Data Transmission Channel Research Articles

VLC channel characteristics and data transmission model in indoor environment for future communication: an overview

VLC channel characteristics and data transmission model in indoor environment for future communication: an overview

SIMULATION AND ANALYSIS OF ENCODERS OF INTERFERENCE-RESISTANT CASCADE CODES FOR DYNAMIC SYSTEMS

For various channels of information transmission that can be used in local control systems of a wide range of processes, affordable, scalable, and inexpensive transmission methods are needed that allow the necessary information to be transmitted reliably without errors. Errors that occur in discrete, continuous communication channels are the main obstacle to the reliability of transmitted data. The main causes of errors are signal attenuation, noise and various interferences. As a result of the analysis of error statistics in discrete data transmission channels, it was concluded that single and double errors occur in the absolute majority of cases. It is proposed to combat errors by using tamper-resistant coding. Among the interference-resistant codes, redundant block-separated systematic codes are highlighted, among which is the Hamming code. The basis of the interference-resistant coding model is proposed to be the use of a systematic Hamming code followed by cascade coding by adding a parity check bit. The used model made it possible to deal with all the most likely cases of errors. Since this coding model must be flexibly used in different systems, a necessary criterion of the model is its universality. Therefore, the model was tested on a sample with code combinations of different numbers of bits. The purpose of this article is to analyze the dependence of the coding procedure execution time for encoders of different levels: a separate first-stage encoder, as well as a first-stage encoder with the addition of a second-stage encoder. Experiments were conducted with a large sample, which were subsequently analyzed and interpreted. Since the model proved to be flexible, simple, stable and effective as a result of experiments, and the process of combating interference by using cascade codes has proven itself well in world practice, it is recommended for use in various information management systems. The implementation of the coder for interference-resistant data transmission is given.

Unsupervised Learning-Based Joint Power Control and Fronthaul Capacity Allocation in Cell-Free Massive MIMO With Hardware Impairments

A deep learning-based resource allocation algorithm that maximizes the sum rate of a limited fronthaul cell-free massive MIMO network with transceiver hardware impairments is proposed in this paper. The sum rate maximization problem with user power constraints and total fronthaul capacity constraints for channel state information (CSI) and data transmission is considered. The deep neural network (DNN) PowerNet is proposed to learn solutions to the joint power control and capacity allocation problem in a low-complex, flexible, and scalable way. An unsupervised learning approach is used which eliminates the need of knowing the optimal resource allocation vectors during model training, hence having a simpler and more flexible model training stage. Numerical simulations show that PowerNet achieves close sum rate performance compared to the existing optimization-based approach, with a significantly lower time complexity which does not exponentially scale with the number of users and access points (APs) in the network. Furthermore, the addition of the online learning stage resulted in a better sum rate than the optimization-based method.

Bivariate Pilot Optimization for Compressed Channel Estimation in RIS-Assisted Multiuser MISO-OFDM Systems

In reconfigurable intelligent surface (RIS)-assisted wireless communication systems, channel estimation is of paramount importance to unleash the full advantage of the high passive beamforming gains from RIS. However, it is particularly challenging due to the massive number of RIS reflecting elements which lack signal perception and processing capabilities, thus incurring prohibitively high pilot overhead between transceivers. To address this challenge, we focus on an RIS-assisted multiuser multiple-input single-output orthogonal frequency division multiplexing (MU-MISO-OFDM) system, and propose a practical transmission protocol with non-uniformly spaced comb -type pilots for compressed channel estimation and data transmission, by exploiting the sparsity of RIS-associated channels. To solve a bivariate pilot optimization problem with the objective of minimizing the mutual coherence of the measurement matrix influenced by pilot positions and pilot powers simultaneously, we propose two enhanced whale optimization algorithm (EWOA)-based approaches by leveraging the second order cone programming (SOCP) and compressed coding scheme (CCS). Simulation results validate the effectiveness of the proposed methods over benchmark schemes in various aspects. It corroborates that considering the coupling relationship between pilot positions and powers can help improve the channel estimation performance of the RIS-assisted MU-MISO-OFDM system with limited pilot overhead.

