Communication Channel Research Articles

Optimal Tracking Performance of Networked Control Systems Under Communication Channel Noise

Optimal Tracking Performance of Networked Control Systems Under Communication Channel Noise

Применение теоремы Гаусса–Маркова для эквализации гидроакустического канала передачи

Researchers in the field of modern hydroacoustics frequently encounter such problems as interference and noise in communication channels. Multipath propagation is an inevitable hydroacoustic communication problem arising in a sound channel due to reflections from the water surface and seabed. In general, this may decrease the overall communication quality. As a rule, noise cannot be completely eliminated, although its influence can be minimized. In this article, we describe a method for equalizing the hydroacoustic transmission channel using the Gauss–Markov theorem. This method can be used for reducing the multipath propagation effect and obtaining an unbiased estimate with minimal variance.

Notice of Violation of IEEE Publication Principles: Washout Filter-Based Distributed Resilient Current Control for Cyber-Physical Microgrids

Notice of Violation of IEEE Publication Principles: <br><br>“Washout Filter-Based Distributed Resilient Current Control for Cyber-Physical Microgrids," <br>by X. Lu and J. Lai, <br> in IEEE Systems Journal, Early Access <br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. <br><br>This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. <br><br>"A Combined Distributed Cooperative Method and Washout Filter-Based Method for Power Sharing and Voltage Balancing in Bipolar DC Microgrids" <br> by Ramin Babazadeh-Dizaji, Mohsen Hamzeh, Nima Mahdian Dehkordi, <br>submitted to IEEE Transactions on Energy Conversion, August 2020. <br><br> <br/> This article proposes a washout filter-based distributed resilient current control scheme that can achieve current sharing of distributed generations (DG) and voltage restoration of dc bus almost surely under communication channel noise interferences. Since the cyber channels are exposed to inherent noise interferences, the stability and reliability of cyber-physical dc microgrids may terribly be reduced. To dispel the adverse influences of noise interferences, a novel discrete time washout filter is developed. Accordingly, a discrete-time-distributed noise-resiliency control algorithm is developed for dc microgrids based on washout filters, in which only the current state variable is allowed to exchange among DGs with the local decentralized voltage controller. This makes the proposed control mode different from the conventional parallel mode usually requiring a leader–follower consensus-based voltage control by exchanging two state variables (i.e., terminal voltage and current output). Thus, the proposed control mode decreases the complexity to the formulation and enhances the robustness to the leader communication failure. By introducing stochastic theory and Lyapunov stability function, the sufficient conditions considering noise interferences is derived to ensure the stability operation of the whole closed-loop dc network. The obtained results show the effectiveness of the proposed strategy by a tested dc microgrid in OPAL-RT real-time simulator.

ВЛИЯНИЕ ЧАСТОТНОГО ШУМА В КАНАЛЕ СВЯЗИ НА ВЕРОЯТНОСТЬ БИТОВОЙ ОШИБКИ ПРИ ПЕРЕДАЧЕ КАМ СИГНАЛОВ

The purpose of the article is to analyze the combined effect of amplitude white Gaussian noise(AWGN) present in the communication channel and frequency noise (FN) resulting from fluctuations inthe frequency of the signal in the communication channel on the probability of bit error when processingQAM signals. Research tasks to be solved: 1. Development of a mathematical model for processing theQAM signal, taking into account the combined effects of AWGN and FN in the communication channel.2. Numerical study of the combined effect of AWGN and FN on the probability of bit error when processingQAM signals. A mathematical model is proposed that establishes the relationship between thesignal-to-noise ratio in the channel and the mean square deviation of the signal frequency, on the onehand, and the probability of bit error during A mathematical model is proposed that establishes therelationship between the signal-to-noise ratio in the channel and the mean square deviation of the signalfrequency, on the one hand, and the probability of bit error during QAM signal demodulation, on theother. The visualization of the effects associated with the presence of AWGN and FN in the channel onthe signal constellation of the received QAM signal is given. The main patterns associated with jointaction AWGN and FN in the communication channel are: - the appearance of FN in the communicationchannel leads to a decrease in the signal level in the channel during the correlation processing of thereceived signal and a corresponding decrease in SNR; - In addition to the blurring of the signal constellationin the azimuthal direction, associated with the appearance of an integral phase fluctuation due tofrequency fluctuations during the pulse, an increase in the blurring of the signal constellation in theradial direction causes a decrease in the SNR. Based on the results obtained, it is concluded that it isnecessary to take into account more fully the deviations of the signal parameters in the channel due toboth the presence of AWGN and FN.

