Demand For Transmission Research Articles

Information-Theoretic Secure Key Sharing for Wide-Area Mobile Applications

With the rapid growth of handheld devices in the internet of things (IoT) networks, mobile applications have become ubiquitous in everyday life. As technology is developed, so do also the risks and threats associated with it, especially in the forthcoming quantum era. Existing IoT networks, however, lack a quantum-resistant secret key sharing scheme to meet confidential message transmission demands in wide-area mobile applications. To address this issue, this article proposes a new scheme, channel reciprocity (CR) based quantum key distribution (QKD) CRQKD, which accomplishes the goal of secret key sharing by combining emerging techniques of QKD and CR-based key generation (CRKG). Exploiting laws of quantum physics and properties of wireless channels, the proposed scheme is able to ensure the secrecy of the key, even against computationally unbounded adversaries. The basic mechanism is elaborated for a single-user case and it is extended into a multi-user case by redesigning a multi-user edge forwarding strategy. In addition, to make CR-QKD more practical, some enhancement strategies are studied to reduce the time delay and to improve the secret key generation rate in a secure manner. A prototype of CR-QKD is demonstrated in a metropolitan area network, where secret keys are shared between two remote IoT devices that are roughly fifteen kilometers apart from each other. The experimental results have verified that CR-QKD allows a secret key rate of 424 bits per second with a retransmission rate of 2.1%.

3D‐Printed Photonic Crystal Sub‐Terahertz Leaky‐Wave Antenna

AbstractWireless systems are facing increasing pressure due to the growing demand for data transmission. One potential solution to this problem is to shift communication frequencies toward the terahertz (THz) spectrum. However, this requires the development of new components that can efficiently process signals at these high frequencies and transmit them via highly directional beams. In this study, a novel approach is proposed to achieving efficient THz signal processing by combining two existing technologies: photonic crystals and leaky‐wave antennas. Incorporating a 2D photonic crystal inside a leaky‐wave waveguide allows to manipulate the wave vector of the guided wave in unique ways, which in turn impacts the far‐field radiation pattern emitted through the leaky‐wave aperture. The device fabrication uses 3D printing of alumina and allows for convenient and scalable manufacturing. Through numerical simulations and experiments, free‐space data transmission at rates of few hundred Mbps at a carrier frequency of 101.2 GHz is demonstrated. The findings illustrate the feasibility of photonic crystal‐based leaky‐wave antennas and lay the groundwork for the development of compact and high‐performance components for THz wireless communication systems.

An offloading method in new energy recharging based on GT-DQN

The utilization of green edge has emerged as a promising paradigm for the development of new energy vehicle (NEV). Nevertheless, the recharging of these vehicles poses a significant challenge in due to limited power resources and enormous transmission demands. A novel architecture based on Wifi-6 communication is proposed, which makes the most of heterogeneous edge nodes to achieve real-time processing and computation of tasks. To address the collaborative power resource optimization problem, the interference between different vehicles is considered, and the task offloading is optimized. In particular, the power contention among recharging clusters is modeled as an exact game and a task offloading strategy model is proposed jointly with the Deep Q-Network (DQN) algorithm, which is employed by a secondary application. Thereby, the recharging efficiency and task offloading computation are optimized and improved. Results indicate that the total resource consumption is favorably improved with this architecture and algorithm and the Nash equilibrium is also demonstrated.

Liquid hydrogen superconducting transmission based super energy pipeline for Pacific Rim in the context of global energy sustainable development

The global energy issue is undergoing transformation owing to various factors, such as climate change and geopolitics. In the long term, the primary pathways to achieve sustainable energy development remain the clean energy and global cooperation. As the largest energy consumption centers, the Asia Pacific and North America possess complementary energy profiles and developmental needs for cooperation. This paper analyses various electricity or hydrogen transmission technologies suitable for the Pacific Rim energy system. The liquid hydrogen superconducting energy pipelines possess the potential to fulfill the demands of long-distance and large-scale energy transmission. Building upon this technology, a super energy pipeline project connecting East Asia and North America across 12 time zones was proposed. It is composed of pipelines and relay energy stations, which can realize large-scale storage and transportation of renewable energy as well as the diversified energy supply at terminals. The techno-economic evaluation of the project has been comprehensively conducted, and the investment can be recovered within 10 years. The project is expected to boost the progress of renewable energy, ensure regional energy security and promote the sustainable development of global energy.

