Reliable Information Transmission Research Articles

Innovation rate and population structure moderate the effect of population size on cumulative technological culture

Cumulative technological culture is defined as the increase in efficiency and complexity of tools and techniques over generations that allowed humans to conquer the whole Earth. While one part of the puzzling ability of humans to develop such a form of culture lies in their cognitive capacities giving rise to reliable transmission of information, another lies in the impact of demographic factors. Indeed, many studies have examined the impact of population size, innovation rate and population structure on cumulative technological culture. Here, we present a computational model based on a previous model of micro-society that we extended to study the impact of population size and the influence of innovations on cumulative technological culture. Our results showed that population size exhibits an influence on cumulative technological culture, principally in small-scale populations. Additionally, the model suggests that the innovation rate constrains cumulative technological culture and the importance of population size. Indeed, when innovations are frequent, the impact of population size is diminished. Furthermore, our results demonstrate that individuals rely more on themselves than on others to innovate in earlier generations as well as in small populations. However, when populations grow as well as in later stages of evolution, reliance on innovation from others increases. Overall, these results indicate that population size has a limited impact on cumulative technological culture and that other demographic factors such as innovation rate could offer a viable alternative explanation for archeological records.

Secure MIMO NOMA transmission with energy harvesting-aided full-duplex jammer under erroneous channel information

NOMA allows for the simultaneous transmission of multiple user signals and full-duplex (FD) communication enables concurrent transmit-and-receive operations, both improving spectral efficiency. Additionally, NOMA networks utilize energy harvesting (EH) to efficiently harvest energy from radio frequency sources, contributing to improved energy efficiency. In addition, deploying multiple antennas at NOMA users facilitates energy transfer and harvesting, as well as reliable information transmission through antenna array processing. Moreover, jamming is presented as a useful method to secure wireless transmission. Therefore, multiple-input multiple-output (MIMO) NOMA transmission with EH-aided FD jammer (MMnOehFD) is envisioned to acquire high performance like energy efficiency, security, reliability, and throughput. The paper numerically assesses the reliability and security of MMnOehFD where evaluation metrics include energy efficiency, throughput, and outage probability. Further, practical factors such as erroneous channel information (ECI) and multi-antenna users are taken into account in the evaluation. Results indicate that the ECI significantly degrades system performance, and this degradation is influenced by multiple parameters. Also, the proposed MMnOehFD can avoid complete outage and attain optimal performance with appropriate system configuration. The performance of the MMnOehFD is notably improved with an increasing number of antennas. Further, the MMnOehFD outperforms two baseline schemes (MIMO OMA transmission with EH-aided FD jammer and MIMO NOMA transmission without jammer), highlighting the effectiveness of combining jammer and NOMA.

Secure Pixel-Level Data Concealment: A Novel Approach for Securing Black and White Images within Color Images

In the era of rampant digital data transfer, concerns regarding the secure and reliable transmission of information persist, with numerous attempts at concealing and transporting data globally. Despite the plethora of existing techniques, issues persist, ranging from misinterpretation to malicious misuse of data during the transfer process. To address some of these challenges, this research introduces an innovative method centered on the modification of pixel data to embed concealed information. The primary objective is to alter pixel values in a manner that accommodates the storage of data pertaining specifically to black and white image pixel data. The proposed technique is designed to exclusively encode information related to two-pixel values, with careful adjustments made to ensure the masked image remains non-deceptive. Pixel values undergo subtle alterations to mitigate susceptibility issues associated with corner values, particularly at the border values of 254 and 255 for RGB values. The developed method presents a simplified yet robust data hiding technique, allowing the storage of black and white images within color images while achieving a high Peak Signal-to-Noise Ratio (PSNR) compared to standard ".png" images. Crucially, the developed approach addresses the challenge of minimizing drastic changes in pixel color, enhancing the overall fidelity of the stego image. Furthermore, the versatility of the proposed method is showcased by its potential to accommodate more than three images when the stego image size is appropriately large and segmented. A practical and efficient solution has been contributed to the persistent issues associated with secure data transfer, presenting a novel methodology for concealing black and white images within color images.

Method of assessing the information reliability of in 5G wireless transmission systems

The article proposes a method of assessing information transmission reliability by using the output normalized logarithmic ratio of the likelihood function (LRLF) of the decoder. Based on the evaluation, the method allows adapting system parameters with turbo codes (TC) or LDPC code. This method can be used in combination with other methods of parametric and structural adaptation using turbo codes or LDPC codes.

Shared input and recurrency in neural networks for metabolically efficient information transmission.