A MATLAB Simulink Study on the Performance of QAM Modulation Scheme in AWGN, Rayleigh, and Rician Fading Channels: BER Analysis

Wireless communication is the fastest-growing segment in the communication industry, with mobile communication being the most widely used. However, it faces several technical challenges, such as Fading, Shadowing, Interference, and Propagation path loss. Meeting the higher demand for capacity with high-quality service is crucial. Orthogonal Frequency Division Multiplexing (OFDM) is a technique that converts wideband signals into narrowband signals for transmission, making it a suitable option for high bandwidth data transmission. The transmission of these narrowband signals is executed with an orthogonal carrier. This paper focuses on building a QAM model using MATLAB to simulate Bit Error Rate (BER) performance for real data communication under different communication channels, including AWGN and fading channels (Rayleigh and Rician). The aim is to investigate the reduction of noise and bit error rate in communication channels. The simulation model built for this research work demonstrates that QAM scheme performs better in AWGN channels than Rayleigh or Rician fading channels.

Залежність ефективності кадрової синхронізації нероздільних факторіальних кодів від параметрів синхронізації

This paper aims at implementing the principles of establishing frame synchronism for non-separable factorial codes, as well as applying the operation of interleaving fragments received from the communication channel to increase the efficiency of finding permutation boundaries. We apply the algorithm for establishing frame synchronism with parameters defined for the upper limit of the communication channel bit error probability P0_max = 0,495 for environments with a bit error probability P0 ≤ 0,495. The parameters of the algorithm for establishing frame synchronism with the upper limit of the communication channel bit error probability P0_max = 0,4 are determined. The efficiency of using the interleaving operation of fragments received from the communication channel is evaluated. The efficiency of implementing algorithms for establishing frame synchronism with parameters determined for the upper limit of the communication channel bit error probability P0_max ≤ 0,495 and P0_max = 0,4 is compared, for environments with a bit error probability P0 ≤ 0,4. We give recommendations for selecting the synchronization algorithm parameters for communication channels where the bit error probability upper limit P0 ≤ 0,4 is known, and for channels where this value is variable. These recommendations can be used to improve the efficiency of algorithms for establishing frame synchronism when designing telecommunication systems with non-separable data factorial coding in conditions of natural or artificially created high-level communication channel noise.

A Secure Sensor Fusion Framework for Connected and Automated Vehicles Under Sensor Attacks

As typical applications of cyber–physical systems (CPSs), connected and automated vehicles (CAVs) are able to measure the surroundings and share local information with the other vehicles by using multimodal sensors and wireless networks. CAVs are expected to increase safety, efficiency, and capacity of our transportation systems. However, the increasing usage of sensors has also increased the vulnerability of CAVs to sensor faults and adversarial attacks. Anomalous sensor values resulting from malicious cyberattacks or faulty sensors may cause severe consequences or even fatalities. In this article, we increase the resilience of CAVs to faults and attacks by using multiple sensors for measuring the same physical variable to create redundancy. We exploit this redundancy and propose a sensor fusion algorithm for providing a robust estimate of the correct sensor information with bounded errors independent of the attack signals, and for attack detection and isolation. The proposed sensor fusion framework is applicable to a large class of security-critical CPSs. To minimize the performance degradation resulting from the usage of the estimation for control, we provide an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> controller for cooperative adaptive cruise control-equipped CAVs. The designed controller is capable of stabilizing the closed-loop dynamics of each vehicle in the platoon while reducing the joint effect of estimation errors and communication channel noise on the tracking performance and string behavior of the vehicle platoon. Numerical examples are presented to illustrate the effectiveness of our methods.

Research on geometric algebra-based robust adaptive filtering algorithms in wireless communication systems