Robust Data Transfer Paradigm Based on VLC Technologies

Methods for improving the system quality of VLC systems design and operation are considered. VLC technologies represent a system that consists of functions and software The main function of the VLC system is data transmission based on LED technologies. According to ISO/IEC 17025-2000, ISO 5725-2002-the main importance is given to metrological support. VLC systems are particularly critical to the stability of operating modes, they are demanding to control modes and operating conditions, to choose the technical parameters of the component base during design. Robustness can be considered an integral indicator of the overall quality of the VLC system. Taking this into account, as a robust paradigm, we study its functional part, in the scope of structural modeling, using the example of an optoelectronic channel for VLC information transmission, including some technical solutions, and the quality of control and measuring processes as a metrological component of robust system support. As a quantitative assessment of functional robustness, it is proposed to use control risks and the correlation function of the connection between «input» and «output», which evaluates the quality of the data transmission channel. Mathematical and simulation models, as well as application software, were developed to assess and predict control risks.

Data Transmission Channel Protection Organiza-tion in Client-server Software Architecture

The study is devoted to the organization of data transmission channel protection in software with a client-server architecture. In today's information environment, where data exchange takes place over the network, ensuring security becomes a critical task. The effectiveness of the data channel protection method in a client-server architecture program was developed and evaluated. A method has been developed that ensures encryption of messages from interception and data modification and prevents modification of the client software and abuse during its use.

A score based link delay aware routing protocol to improve energy optimization in wireless sensor network

The Wireless Sensor Network (WSN) is the most appearing expertise that has potential applications broad ranges that include environment examining, smart spaces, medical systems, and robotic study. Energy efficiency is a consideration of vital design for WSN. The collision is occurred owing to the transmission of data from the sensor nodes and the traffic at the SINK node is high because of the excess data transmission by the sensor nodes. An essential division of the consumption of resources in a WSN is managed by the mechanism of Medium Access Control (MAC). An existing MAC protocols initiated for the utilization of WSNs single channel for data transmission. The deployment of wireless sensor nodes is concerned in the harsh environment in which the drastic change of conditions suffers from sudden changes in the status of a node and the quality of a link. With limited energy, the sensor nodes are supplied and a major concern is towards improving the lifetime of a network. To deal with these issues, a novel and simple routing mechanism Score based Link Delay Aware Routing (SBLDAR) is proposed, which utilizes the multi-channel MAC procedure comprises of Carrier Sense Multiple Access/ Collision Avoidance (CSMA/CA), to exchange the data, the activity of Time Division Multiple Access (TDMA) sequencing nodes and also Frequency Division Multiple Access FDMA) to allow collision-free exchange simultaneously. Also, in order to overcome this issue, an approach has been put out in this work that involves leveraging a variety of trust variables to identify malicious nodes and then using fuzzy based Modified Sun Flower Optimization (FMSFO) algorithm to elect an effective cluster head. The score based route selection increases the network lifetime and improves network performance. By comparing with the other protocols, the proposed SBLDAR combined with the technique of multi-MAC protocol has shown that it increases the network’s overall performance based on the simulation studies.

Построение распределенных микропроцессорных систем управления движением поездов

High material requirements of new relay systems make it impossible to modernize devices within existing areas and require the construction of new interlocking system buildings, which significantly affects the volume of capital investments. Transitioning to microelectronic and microprocessor electronic platforms allows for the design of more compact systems with expanded functional capabilities. In global practice, there is a trend towards widespread use of microprocessor-based interlocking system. However, there is a slow pace of device updates, mainly due to the high cost of microprocessor-based interlocking system, which exceeds by several times the cost of similar relay-based interlocking system. The high performance of computing resources and fiber-optic data transmission channels allows for the design of efficient structures for microprocessor-based interlocking system. The article presents a comparative analysis of the structures of microprocessor-based interlocking system. The implemented decentralized structures solve the issues of reducing investments for the design and construction of the station’s cable network. The advantages of using these systems from the point of view of controlling the transportation process are described, conclusions are drawn on the effective use of the capabilities of modern control systems with integrated subsystems in relation to field-based train traffic control technologies.