High-capacity medical information hiding scheme with P-tensor product secret image sharing for wireless body area networks

Given the escalating demand for information transmission in the resource-restricted wireless body area networks (WBANs), securing medical data and minimizing energy consumption are paramount. We present an innovative information hiding scheme that employs P-tensor product secret image sharing (PTP-SIS) and multiple information-hiders for WBANs. Considering the remarkable compression performance demonstrated by compressed sensing (CS), as well as its link to Shamir's (k, n) secret sharing method, using CS rather than traditional secret sharing techniques for image processing purposes could potentially help alleviate transmission burden of sensor nodes. However, utilizing CS to process high-dimensional signals poses a significant challenge due to the large dimensionality of the measurement matrix. The P-tensor product (PTP) is a tool that offers outstanding universality and can overcome the dimension limitations of traditional matrix multiplication, it is applied in the secret sharing stage. Moreover, applying the ideas of secret sharing leads to less stress on an individual device as well as lower communication spending, and multiple hiders have the ability to independently embed additional secrets into shadow images for efficient information backup. Theoretical analysis and experiments validate that the proposed scheme ensures information security and transmission efficiency while achieving superior image recovery performance and higher information embedding rates compared to other approaches.

Techno-economic analysis of hydrogen pipeline network in China based on levelized cost of transportation

Pipeline hydrogen transmission is a powerful method for the large-scale, long-distance transport of hydrogen and is pivotal for the rapid expansion of the hydrogen energy sector. In different scenarios of hydrogen transmission demand, the levelized cost of transportation can vary greatly, mainly due to the effects of scaling up the network construction. For hydrogen pipeline networks of different scales, it is essential to determine the right design parameters to ensure the transport is economically viable. This paper introduces a techno-economic analysis model tailored for hydrogen pipeline networks of various scales. Guided by design pressures, annual hydrogen transmission quality, and transmission distances, an engineering design and simulation of process flows were conducted. This simulation highlights crucial technical parameters, such as energy consumption benchmarks, equipment costs, and the distribution across the inlet station, pipeline, and enroute stations. The scale-up effects on the capital and operational costs within the network is also examined. In conclusion, the study shows how the levelized cost of transportation fluctuates based on the three design parameters, offering quantifiable data essential for the techno-economic assessment required for the deployment of hydrogen pipeline networks of varying scales. The findings suggest that the levelized cost of transportation ranges from 0.13 to 1.81 $/kg when the design pressure spans 4–10 MPa, the annual transmission quality is between 0.25 and 2 million tons, and the distance extends from 200 to 1800 km. For shorter distances and reduced hydrogen transmission quality, a diminished design pressure is advised. Conversely, as both the transportation distance and quality of hydrogen escalate, it becomes necessary to incrementally adjust the design pressure to optimize the levelized cost of transportation.

Chaotic map-based selective image encryption via diffusion and confusion

Industrial diversification and Technology have a drastic impact on the day-to-day life and economic growth of the country. Sharing multimedia content over the network has drastically increased. The multimedia data can be just social media images or some highly confidential data. There is a high demand for secure image transmission over networks in the age of the Internet and other transmission mediums. Since images are high-volume data, care must be taken to ensure that the security does not become computationally very expensive. To overcome these problems, we propose a method to encrypt the images selectively using a chaos map. Selective encryption is the process of encrypting an image so that only a piece of it is visible while the remainder is encrypted. This decreases the computational cost of the algorithm to a great extent. Selective encryption consists of two parts, public and private. The public part of the image is visible to everyone but the private part is only visible to the authorized user. The chaotic map is used for encrypting the image and providing security to the algorithm. Confusion and diffusion are used for key generation using pixel value substitution and scrambling. We use PSNR, histogram analysis, and correlation coefficient to verify the result.