Noise and interference are the two most common and basic problems in wireless communication systems. The noise in wireless communication channels has the characteristics of randomness and impulsivity, so the performance of adaptive filtering algorithms based on geometric algebra (GA) and second-order statistics is greatly reduced in the wireless communication systems. In order to improve the performance of adaptive filtering algorithms in wireless communication systems, this paper proposes two novel GA-based adaptive filtering algorithms, which are deduced from the robust algorithms based on the minimum error entropy (MEE) criterion and the joint criterion (MSEMEE) of the MEE and the mean square error (MSE) with the help of GA theory. The noise interference in wireless communication is modeled by alpha-stable distribution which is in good agreement with the actual data in this paper. Simulation results show that for the mean square deviation (MSD) learning curve, the GA-based MEE (GA-MEE) algorithm has faster convergence rate and better steady-state accuracy compared to the GA-based maximum correntropy criterion algorithm (GA-MCC) under the same generalized signal-to-noise ratio (GSNR). The GA-MEE algorithm reduces the convergence rate, but improves the steady-state accuracy by 10–15 dB compared to the adaptive filtering algorithms based on GA and second-order statistics. For GA-based MSEMEE (GA-MSEMEE) algorithm, when GA-MSEMEE and the adaptive filtering algorithms based on GA and second-order statistics keep the same convergence rate, its steady-state accuracy is improved by 10–15 dB, and when GA-MSEMEE and GA-MEE maintain approximately steady-state accuracy, its convergence rate is improved by nearly 100 iterations. In addition, when the algorithms are applied to noise cancellation, the average recovery error of the two proposed algorithms is 7 points lower than that of other GA-based adaptive filtering algorithms. The results validate the effectiveness and superiority of the GA-MEE and GA-MSEMEE algorithms in the alpha-stable noise environment, providing new methods to deal with multi-channel interference in wireless networks.

Robust sliding mode controller design of memristive Chua’s circuit systems

Aiming at the memristive Chua’s circuit system, a design method based on robust sliding mode control is proposed in this paper. Due to the complexity of quantization mismatch, communication channel noise, and external disturbances, it is very challenging and difficult to control the memristor-based circuit system. By applying delta operator discretization technology and the working principle of signal encoding and decoding, the dynamical model of the fast sampling quantization mismatched memristive circuit system is established, and the sliding surface is designed via linear matrix inequality technology to ensure the robust quadratic stability of sliding dynamics. Then, a sliding mode reaching control law is designed to realize the robust and stable operation of the memristive circuit system by the combination of delta operator theory and robust sliding mode control theory. The effectiveness and advantages of the proposed method are finally verified on the Matlab/Simulink simulation platform.

COMBINATORIAL OPTIMIZATION OF SYSTEMS OF NEURAL NETWORK CRYPTOGRAPHIC DATA PROTECTION

The problem of improving the reliability of cryptographic data protection in neural network systems with flexible configuration is considered. To ensure the possibility of encrypting/decrypting messages it is proposed to use combinatorial optimization methods for the tasks of forming encoded sequences with improved quality indicators for correcting ability, noise immunity, and autocorrelation properties. The basis of combinatorial optimization is the principle of optimal structural relationships, the essence of which is to achieve the maximum diversity of the system under the established restrictions on the number of structural elements and their mutual placement in space-time. It is proposed to use signal-code sequences for neural network data protection, which are characterized by high noise immunity and low level of the autocorrelation function, using various types of optimized code sequences depending on the set of requirements for work under specific conditions, taking into account restrictions on the duration of sending encrypted messages and the presence of noise in communication channels. The system for neural network cryptographic data protection has been developed using encoded signal sequences, where the number of binary characters of different names differs by no more than one character, which minimizes the value of the autocorrelation function of the encoded signal at a fixed bit depth. To ensure high technical and economic indicators of the cryptosystem, it is advisable to equip it with specialized modules of neuro-similar elements of the network with the possibility of training and flexible configuration for cryptographic data encryption. The relationship between the parameters of optimized encoded signal sequences, in which the value of the autocorrelation function is minimized, and the maximum achievable number of detected and corrected errors has been established. It is proposed to use unique properties of combinatorial configurations with a non-uniform distribution of structural elements, which are distinguished by the fact that the set of all ring sums of their numerical values occurs a fixed number of times. A comparative analysis of cryptographic methods for data protection and transfer using non-standard codes built on the so-called IRB code sequences together with other signal-code constructions was carried out.

A Robust Dynamic State Estimation Method for Power Systems Using Exponential Absolute Value-Based Estimator

Even though the noise model applied in power system dynamic state estimation is usually assumed to be Gaussian, this is not the case due to the unknown system inputs, influence from the communication channel noise and the outliers generated by phasor measurement units (PMUs). In this paper a robust power system dynamic state estimation (DSE) method combining a robust exponential absolute value based estimator and the unscented Kalman filter together is proposed under non-Gaussian noise. Based on the quadratic function and the exponential absolute value function, robust exponential absolute value based estimator is derived, further mitigating the effects of bad data or outliers. The influence function is utilized to calculate the state estimation error covariance of the proposed robust DSE method. The simulation results on the IEEE 39-bus system verify the robustness and effectiveness of the proposed dynamic state estimation method.