Shared input to a population of neurons induces noise correlations, which can decrease the information carried by a population activity. Inhibitory feedback in recurrent neural networks can reduce the noise correlations and thus increase the information carried by the population activity. However, the activity of inhibitory neurons is costly. This inhibitory feedback decreases the gain of the population. Thus, depolarization of its neurons requires stronger excitatory synaptic input, which is associated with higher ATP consumption. Given that the goal of neural populations is to transmit as much information as possible at minimal metabolic costs, it is unclear whether the increased information transmission reliability provided by inhibitory feedback compensates for the additional costs. We analyze this problem in a network of leaky integrate-and-fire neurons receiving correlated input. By maximizing mutual information with metabolic cost constraints, we show that there is an optimal strength of recurrent connections in the network, which maximizes the value of mutual information-per-cost. For higher values of input correlation, the mutual information-per-cost is higher for recurrent networks with inhibitory feedback compared to feedforward networks without any inhibitory neurons. Our results, therefore, show that the optimal synaptic strength of a recurrent network can be inferred from metabolically efficient coding arguments and that decorrelation of the input by inhibitory feedback compensates for the associated increased metabolic costs.

A blind signature scheme for IoV based on 2D-SCML image encryption and lattice cipher

Today’s Internet of Vehicles (IoV) faces many security risks in the data transmission process, and image data is more vulnerable to security threats in the transmission process due to its special characteristics such as large amounts of information and high visibility. Therefore, to guarantee the dependability of data transmission in the IoV environment, this paper designs a blind signature scheme for IoV based on two-dimensional sine cosine cross-chaotic mapping (2D-SCML) image encryption and lattice cipher (BSS-IoV). The innovation of this scheme is that it aims at blind signature of image information, blinds it before sending the information, and combines the lattice public key encryption algorithm to better ensure the safe and reliable transmission of information and reduce the risk of information disclosure. To further ensure the security of the scheme, an image encryption algorithm based on 2D-SCML and pixel splitting (2PS-IEA) is proposed, which is used to blind the information and thus reduce the risk of information leakage on the one hand, on the other hand, it is used in the signature process to ensure the security of the signed information. The 2D-SCML is derived from the cross-model structure proposed in this paper. Through simulation results and experimental analysis, the values of NPCR and UACI, respectively, 99.6094% and 33.4635%, are close to ideal values. And 50% of the cut image can also recover the rough information, which indicates that the signature scheme has the security against differential attacks, cut attacks and noise attacks. Moreover, the security analysis shows that the scheme has the anti-tamper, anti-repudiation and traceability.

Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel

This work addresses the quasi-synchronization of delay master–slave BAM neural networks. To improve the utilization of channel bandwidth, a dynamic event-triggered impulsive mechanism is employed, in which data is transmitted only when a preset event-triggered mechanism or a forced impulse interval is satisfied. In addition, to guarantee the reliability of information transmission, a reliable redundant channel for BAM neural networks is adopted, whose transmission scheduling strategy is designed on the basis of the packet dropouts rate of the main communication channels. Further, an algorithm is employed to reduce the quasi-synchronization range of the error systems and the controllers are obtained. At last, a simulation result is shown to illustrate the effectiveness of the presented strategy.

Ultra-Reliable Deep-Reinforcement-Learning-Based Intelligent Downlink Scheduling for 5G New Radio-Vehicle to Infrastructure Scenarios.

Higher standards for reliability and efficiency apply to the connection between vehicle terminals and infrastructure by the fifth-generation mobile communication technology (5G). A vehicle-to-infrastructure system uses a communication system called NR-V2I (New Radio-Vehicle to Infrastructure), which uses Link Adaptation (LA) technology to communicate in constantly changing V2I to increase the efficacy and reliability of V2I information transmission. This paper proposes a Double Deep Q-learning (DDQL) LA scheduling algorithm for optimizing the modulation and coding scheme (MCS) of autonomous driving vehicles in V2I communication. The problem with the Doppler shift and complex fast time-varying channels reducing the reliability of information transmission in V2I scenarios is that they make it less likely that the information will be transmitted accurately. Schedules for autonomous vehicles using Space Division Multiplexing (SDM) and MCS are used in V2I communications. To address the issue of Deep Q-learning (DQL) overestimation in the Q-Network learning process, the approach integrates Deep Neural Network (DNN) and Double Q-Network (DDQN). The findings of this study demonstrate that the suggested algorithm can adapt to complex channel environments with varying vehicle speeds in V2I scenarios and by choosing the best scheduling scheme for V2I road information transmission using a combination of MCS. SDM not only increases the accuracy of the transmission of road safety information but also helps to foster cooperation and communication between vehicle terminals to realize cooperative driving.