Analysis of Lightweight Cryptographic Algorithms for IoT Gateways

This research work explores the growing role of IoT devices in daily life and the increasing demand for secure data transmission in different sectors like healthcare, military, etc. Moreover, this study focuses on the recent advancements in lightweight cryptography and compares various encryption algorithms in an IoT environment using real-time data. Employing Message Queuing Telemetric Transport (MQTT) protocol, this research work assess the time of encryption, memory usage, and CPU usage as key parameters. By standardizing iterations, key width, and block length, this study aims to identify optimal encryption solutions for IoT applications.

Influence of the digital file format on radiographic diagnostic in dentistry: a scoping review.

Given today's higher demand for online transmission of radiographic images, clinicians and regulatory agencies should be given the evidence they need to guide them in choosing the best image file format to be adopted. To this end, the present scoping review aims to explore, map, and evaluate the literature, with the object of reporting the influence of image file formats on dental diagnostic tasks by assessing intraoral radiographic images. This scoping review complies with PRISMA-ScR. It was customized to assess the risk of bias of the included studies, and was registered on the Open Science Framework platform. The data extraction protocol was developed based on the PCC acronym. An electronic search was conducted in six databases (Pubmed, Web of Science, Scopus, Embase, Lilacs, Cochrane) in December 2023. Original articles were screened, having observational, diagnostic accuracy, and consisting of in vivo or ex vivo laboratory studies investigating the influence of file formats on different diagnostic tasks in dentistry. Eighteen studies, published between the years 1996 and 2022, were included. The following data were extracted from the selected articles: article title, authors' citation, publication date, country, diagnostic task, image file formats tested, compression level, and main conclusion. The most widely investigated diagnostic task was caries lesions (n = 10), led by root resorptions (n = 3), root fractures (n = 2), periapical lesions (n = 2), and periodontal disease (n = 1). The most commonly used radiographic techniques were periapical (n = 12) and bitewing (n = 6). The most frequently investigated image file formats were JPEG (all studies) and TIFF (n = 10 studies). BMP, PNG, and JPEG2000 were also included in 7, 3 and 3 studies, respectively. No studies included the DICOM file format. In regard to the subjective assessment of the several dental diagnostic tasks, the studies mostly showed that the influence of the file formats was not significant (n = 10/55.5%). As for the quality assessment of the included papers, more than 70% of the studies featured a low risk of bias. Current evidence on image file formats and dental radiographic diagnosis is reliable. Any image file format can be used without impairing diagnostic accuracy.

Design of Intelligent City Communication Network Based on Internet of Things

Abstract In response to the advancements in Internet of Things (IoT) technology and the growing demands for data transmission, there is a crucial need for further integration of communication network technology with IoT to enhance efficiency. This paper presents the design of a multi-node communication network model utilizing the Orthogonal Frequency-Division Multiplexing (OFDM) algorithm. In the realm of physical layer parameter design, uplink, and downlink carriers are allocated based on OFDM symbols, employing the Zadoff-Chu (ZC) sequence as the pilot frequency sequence. Additionally, the Cyclic Redundancy Check (CRC) error-checking code is implemented to ensure the accuracy of network transmissions. The model proposed in this study is applied to the operational dynamics of traffic systems within a smart city, focusing on the security and operational efficiency of the traffic communication network. Empirical testing and analysis demonstrate that the communication network, as designed, is susceptible to malware attacks by 25.68%, representing the least vulnerability among the three algorithms assessed. Moreover, in examining the bus trip time distribution with the implementation of this model, the average running time is predominantly around 11.76 minutes, which is a reduction of 0.74 minutes compared to previous configurations, thereby indicating an improvement in operational efficiency.