Iterative learning control for nonlinear nonaffine networked systems with stochastic noise in communication channels

This article investigates the convergence analysis of networked iterative learning control for nonlinear nonaffine systems firstly by considering stochastic noise introduced by the network channels. The convergence analysis is under a data-driven framework, which does not rely on any mechanism model information. To deal with the nonlinearity, both the state transition technique and the differential mean value principle are used to formulate the iterative dynamics of system states, tracking errors and input signals using a lifted matrix expression, respectively. In terms of the contraction mapping principle, the tracking error is shown to be iteratively convergent under the sense of mathematical expectation. Since the [Formula: see text]-norm is not used in the analysis, the convergence property of the tracking error is not affected by the operation interval and a good transient performance can be ensured in theory. Simulation studies test the theoretical results.

Enhanced energy-constrained quantum communication over bosonic Gaussian channels

Quantum communication is an important branch of quantum information science, promising unconditional security to classical communication and providing the building block of a future large-scale quantum network. Noise in realistic quantum communication channels imposes fundamental limits on the communication rates of various quantum communication tasks. It is therefore crucial to identify or bound the quantum capacities of a quantum channel. Here, we consider Gaussian channels that model energy loss and thermal noise errors in realistic optical and microwave communication channels and study their various quantum capacities in the energy-constrained scenario. We provide improved lower bounds to various energy-constrained quantum capacities of these fundamental channels and show that higher communication rates can be attained than previously believed. Specifically, we show that one can boost the transmission rates of quantum information and private classical information by using a correlated multi-mode thermal state instead of the single-mode thermal state of the same energy.

LMS Algorithm for Adaptive Transversal Equalization of a Linear Dispersive Communication Channel

The presence of any type of distortion in communication system, regardless of the causes, is undesirable and undeniably has a negative impacts on the system in general and therefore it is necessary to eliminate its effects. This study employs one of the well-known algorithms for adaptive equalization of linear dispersive communication channel which is Least Mean Square (LMS) algorithm. The LMS technique is basically utilized to eliminate the noise in communication channel. The novelty of this paper includes the profoundly analyzing of the influence of rate of convergence, miss-adjustment, computational requirement, and sensitivity to Eigen-value spread in sufficient details in a simple and plain way. Moreover, the system performance improvement employing the feedback equalizer technique is intensively presented which shows that our methodology is very effective to eliminate the noise in the system. The simulation work has been performed with MATLAB software.

Hiding information in images using pseudo-random sequences

In this article are discussed techniques of hiding information messages in cover image using direct spectrum spreading technology. This technology is based on the use of poorly correlated pseudorandom (noise) sequences. Modulating the information data with such signals, the message is presented as a noise-like form, which makes it very difficult to detect. Hiding means adding a modulated message to the cover image. If this image is interpreted as noise on the communication channel, then the task of hiding user’s data is equivalent to transmitting a noise-like modulated message on the noise communication channel. At the same it is supposed that noise-like signals are poorly correlated both with each other and with the cover image (or its fragment). However, the latter assumption may not be fulfilled because a realistic image is not an implementation of a random process; its pixels have a strong correlation. Obviously, the selection of pseudo-random spreading signals must take this feature into account. We are investigating various ways of formation spreading sequences while assessing Bit Error Rate (BER) of information data as well as cover image distortion by mean squared error (MSE) and by Peak signal-to-noise ratio (PSNR). The obtained experimental dependencies clearly confirm the advantage of using Walsh sequences. During the research, the lowest BER values were obtained. Even at low values of the signal power of the spreading sequences (P≈5), the BER value, in most cases, did not exceed 0,01. This is the best result of all the sequences under consideration in this work. The values of PSNR when using orthogonal Walsh sequences are, in most cases, comparable to other considered options. However, for a fixed value of PSNR, using the Walsh transform results in significantly lower BER values. It is noted that a promising direction is the use of adaptively generated discrete sequences. So, for example, if the rule for generating expanding signals takes into account the statistical properties of the container, then you can significantly reduce the value of BER. Also, another useful result could be increasing PSNR at a fixed (given) value of BER. The purpose of our work is to justify the choice of extending sequences to reduce BER and MSE (increase PSNR).