Blockchain Technology in Construction Supply Chain Management: Enhance Transaction Speed, Cost Effectiveness and Security

The traditional construction sector encountered obstacles that prevented it from developing, including knowledge asymmetry, complicated intermediary relationships, and high transaction costs. Blockchain technology offered a more effective, secure, and convenient mode of transaction and management to the construction industry because it was a decentralized, safe, and reliable information transmission and management tool. Blockchain technology could be applied to the construction industry's supply chain to achieve traceability and supervision, enhancing the transparency and dependability of transactions. At the same time, blockchain technology could be applied to the management of the construction supply chain to achieve rapid information sharing and verification, lowering transaction costs, and increasing transaction efficiency. However, the previous study on the use of blockchain technology in the building sector was still in its infancy and required more investigation and study. This study aimed to investigate how blockchain technology could be used in supply chain management for the construction sector to address present issues. The study's goals were to examine how blockchain technology could speed up transactions and improve supply chain management for the construction industry, as well as to examine how it could lower transaction costs and increase data sharing and information transparency. This study used a semi-structured interviewing technique for the purpose of gathering and analysing data. The researcher learned more about professionals and industry experts' thoughts and experiences with blockchain technology in construction supply chain management through in-person or remote interviews with them. The advancement of the construction industry's digital transformation and information upgrading reflected the significance of this study. This study would help the supply chain management in the construction sector in enhancing the effectiveness of supply chain transactions in the construction industry and reducing the transaction cycle; lowering the price of supply chain transactions in the construction industry and boosting the industry's competitiveness; strengthening the security and reliability of supply chain transactions in the construction industry and reducing data compromise and transaction risks.

Method of adaptation of cascade codes to ensure reliability of information transmission of wireless data transmission systems

The article proposes a method of structural adaptation of cascade codes, designed to ensure the specified reliability of information transmission of wireless data transmission systems in the event of interference, due to the dynamic synthesis of combined structures of cascade codes under conditions of a priori uncertainty. The essence of the method is to identify the internal structure of the code, due to which the structure of the component codes of the turbo code is determined. It was developed using the gradient method due to the implementation of a multi-step iterative procedure for finding optimal system parameters. Implementation of the method allows to ensure the reliability of information transmission of wireless data transmission systems. To check the effectiveness of the method of structural adaptation of cascade codes, a simulation model was developed in the C++ programming language in the Visual Studio 2019 software environment, and wireless data transmission systems were simulated. The simulation results show that the combined structure of building cascade codes together with OFDM technology allows you to independently adapt the coding rate of each of the coding stages depending on the results of the analysis of the reliability of information in this cascade, which leads to the provision of the specified reliability of information transmission, while the BSPD bandwidth is reduced by 4–12% against 20–35% of known results. The use of Reed-Solomon codes in a sequential cascade scheme with turbo codes due to the adaptation of the coding rate of this cascade design allows obtaining an energy gain of 0.5–0.7 dB without increasing the bandwidth of the transmission system compared to systems that use only turbo codes. The obtained results are of significant relevance and can be implemented in the development of information transmission systems to ensure the reliability of data transmission, both in peacetime and in conditions of armed aggression of the Russian Federation against Ukraine.

Study of the Telecommunication Networks Performance and Reliability Indicators

It is currently urgent to improve the technical characteristics and increase the efficiency of telecommunication networks because of the global problem of ensuring the reliable transmission, processing and protection of commercial information in telecommunication networks. The aim of this study is to assess the reliability indicators of telecommunication networks and analyse the level of their development. The aim was achieved through the methods that were used to assess the reliability of the entire network: the generalized method of analytical assessment of the telecommunication network reliability; connection-based metrics; scaling of telecommunication networks, and application of unified reliability indicators to routine control, operation and maintenance. As a result of the research, the indicators of telecommunication networks were studied with and without using connection-based metrics. As a result, the network metrics were also divided into distribution and generation/transmission reliability and telecommunication network metrics – into connection-, performance-, and condition-based metrics, which showed improvements in network performance and reliability. As a prospect for further research, studying and improving the telecommunication network reliability indicators is suggested.