Prospects for visible color for underwater wireless broadband communications

Nowadays, underwater wireless communications are realized through communication systems based on acoustic waves, electromagnetic waves (radiofrequency waves and low frequency waves), magnetic induction and visible light. This paper provides a basic problems and key aspects in the development of underwater wireless optical communication systems. The latter attracts considerable interest from science, industry and ecology as an effective solution to satisfy the rapidly increasing demands of underwater high data-rate transmission on at any depth. However, severe aquatic channel conditions (absorption, scattering, turbulence, etc.) significantly reduce the attainable communication ranges. The second serious problem limiting the functioning of wireless optical communication systems is the difficulty of aligning the transmitter beam with the receiver's field of view. Two main types between transmitter and receiver are considered: diffuse line-of-sign (wide-beam) configuration and point-to-point light-of-sign (narrow-beam) configuration. Diffuse line-of-sign communication have reduced alignment requirements, but data rates and distances are noticeably lower than in narrow-beam systems. The main technical solutions for adjusting the receiver and transmitter in narrow-beam communication systems are discussed in this paper.

Subject review: Image Compression Techniques

Research on image compression is now a hot area for both commercial and military academics. picture compression is required because of the quick expansion of digital media and the ensuing demand for less storage and efficient picture transmission. In order to retain the apparent visual quality of a picture while requiring fewer bits to express it digitally, image compression is used.

Reuse-based online joint routing and scheduling optimization mechanism in deterministic networks

Deterministic networks plan the entire network traffic and calculate the scheduling time to meet the critical traffic requirements of specific domains, enabling real-time and deterministic interaction of massive data. However, in dynamic industrial automation scenarios where devices undergo changes, existing mechanisms face challenges in quickly responding to dynamic transmission demand changes caused by rapid traffic migration. To address this issue, this paper proposes a reuse-based online scheduling mechanism that utilizes dynamic path planning of flows and coordinated scheduling of time slots to achieve deterministic transmission of dynamic flows. In the offline phase, the mechanism proposes a backbone link selection and a scalable intelligent routing strategy, constructs a set of routing and scheduling co-design constraints, and generates an offline scheduling table using an iterative scheduling algorithm. In the online scheduling phase, a reuse-based online scheduling algorithm is proposed to achieve rapid scheduling and deterministic transmission of dynamic real-time flows. It utilizes the offline scheduling results and the period offset of migrated flows. The reuse of offline scheduling results reduces computation time and expands the solution space. Experimental results demonstrate that the proposed mechanism achieves a maximum increase in scheduling success rate of 37.3% and reduces time costs by up to 66.6% compared to existing online scheduling algorithms.

Analysis of renewable energy consumption and economy considering the joint optimal allocation of “renewable energy + energy storage + synchronous condenser”

As renewable energy becomes increasingly dominant in the energy mix, the power system is evolving towards high proportions of renewable energy installations and power electronics-based equipment. This transition introduces significant challenges to the grid’s safe and stable operation. On the one hand, renewable energy generation equipment inherently provides weak voltage support, necessitating improvements in the voltage support capacity at renewable energy grid points. This situation leads to frequent curtailments and power limitations. On the other hand, the output of renewable energy is characterized by its volatility and randomness, resulting in substantial power curtailment. The joint intelligent control and optimization technology of “renewable energy + energy storage + synchronous condenser” can effectively enhance the deliverable capacity limits of renewable energy, boost its utilization rates, and meet the demands for renewable energy transmission and consumption. Initially, the paper discusses the mechanism by which distributed synchronous condensers improve the short-circuit ratio based on the MRSCR (Multiple Renewable Energy Station Short-Circuits Ratio) index. Subsequently, with the minimum total cost of system operation as the optimization objective, a time-series production simulation optimization model is established. A corresponding optimization method, considering the joint configuration of “renewable energy + energy storage + synchronous condenser,” is proposed. Finally, the effectiveness of the proposed method is verified through common calculations using BPA, SCCP, and the production simulation model, considering a real-world example involving large-scale renewable and thermal energy transmission through an AC/DC system. The study reveals that the joint intelligent control and optimization technology can enhance both the sending and absorbing capacities of renewable energy while yielding favorable economic benefits.