METHODS OF FACTORIAL CODING OF SPEECH SIGNALS

Context. The paper outlines the methods of factorial coding of speech signals using a factorial code to provide integrated information security and to maintain a receiver and transmitter clock phase. By integrated information security, for the methods proposed in this article, we mean data protection from effects of noise in communication channel and attempts of data unauthorized access in open multiple access telecommunication networks. Objective. The goal of the research is to provide integrated protection of real-time speech signals based on factorial coding. For this, the methods for factorial coding of speech signals and building speech codecs have been developed. These methods are based on the properties of factorial codes to keep synchronism with the working signal, to detect a significant part of errors caused by the action of noise, natural or created intentionally, to provide the ability to correct all detected errors with a finite accuracy, as well as to provide cryptographic protection against voice message unauthorized listening by hiding the law of converting speech signal samples into a permutation. Method. The main idea of the proposed methods is to choose permutations for information transferring with a specific set of properties and features that provide the ability to correct errors detected by code and to recover speech signal samples with a finite degree of accuracy (with a nonzero aperture). Results. The procedures for information coding/decoding have been determined. The results of the experimental evaluation of the model of such systems when working on a communication channel with both independent and multiple bit errors are presented. The magnitude of decoding noise due to the finite accuracy of speech signal samples recovery is determined as a function of bit error probability in a communication channel. Conclusions. The proposed methods of factorial coding of a speech signal provide integrated information security and recovery with finite accuracy of speech signal samples deformed by noise in communication channel. The requirements to the quality of communication channel (to the value of bit error probability) for comfortable speech perception are determined.

Is Usage of Visual Images in Online Marketing Effective?

This paper discusses the importance of visual images in online marketing communication such as on Facebook. Because of noise in online communication channels it is becoming more and more difficult for marketing messages to be noticed. Visual images are now common on social media and can attract target audience and consumers and draw their attention in the online environment. This paper presents a study that selected 37 companies’ photos posted on Facebook. Four of these companies were highlighted owing to the high popularity and acceptance of their photos. Qualitative research was performed to investigate what kinds of photos these companies posted from Feb 2018 to Jan 2019. The results of this study show that there are diverse types of photos (of food, children, sports, animals, landscape, automobile, portraits, architecture, macros, quotes, events, aerial, street, and documentary) used for various marketing purposes. We concluded that visual images are effective in online marketing.

Coherence of Noisy Double-Integrator Networks Without Velocity Measurements

This brief studies the systemic performance of double-integrator consensus networks in the presence of stochastic noises. The systemic performance is characterized in terms of the network coherence, which is equal to the squared H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">12</sub> norm of the network and can capture the deviation from network average. Four different types of structured noises are mainly considered and for each type of noise, a consensus protocol without velocity measurements is proposed to guarantee consensus achieving. For the cases with dynamics noise, sensor noise and communication channel noise, it is shown that the network coherence can be explicitly expressed by a function of the nonzero eigenvalues of the Laplacian matrix and the network size. For the case with receiver noise, a sufficient condition is derived to ensure that the network coherence is less than a given constant.

Modelling noise and pulse width modulation interference in indoor visible light communication channels

Visible light communication (VLC) has the potential to supplement the growing demand for wireless connectivity. In order to achieve the full potential of VLC, channel models are required. Discrete channel models based on semi-hidden Markov models (Fritchman model) for indoor VLC using low data rate LEDs are presented. Each channel considered includes background noise and differing types of interference from fluorescent lights and pulse-width modulated (PWM) LEDs, which could be part of an indoor smart lighting system. Models were developed based on experimental error sequences from a VLC system using an on-off keying (OOK) modulation scheme. The error sequences were input into the Baum-Welch algorithm to determine the model parameters by expectation maximisation. Simulated error sequences generated by the models are compared to and, in most cases, perform better than simpler models with a single bit error rate. The models closely approximate the experimental errors sequences in terms of error distribution. The models performed better in channels where there is less interference. It was also found that periodic errors were introduced as a results of the PWM modulated smart lighting LEDs. These models have use for designing error control codes and simulating indoor VLC environments with different types of interference.

Efficiency Analysis of Time Synchronization and PAPR Reduction of N-OFDM Modem

Non-Orthogonal Frequency Division Multiplexing (N-OFDM) remains to be a promising digital modulation technique for high-data-rate wireless transmission. This research is focused on the efficiency analysis of a technique for data frames time synchronization in a white noise communication channel and on an optimal demodulation in the N-OFDM system. N-OFDM signals are generated using the Hartley transform and the Cauchy method is applied for the evaluation signal amplitude the demodulation procedure. The peak-to-average power ratio (PAPR) for different frequency spacing between N-OFDM subcarriers is analyzed. As a result, the mathematical expression for the subcarrier initial phase over subcarrier frequency is derived that allows calculating initial phase with the minimum of PAPR. The paper contains experimental results confirming the operability of the proposed time synchronization scheme. In the experiment, bit error rate estimation was performed for various spacing frequencies and signal-to-noise ratio in the range from 0 to 25 dB. The experimental results have shown the opportunity of PAPR reduction through the calculation of reasonable initial phase for each subcarrier. The experiment was based on simulation in MATLAB with the use of a sound card of a personal computer.