A new reliability analysis method for software‐intensive systems with degradation accumulation effect based on goal oriented methodology

AbstractSystem reliability directly affects the realization of software‐intensive system functions, which rely on both hardware and software. The operating status of hardware and software affect each other, and the continuous accumulation of their degraded performances will accelerate the occurrence of failures. However, the interaction relationship between hardware and software is often overlooked in most current research. In this paper, a new reliability analysis method is proposed for multi‐state software‐intensive systems with degradation accumulation effect and information transmission attenuation based on goal oriented (GO) methodology. First, a new function GO operator is created, and its operation formula is derived with the aid of Markov process theory. To quantify the impact of degradation accumulation on availability, non‐negative constant and random variable critical thresholds are set for the degradation state. Then, an effective optical power loss model is established to analyze the reliability of information transmission in the presence of attenuation. Next, the reliability analysis framework for multi‐state software‐intensive system is established based on the GO method. Finally, the proposed reliability analysis method is applied to the example of meter and decameter wavelength radio heliograph to demonstrate the applicability and feasibility of our work. The proposed model provides a more accurate reflection of the system reliability under actual operating conditions.

Multiphysical Field Modulated VO2 Device for Information Encryption.

In the information explosion society, information security is highly demanded in the practical application, which raised a surge of interest in designing secure and reliable information transmission channels based on the inherent properties of emerging devices. Here, an innovative strategy to achieve the data encryption and reading during the data confidential transmission based on VO2 device is proposed. Owing to the specific insulator-to-metal transition property of VO2 , the phase transitions between the insulator and metallic states are modulated by the combination of electric field, temperature, and light radiation. These external stimulus-induced phase diagram is directly associated with the defined VO2 device, which are applicable for control the "0" or "1" electrical logic state for the information encryption. A prototype device is fabricated on an epitaxial VO2 film, which displayed a unique data encryption function with excellent stability. The current study not only demonstrated a multiphysical field-modulated VO2 device for information encryption, but also supplied some clues for functional devices applications in other correlated oxide materials.

A target parameter estimation algorithm for integration of radar and communication based on orthogonal time frequency space

AbstractOrthogonal time frequency space (OTFS) is a new method technique that supports reliable information transmission in a strong Doppler environment. Aiming at the radar target parameter estimation problem of integration of radar and communication (IRC) based on OTFS, this paper proposes a two‐step radar target parameter estimation algorithm combining maximum likelihood (ML) estimation and gradient descent (GD) principle. Firstly, the echo signal of the OTFS integrated signal is constructed and based on this, the ML estimation model is constructed, and the alternating projection (AP) algorithm is employed to make a rough estimation of the target parameters. Then the rough estimation results of the AP‐ML algorithm are employed as the initial value of the GD algorithm for the fine parameter estimation. Simulation results show that the proposed algorithm has better target parameter estimation performance and resolution while reducing the computational complexity.

Research on Train-to-Train Communication Resource Allocation for Urban Rail Transport

As communication technology improves and urban rail communication system develops, the new CBTC (Communication-Based Train Control) system built upon train – train(T2T) communication has become the mainstream of future rail transit signaling systems. In the future train-centered CBTC system, Train-to-Ground (T2G Train-to-Ground) mode may coexists with T2T communication mode. To reduce the interference and ensure the reliable transmission of information and system security, a joint channel allocation and power control communication resource distrbution method is proposed, which firstly allocates channels to users by the Hungarian algorithm, and then make use of sparrow search algorithm to coordinates the user’s transmit power. Obtained by simulation results, this suggested strategy not only reduces interferences caused by resource sharing and satisfies the dependability of the system, but also significantly improves the throughput of the system.

DQL-based intelligent scheduling algorithm for automatic driving in massive MIMO V2I scenarios

Connected and autonomous vehicle (CAV) vehicle to infrastructure (V2I) scenarios have more stringent requirements on the communication rate, delay, and reliability of the Internet of vehicles (IoV). New radio vehicle to everything (NR-V2X) adopts link adaptation (LA) to improve the efficiency and reliability of road safety information transmission. In order to solve the problem that the existing LA scheduling algorithms cannot adapt to the Doppler shift and complex fast time-varying channel in V2I scenario, resulting in low reliability of information transmission, this paper proposes a deep Q-learning (DQL)-based massive multiple-input multiple-output (MIMO) LA scheduling algorithm for autonomous driving V2I scenario. The algorithm combines deep neural network (DNN) with Q-learning (QL) algorithm, which is used for joint scheduling of modulation and coding scheme (MCS) and space division multiplexing (SDM). The system simulation results show that the algorithm proposed in this paper can fully adapt to the different channel environment in the V2I scenario, and select the optimal MCS and SDM for the transmission of road safety information, thereby the accuracy of road safety information transmission is improved, collision accidents can be avoided, and bring a good autonomous driving experience.