Comprehensive energy efficiency optimization algorithm for steel load considering network reconstruction and demand response

Industrial loads are usually energy intensive and inefficient. The optimization of energy efficiency management in steel plants is still in the early stage of development. Considering the topology of power grid, it is an urgent problem to improve the operation economy and load side energy efficiency of steel plants. In this paper, a two-level collaborative optimization method is proposed, which takes into account the dynamic reconstruction cost, transmission loss cost, energy cost and demand response benefit. The upper level objective is the optimization of topology in the grid structure to optimize the power loss and dynamic reconstruction costs of the grid. The lower level is the energy cost considering demand response, real time price and dynamic demand response price. Firstly, the mathematical models of stable load, impact load and the steel production line load are built. The key parameters are identified by the Back Propagation neural network algorithm according to the actual production data. Secondly, considering the constraints of grid structure and load operation capacity, the impact of dynamic grid loss and real-time dynamic electricity price on the energy efficiency of the whole grid are analyzed in depth. The optimal operation model considering the dynamic reconfiguration and grid tramission loss of distribution network is built. Taking a steel plant park in Northeast China as an example, it is proved that the optimization model can improve energy efficiency on the load side by optimizing energy consumption and demand response participation time on load side. The energy cost is reduced by 17.77% on the load side, the network loss is reduced by 1.8%, and the operating cost of the power grid is reduced by 26.2%, which has a positive effect on improving energy utilization efficiency, reducing distribution network loss, and improving overall economic efficiency.

Complementary scheduling rules for hybrid pumped storage hydropower-photovoltaic power system reconstructing from conventional cascade hydropower stations

The reconstruction of conventional cascade hydropower plants (CHP) into hybrid pumped storage hydropower plants (HPSH) by adding a pumping station has the potential to increase the hydropower's flexibility and promote the consumption of renewable energy into the power grid. However, the complex hydraulic and electric connections between cascade hydropower stations and multi-energy sources pose challenges to safe and economic operation. This study explores the complementary scheduling for hybrid pumped storage hydropower-photovoltaic (HPSH-PV) system and evaluates the operation benefit and risk. First, the complementary scheduling rules that consider the demand for long-distance and across-regions power transmission are proposed to guide the peak-shaving operation of the system. Then a case study is performed with a hydro-PV complementary project in China, and the benefit and risks are evaluated quantitatively while considering the uncertainty of PV power prediction. The results demonstrate that after a pumping station is added (1) the power generation profit can be increased, especially in the dry seasons and the upstream reservoir; (2) the regulation capacity and power-supply reliability of the upstream reservoir is increased, while that of the downstream reservoir is slightly reduced; (3) the reservoir water level fluctuation and operation risk increase, but it can be lowered as the inflow increases.

Experimental Testing and Validation of Adaptive Equalizer Using Machine Learning Algorithm

Due to the increasing demand for high-speed data transmission, wireless communication has become more advanced. Unfortunately, the various kinds of impairments that can occur when carrying data symbols through a wireless channel can affect the network performance. Some of the solutions that are proposed to address these issues include channel equalization, and that can be solved through machine learning techniques. In this paper, a hybrid approach is proposed that combines the features of tracking mode and training mode of adaptive equalizer. This method utilizes the concept of machine learning (ML) to classify different environments (highly, medium, low, open space cluttered) based on the measurements of their RF signal. The results of the study revealed that the proposed method can perform well in real-time deployments. The performance of ML algorithms namely Logistic Regression, KNN Classifier, SVM Classifier, Naive Bayes, Decision Tree classifier and Random Forest classifier is analyzed for different number of samples such as 10, 50 and 100. The performance of these algorithms is evaluated by comparing their accuracy, sensitivity, specificity, F1 score and Confusion Matrix. The objective of this study is to demonstrate that a single ML algorithm cannot perform well in all kinds of environments. In order to choose the best algorithm for a given environment, the decision device has to analyze the various factors that affect the performance of the system. For instance, the random forest classifier performed well in terms of accuracy (100 percent), specificity (100 percent), sensitivity (100 percent), and F1_score (100 percent). On the other hand, the logistic regression algorithm did not perform well in low cluttered environment.