An Efficient Spam Detection Technique for IoT Devices Using Machine Learning

Abstract: The Internet of Things (IoT) is a group of millions of devices having sensors and actuators linked over wired or wireless channels for data transmission. IoT has grown rapidly over the past decade with more than 25 billion devices are expected to be connected by 2020. The volume of data released from these devices will increase many-fold in the years to come. In addition to an increased volume, the IoT devices produces a large amount of data with a number of different modalities having varying data quality defined by its speed in terms of time and position dependency. In such an environment, machine learning algorithms can play an important role in ensuring security and authorization based on biotechnology, anomalous detection to improve the usability and security of IoT systems. On the other hand, attackers often view learning algorithms to exploit the vulnerabilities in smart IoT-based systems. Motivated from these, in this paper, we propose an innovative approach for spam detection in IoT devices using machine learning. Our technique harnesses the power of advanced machine learning algorithms to accurately identify and mitigate spam attacks, ensuring the integrity and security of IoT ecosystems. We present a comprehensive methodology that combines data collection, feature extraction, model training, and evaluation to build a robust spam detection system.

Development of Unified Hybrid WDM-PON With Spectrally Hidden Data Channel System and FBG Optical Sensor Network

Abstract As the demand for fiber optical data transmission systems and other type of applications, which require optical media, like optical sensing increases, the unauthorized parties are becoming increasingly interested in such systems. Also, with such demand, more complex optical systems are required; thus, the network infrastructure is becoming more crowded. It is vital to economize on the available resources and infrastructure to ensure the needs of all interested business, governmental or end-user sides. Therefore, the present research focuses on the development of a unified hybrid optical system. The developed hybrid optical transmission system adds additional protection to the channels, allows for the unification of standard optical data transmission channels, optical sensors and spectrally hidden data transmission channel systems, and increases the efficiency of the optical components used.

Hierarchical Model and Decision Optimization Algorithm for Distributed Data Storage and Processing

The task of optimizing distributed data storage and processing is difficult to solve in a limited time. In this regard, a hierarchical approach has been applied to solve it, which provides for the presentation of a generalized problem in the form of a set of hierarchically ordered subtasks, for each of which locally optimal solutions are determined at the appropriate hierarchy level. To optimize solutions for distributed data storage and processing, a process model has been formed, presented in the form of a set of hierarchically ordered components, a mathematical model of a hierarchical game, which is a way to optimize solutions at hierarchy levels. In order to determine effective solutions at hierarchy levels, an algorithm for local optimization of solutions based on genetic algorithms has been developed. The construction of data processing schedules assigned to computing devices is implemented using the proposed heuristic procedure. The application of the developed models of the distributed data storage and processing process, hierarchical game models and algorithms for optimizing solutions made it possible to significantly increase the dimension of the problem, take into account the parameters characterizing data transmission channels when optimizing solutions at hierarchy levels, and minimize the amount of unused resources.

RETURN OF ELECTRIC DRILLING — PROSPECTS FOR DOMESTIC TECHNOLOGY FOR HIGH-TECH WELL DRILLING

The article gives a comparative analysis of the results of electric drilling in the USSR and the advantages of the new electric drilling complex (EBK).
 Since 1948, over the next 15 years, the use of the first generation of EBK was organized in the fields of Azerbaijan, Turkmenistan, Bashkiria and Ukraine. The efficiency of mechanical drilling was higher than that of the turbine, but the overall performance was unstable due to a number of organizational and technical problems. The improvement of the ECB continued from 1963 to 1970: a series of geared electric boilers, equipment for directional drilling, a ground control and control station, and a data transmission system for a power electric cable were developed. The telemetry system provided the ability to control bottomhole equipment and monitor the drilling process.
 Bashkiria fields were the main "test site" for the development of the ECB, and this drilling method was used until 2013. Drilling performance in the complex geological and technical conditions of directional drilling was higher than the GZD drilling used everywhere in the USSR. In 2017, work began on the return of a new generation ECB to the well construction market in Russia. The new ECB meets modern requirements for the construction of high-tech wells through the use of a piercing valve motor (CVED) and a high-speed data transmission channel. The ECB provides optimal parameters of rock destruction regardless of the well profile and type of drilling agent, as well as increases the efficiency of prevention and elimination of complications and creates conditions for automation of the drilling process. In parallel with the development of ECBs on drill pipes with cable sections, electric drilling is being developed on a tubing — a promising method for drilling sidetracks and branches from horizontal boreholes. The level of readiness of the PU technology for the current day corresponds to SCT 3 according to State Standart R 58048-2017.

A Resource-Adaptive Routing Scheme with Wavelength Conflicts in Quantum Key Distribution Optical Networks.

