Design Of Communication Networks Research Articles

Dimensioning Space-Air-Ground Integrated Networks for In-Flight 6G Slice Orchestration

In this study, we present an in-depth analysis of communication services for commercial airline passengers, focusing on the challenges posed by increasing internet traffic demand. We explore the integration of satellite, airborne, and terrestrial networks, emphasizing the roles of Low Earth Orbit (LEO) satellites, High-Altitude Platform Station (HAPS), and Terrestrial Aviation Network (TAN)-based services. Our contribution includes a theoretical model for optimizing resource allocation and capacity planning in non-terrestrial wireless networks, using a bipartite graph approach and linear programming techniques. The model shows adaptability and efficiency, providing key insights through numerical analysis. Leveraging a detailed air traffic dataset, a machine learning-based aggregation method, and real-world network parameters, our research addresses current challenges, such as scalable network capacity dimensioning in high-density airspaces and meeting the demand for quality of service by robust resource provisioning, and advances the design of communication networks for Space–Air–Ground Integrated Network (SAGIN). Numerical results from European airspace suggest that complementing TAN and LEO satellite networks with HAPS-based services will be essential as airline passengers adopt ground-level internet usage patterns.

Optimization Problem for Probabilistic Time Intervals of Quasi-Deterministic Output and Self-Similar Input Data Packet Flow in Telecommunication Networks

Introduction. When managing traffic at the packet level in modern telecommunication networks, it is proposed to use methods that transform a self-similar stochastic packet flow into a quasi-deterministic one. To do this, it is required to apply complex probabilistic laws of distribution of self-similar flows. From the literature, methods of balancing the network load are known, which, with the problem indicated above, contribute to increasing the efficiency of telecommunication systems. However, there is no strictly mathematical solution to find out the optimal probabilistic characteristics of the output flow, based on the input flow. The presented research is intended to fill this gap. Its objective is to create a method for determining the optimal probabilistic characteristics of the packet flow, using the minimum value of the proximity measure of the self-similar input and quasi-deterministic output flows.Materials and Methods. To solve the research problem, the parameters of the output flow distribution were selected so that the approximation function was close to 𝛿𝛿-function. The Kullback-Leibler divergence was used as a proximity measure of the input and output distributions of time intervals. Methods of set theory, metric spaces, multidimensional optimization, and teletraffic were used. The solution algorithm included minimization of the Kullback-Leibler divergence and the limit passage to 𝛿𝛿-function.Results. A probability distribution is shown — an approximation of 𝛿𝛿-function, which maintains the equality of time intervals of a quasi-deterministic output packet flow. A method for transforming a self-similar input flow into a quasideterministic output flow is presented. The Kullback–Leibler divergence was used as a measure of their proximity. The minimum of the Kullback-Leibler divergence between the input and output flows with a normal distribution was achieved in the case of equality of the mathematical expectations of these flows. Using the passage to the limit, it has been established that time interval T between packets of the quasi-deterministic output flow must be equal to the mathematical expectation of the time intervals between packets of the input self-similar flow. To obtain a quasi-deterministic flow, the passage to the limit is performed for the found value of the mathematical expectation at σ → 0.Discussion and Conclusion. The application of this method will reduce the negative impact of self-similarity of network traffic on the efficiency of the telecommunication network. The use of quasi-deterministic flows makes it possible to predict the load of network resources, which can be the basis for improving the quality of user service. Two difficulties associated with calculations and practical implementation of the solution are eliminated. Firstly, it is difficult to use the delta function as a function of the output flow distribution density. Secondly, there are no ideal deterministic flows in the operation of telecommunication networks. The proposed method has great potential in the design and optimization of communication networks.

Unmanned-Aerial-Vehicle-Assisted Secure Free Space Optical Transmission in Internet of Things: Intelligent Strategy for Optimal Fairness.

In this article, we consider an UAV (unmanned aerial vehicle)-assisted free space optical (FSO) secure communication network. Since FSO signal is impossible to detect by eavesdroppers without proper beam alignment and security authentication, a BS employs FSO technique to transfer information to multiple authenticated sensors, to improve the transmission security and reliability with the help of an UAV relay with decode and forward (DF) mode. All the sensors need to first send information to the UAV to obtain security authentication, and then the UAV forwards corresponding information to them. Successive interference cancellation (SIC) is used to decode the information received at the UAV and all authenticated sensors. With consideration of fairness, we introduce a statistical metric for evaluating the network performance, i.e., the maximum decoding outage probability for all authenticated sensors. In particular, applying an intelligent approach, we obtain a near-optimal scheme for secure transmit power allocation. With a well-trained allocation scheme, approximate closed-form expressions for optimal transmit power levels can be obtained. Through some numerical examples, we illustrate the various design trade-offs for such a system. Additionally, the validity of our approach was verified by comparing with the result from exhaustive search. In particular, the result with DRL was only 0.3% higher than that with exhaustive search. These results can provide some important guidelines for the fairness-aware design of UAV-assisted secure FSO communication networks.