An OFDM-Based Frequency Domain Equalization Algorithm for Underwater Acoustic Communication with a High Channel Utilization Rate

The underwater acoustic communication technique for high-speed and highly reliable information transmission in the ocean has been one of the popular research focuses facing the fast-growing information technology sector and the accelerating development of ocean resources. In order to achieve a high information transmission rate with limited underwater acoustic channel bandwidth, researchers have paid much attention to the underwater acoustic communication technique based on orthogonal frequency division multiplexing (OFDM). A traditional OFDM-based frequency domain equalization algorithm relies on cyclic prefixes for the effective resistance to the multipath effect of an underwater acoustic channel. However, a redundant cyclic prefix may lead to a severe waste of energy and bandwidth in the underwater acoustic system if it is too long. The high utilization rate of OFDM signal channel will not be practically achieved in this case. Based on the limitations of the existing frequency domain equalization algorithm, this paper studied the influence of the multipath effect on the OFDM signal transmission. Subsequently, the principles of the OFDM-based frequency domain equalization were further explored for an improved structural model design of the communication system. On this basis, a novel frequency domain adaptive equalization algorithm was put forward. In addition, the proposed algorithm was optimized to address the problem of increased computation. The simulation results proved that the novel frequency domain equalization algorithm delivers a better symbol error ratio than the existing algorithm, and the compensation for the multipath effect through frequency selective fading. The proposed algorithm can realize the information transmission at a low symbol error ratio when fewer cyclic prefixes are used, so that it takes up a lower number of channels with cyclic prefixes in the OFDM communication system.

Genetic optimization of 5G-NR LDPC codes for lowering the error floor of BICM systems

With the wide range of commercial uses of fifth generation (5G), new radio (NR) communication networks, the wireless transmission becomes more efficient, reliable and faster. At the same time, high-quality signal transmission for 5G networks and beyond has also encountered new opportunities and challenges. Channel coding is a key technology to ensure reliable information transmission and service quality. However, the 5G-NR LDPC coded bit-interleaved coded modulation (BICM) sometimes suffers from relatively high error floors, so it can not always guarantee the high-quality and low-delay wireless transmission. In this paper, we propose a further redesign of the 5G-NR LDPC coded BICM based on genetic algorithm (GenAlg). By adjusting the number of the non-zero elements, the corresponding positions and shifting values in base matrix, we optimize the 5G-NR LDPC codes with GenAlg according to the error performances of coded BICM schemes. Simulation results show that the optimized 5G-NR LDPC codes which still support length and rate compatible coding have lower error floors with a little performance loss int the waterfall region compared to the standard 5G-NR LDPC codes with different modulation orders.

Study of permutation decoding algorithms in UAV control systems

Relevance. This paper presents relevant topic of the use of unmanned aerial vehicles (UAV) in the agroindustrial complex (AIC) to obtain timely reliable information about the state of agricultural land for the entire period. In modern infocommunication technologies and communication systems, high requirements are placed on the reliability of information transmission. In mobile data exchange systems, compositions of noise-resistant codes are used in the form of cascade designs or turbo codes, and in order to increase their efficiency, it is necessary to make the fullest use of the redundancy introduced at each stage of data processing. To solve such a problem, it is advisable to apply a decoding method based on the ordering of the character confidence indices (CCI) of the code combination.Methods. When determining the encoding-decoding systems, the Mathcad application software was used. Mathematical studies have shown that binary block codes for reaching the specified boundary can be decoded not only on the basis of ordered statistics, but also using the method of dividing the space of allowed code combinations into clusters. Based on this method, a block diagram of the algorithm of the simulation model of the operation of the block code decoder based on cluster calculation is compiled.Results. The application of the proposed method of soft decoding of systematic block codes reduces the processing time of code combinations in the decoder by reducing the dimension of the square matrix to determine the nonlinearity property of the rows of the rearranged generating matrix after ordering the columns of the original generating matrix.

The Characteristics and Performance Style of Dance Art Based on the Perspective of New Media Environment

New media is the main means by which modern information technology can be rapidly promoted and occupies an increasingly important position in people's lives. Due to the great convenience of new media technology, further information exchange greatly ensures the timeliness and reliability of information transmission. This paper adopts the method of literature research to analyze that the development of new media technology has brought new elements to traditional dance art, resulting in significant changes in the expression and dissemination of dance art. This paper analyzes the characteristics and artistic styles of dance art in the new media environment, with the aim of promoting its better development and enabling dance art to adapt to the rapid development of the times.