Quantum key distribution (QKD) has great potential in ensuring data security. Deploying QKD-related devices in existing optical fiber networks is a cost-effective way to practically implement QKD. However, QKD optical networks (QKDON) have a low quantum key generation rate and limited wavelength channels for data transmission. The simultaneous arrival of multiple QKD services may also lead to wavelength conflicts in QKDON. Therefore, we propose a resource-adaptive routing scheme (RAWC) with wavelength conflicts to achieve load balancing and efficient utilization of network resources. Focusing on the impact of link load and resource competition, this scheme dynamically adjusts the link weights and introduces the wavelength conflict degree. Simulation results indicate that the RAWC algorithm is an effective approach to solving the wavelength conflict problem. Compared with the benchmark algorithms, the RAWC algorithm can improve service request success rate (SR) by up to 30%.

Modern automatic recognition technologies for visual communication tools

Communication refers to a wide range of different behaviors and activities aimed at handing over information. The communication process includes verbal, paraverbal and non-verbal components, conveying the informational part of a message and its emotional part respectively. A complex analysis of all communication components makes it possible to evaluate not only the content, but also the situational context of what is being said, as well as to identify additional factors inherent in the mental and somatic state of the speaker. There are several methods of conveying a verbal message, among which are oral and gestural speech (such as the sign language and fingerspelling). Various forms of communication can be contained in multiple data transmission channels, such as audio or video channels. The review is concerned with video data analysis systems, as the audio channel is incapable of non-verbal components transmission that contribute supplemental details. The article analyzes databases of static and dynamic images and systems, developed to recognize the verbal component conveyed by oral and gestural speech, as well as systems that evaluate paraverbal and non-verbal components of communication. Challenges of designing such databases and systems are specified. Prospective directions in complex analysis of all communication components and its combinations for the most complete evaluation of messages are defined.

An anonymization-based privacy-preserving data collection protocol for digital health data.

Digital health data collection is vital for healthcare and medical research. But it contains sensitive information about patients, which makes it challenging. To collect health data without privacy breaches, it must be secured between the data owner and the collector. Existing data collection research studies have too stringent assumptions such as using a third-party anonymizer or a private channel amid the data owner and the collector. These studies are more susceptible to privacy attacks due to third-party involvement, which makes them less applicable for privacy-preserving healthcare data collection. This article proposes a novel privacy-preserving data collection protocol that anonymizes healthcare data without using a third-party anonymizer or a private channel for data transmission. A clustering-based k-anonymity model was adopted to efficiently prevent identity disclosure attacks, and the communication between the data owner and the collector is restricted to some elected representatives of each equivalent group of data owners. We also identified a privacy attack, known as "leader collusion", in which the elected representatives may collaborate to violate an individual's privacy. We propose solutions for such collisions and sensitive attribute protection. A greedy heuristic method is devised to efficiently handle the data owners who join or depart the anonymization process dynamically. Furthermore, we present the potential privacy attacks on the proposed protocol and theoretical analysis. Extensive experiments are conducted in real-world datasets, and the results suggest that our solution outperforms the state-of-the-art techniques in terms of privacy protection and computational complexity.

Detecting Parallel Covert Data Transmission Channels in Video Conferencing Using Machine Learning

Covert communication channels are a concept in which a policy-breaking method is used in order to covertly transmit data from inside an organization to an external or accessible point. VoIP and Video systems are exposed to such attacks on different layers, such as the underlying real-time transport protocol (RTP) which uses Transmission Control Protocol (TCP) or User Datagram Protocol (UDP) packet streams to punch a hole through Network address translation (NAT). This paper presents different innovative attack methods utilizing covert communication and RTP channels to spread malware or to create a data leak channel between different organizations. The demonstrated attacks are based on a UDP punch hole created using Skype peer-to-peer video conferencing communication. The different attack methods were successfully able to transmit a small text file in an undetectable manner by observing the communication channel, and without causing interruption to the audio/video channels or creating a noticeable disturbance to the quality. While these attacks are hard to detect by the eye, we show that applying classical Machine Learning algorithms to detect these covert channels on statistical features sampled from the communication channel is effective for one type of attack.