Design analysis and optimization of chaotic systems for duration and carrier parallel index modulation

With the rapid advancement in communication technology, the demand for high speed and efficient transmission has increased significantly. Traditional communication systems are unable to meet these demands, and thus, this paper proposes a new correlated delay shift keying system for duration and carrier parallel index modulation (DCIM-CDSK) that employs duration and carrier parallel index modulation. The DCIM-CDSK system utilizes index mapping to transmit extra bits, while group mapping the timeslots on the carrier. By using spare timeslots in each group to transmit modulated information bits, the system achieves high-speed transmission with high efficiency. Additionally, the system introduces a noise reduction method to optimize the information-carrying signal to improve its noise immunity. The theoretical bit error rate (BER) equations is derived in the paper for the DCIM-CDSK system under Gaussian and Rayleigh fading channels, and compared them with practical simulations to validate the theoretical derivation. The paper also analyzes the BER of the system for a single longest timeslot length and mixed longest timeslot length, respectively. The simulation results show that the proposed DCIM-CDSK system has better noise immunity and higher transmission rates than other similar systems. In today's increasingly stringent requirements for communication systems, the DCIM-CDSK system, with its high spectral and energy efficiency, provides a feasible solution for the current communication system industry to realize large user group services and high bandwidth utilization efficiency. At the same time, because of the flexibility of the system between the transmission rate and BER performance, the communication system can get a better trade-off and balance between the two contradictions of effectiveness and reliability.

A transient flow analysis method for high-rate mud pulse telemetry in rotary steerable system

With the development of ultra-deep offshore and onshore deep-water wells, there is a growing demand for high-speed data transmission. Mud pulse telemetry (MPT) is the most commercially mature wireless data transmission method. The time-domain parameter analysis of the down-hole mud pulse pressure signal is useful to study the optimization measures of the down-hole signal. Currently, the main approaches are experiment and computational fluid dynamics (CFD) numerical simulations, but both methods are time-consuming and costly, which is not conducive to multi-parameter studies. transient flow modelis widely used to analyze water hammers in pipelines, but its application to mud pulse telemetry (MPT) systems has been less studied. In this paper, based on the classical transient flow equation, the method of characteristics (MOC) is used to solve the governing equation, and the boundary conditions suitable for the MPT are proposed and verified with the experiment and CFD method. Based on the newly established transient flow mathematical model, the generation characteristics of the downhole pressure wave and the influence law of key parameters are studied. The results show that the essence of continuous wave is a three-wave coupling of pressure wave, density wave and flow wave. With the transmission of continuous wave, unsteady friction will be generated in the wave region of the wellbore, increasing the attenuation degree of the signal. The amplitude of continuous wave increases with the increase of density and displacement, independent of frequency and viscosity. However, as the frequency and viscosity increase, the continuous wave will decay faster. This paper provides the new transient flow method with fast computational time and a technical means for MPT studies under subsequent drilling conditions.

Adaptive Load Balancing for Dual-Mode Communication Networks in the Power Internet of Things

As an important part of the power Internet of Things, the dual-mode communication network that combines the high-speed power line carrier (HPLC) mode and high-speed radio frequency (HRF) mode is one of the hot directions in current research. Since non-uniform transmission demands for power consumption information can lead to link congestion among nodes, improving the network load-balancing performance becomes a critical issue. Therefore, this paper proposes a load-balancing routing algorithm for dual-mode communication networks, which is achieved in dual-mode communication networks by adding alternate paths and proxy coordinator (PCO) node election mechanism. Simulation results show that the proposed algorithm achieves the load-balanced distribution of power consumption information transmission. The proposed scheme reduces the delay and packet loss rate, as well as improving the throughput of dual-mode communication compared to existing routing algorithms.