Information Transmission Features of Live Mode Radio Channel When Using Unmanned Dosimetry Complex

The accident at the Fukushima NPP has revealed a certain drawback of traditional methods of registration of ionizing radiation by means of the automated radiation monitoring system, because in the conditions of the accident at the NPP the monitoring posts of the system were damaged as a result of the tsunami (23 of 24), which did not allow to evaluate the degree of radioactive contamination of the area in the early stages. In such conditions the most promising method of radiation control carried out on the potentially hazardous area is a non-contact method using an unmanned dosimetry complex (UDC), the application of which would reduce the risk of exposure to additional dose loads of personnel carrying out search and reconnaissance work and, additionally, provide management not only with information regarding radioactive contamination of the environment, but also directly provide the results of the search and reconnaissance. However, apart from the equipment used to determine the radiation background (detectors, spectrometers, radiometers, etc.) an important part of the UDC is the organization of the dosimetry complex and the way of information transfer.A possible variant of data transmission channel from the dosimetry complex installed on the UDC to the operator's personal computer is presented using NRF radio modules as an example.

Integrated sensing and communication in an optical fibre

The integration of high-speed optical communication and distributed sensing could bring intelligent functionalities to ubiquitous optical fibre networks, such as urban structure imaging, ocean seismic detection, and safety monitoring of underground embedded pipelines. This work demonstrates a scheme of integrated sensing and communication in an optical fibre (ISAC-OF) using the same wavelength channel for simultaneous data transmission and distributed vibration sensing. The scheme not only extends the intelligent functionality for optical fibre communication system, but also improves its transmission performance. A periodic linear frequency modulation (LFM) light is generated to act as the optical carrier and sensing probe in PAM4 signal transmission and phase-sensitive optical time-domain reflectometry (Φ-OTDR), respectively. After a 24.5 km fibre transmission, the forward PAM4 signal and the carrier-correspondence Rayleigh backscattering signal are detected and demodulated. Experimental results show that the integrated solution achieves better transmission performance (~1.3 dB improvement) and a larger launching power (7 dB enhancement) at a 56 Gbit/s bit rate compared to a conventional PAM4 signal transmission. Meanwhile, a 4 m spatial resolution, 4.32-nε/sqrt {Hz} strain resolution, and over 21 kHz frequency response for the vibration sensing are obtained. The proposed solution offers a new path to further explore the potential of existing or future fibre-optic networks by the convergence of data transmission and status sensing. In addition, such a scheme of using shared spectrum in communication and distributed optical fibre sensing may be used to measure non-linear parameters in coherent optical communications, offering possible benefits for data transmission.

Ultra-compact mode converters with nano strips for efficient phase shifting

Mode-division multiplexing (MDM) is an effective solution to improve the integration of photonic integrated circuits. MDM systems increase the number of channels for data transmission by introducing higher-order modes. The mode converter is a key component for MDM. In this work, we propose a novel ultra-compact mode converters in the silicon-on-insulator platform, combining beam splitters with nano strips. The nano strips are used to achieve the phase matching. The high-performance TE1-TE0, TE2-TE0, and TE3-TE0 mode converters exhibit high conversion efficiency and broad transmission bandwidth, in ultra-small footprints.

Smart Data Placement Using Storage-as-a-Service Model for Big Data Pipelines.

Big data pipelines are developed to process data characterized by one or more of the three big data features, commonly known as the three Vs (volume, velocity, and variety), through a series of steps (e.g., extract, transform, and move), making the ground work for the use of advanced analytics and ML/AI techniques. Computing continuum (i.e., cloud/fog/edge) allows access to virtually infinite amount of resources, where data pipelines could be executed at scale; however, the implementation of data pipelines on the continuum is a complex task that needs to take computing resources, data transmission channels, triggers, data transfer methods, integration of message queues, etc., into account. The task becomes even more challenging when data storage is considered as part of the data pipelines. Local storage is expensive, hard to maintain, and comes with several challenges (e.g., data availability, data security, and backup). The use of cloud storage, i.e., storage-as-a-service (StaaS), instead of local storage has the potential of providing more flexibility in terms of scalability, fault tolerance, and availability. In this article, we propose a generic approach to integrate StaaS with data pipelines, i.e., computation on an on-premise server or on a specific cloud, but integration with StaaS, and develop a ranking method for available storage options based on five key parameters: cost, proximity, network performance, server-side encryption, and user weights/preferences. The evaluation carried out demonstrates the effectiveness of the proposed approach in terms of data transfer performance, utility of the individual parameters, and feasibility of dynamic selection of a storage option based on four primary user scenarios.