Optimal Communication Network Design for Discrete-Time Distributed Secondary Control of Islanded Microgrid

Optimal Communication Network Design for Discrete-Time Distributed Secondary Control of Islanded Microgrid

Real-Time Co-Simulation Implementation for Voltage and Frequency Regulation in Standalone AC Microgrid with Communication Network Performance Analysis across Traffic Variations

Effective communication networks are crucial for ensuring reliable and stable operation and control in smart microgrids (MGs). This paper proposes a comprehensive analysis of the interdependence between power and communication networks in the real-time control of a standalone AC microgrid to address this vital need. Thus, the role of communication network design is emphasized in facilitating an effective centralized secondary control to regulate the voltage and frequency of an MG. Consequently, voltage and frequency deviations from the droop-based primary control should be eliminated. This study employs a real-time co-simulation testbed setup that integrates OPAL-RT and network simulator (ns-3), supporting a rigorous evaluation of the interplay between the communication networks and control within the MG. Experiments have been conducted to demonstrate the effectiveness of the designed communication infrastructure in seamlessly enabling real-time data exchange among the primary and secondary control layers. Testing scenarios have been implemented, encompassing low-traffic patterns with minimal load variations and high traffic characterized by more frequent and severe load changes. The experimental results highlight the significant impact of traffic variations on communication network performance. Despite the increase in traffic, the effectiveness and reliability of the designed communication network have been validated, underscoring the vital role of communication in ensuring the resilient and stable operation of cyber–physical standalone AC microgrids.

К вопросу реализации алгоритмов проектирования защищенных сетей передачи данных

Existing approaches to the design of secure data transmission networks (DRN) are often based on guidelines for the design of communication networks in a broad sense, at the moment there are no clear regulations for the design of communication networks in a secure version from the point of view of information security. In the process of advanced design of the SPDS, problems arise in finding effective solutions for the construction of such communication networks and ensuring the information security of the SPDS in terms of information security tools (SIS) in given areas determined by information security measurements, such as the availability, accessibility, secrecy of information circulating in the SPDS. The article proposes algorithms based on the parameters of non-stationary hyper-network models, which make it possible to implement the analysis and synthesis of ZSPD, as well as take into account the initial data on the intended users, services/applications implemented on ZSPD under conditions of external destructive effects (VDV).

Algorithms of Cross-Domain Redundancy Management for Resilient of Dual-Priority Critical Communication Systems

The paper presents models for managing cross-domain redundancy to enhance the reliability of two priority communication channels within critical infrastructure systems. Employing Markov chain models, the paper analyzes the impact of two distinct redundancy management strategies: a unified reserve pool and a separate pool approach with cross-domain resource sharing. The study introduces reliability improvement factors to quantify system performance, exploring their dependency on the number of additional redundant elements, their inherent reliability, and the chosen strategy for managing cross-domain redundancy. An air traffic control system serves as a case study of the application of the proposed management algorithms. Results indicate that the integration of resources from different priority domains significantly improves communication reliability. The findings may be useful for the design and operation of secure communication networks.

A Graph Reinforcement Learning-Based Handover Strategy for Low Earth Orbit Satellites under Power Grid Scenarios

Amidst the escalating need for stable power supplies and high-quality communication services in remote regions globally, due to challenges associated with deploying a conventional power communication infrastructure and its susceptibility to natural disasters, LEO satellite networks present a promising solution for broad geographical coverage and the provision of stable and high-speed communication services in remote regions. Given the necessity for frequent handovers to maintain service continuity, due to the high mobility of LEO satellites, a primary technical challenge confronting LEO satellite networks lies in efficiently managing the handover process between satellites, to guarantee the continuity and quality of communication services, particularly for power services. Thus, there is a critical need to explore satellite handover optimization algorithms. This paper presents a handover optimization scheme that integrates deep reinforcement learning (DRL) and graph neural networks (GNN) to dynamically optimize the satellite handover process and adapt to the time-varying satellite network environment. DRL models can effectively detect changes in the topology of satellite handover graphs across different time periods by leveraging the powerful representational capabilities of GNNs to make optimal handover decisions. Simulation experiments confirm that the handover strategy based on the fusion of message-passing neural network and deep Q-network algorithm (MPNN-DQN) outperforms traditional handover mechanisms and DRL-based strategies in reducing handover frequency, lowering communication latency, and achieving network load balancing. Integrating DRL and GNN into the satellite handover mechanism enhances the communication continuity and reliability of power systems in remote areas, while also offering a new direction for the design and optimization of future power system communication networks. This research contributes to the advancement of sophisticated satellite communication architectures that facilitate high-speed and reliable internet access in remote regions worldwide.

Space-code division multiple access for broadband acoustic networks

We present an investigation into the design of an acoustic communication network, where multiple users are distributed across space and transmit and receive simultaneously in the same band to and from a common base station. Specifically, we focus on a system that utilizes orthogonal frequency division multiplexing as a modulation method, and allows users to transmit and receive in either synchronous or asynchronous fashion. To distinguish between users on the uplink, the base station employs a combination of code-division and space-division multiple access. The base station iteratively steers a beam to each stable propagation path of the desired user’s channel while placing nulls in the direction of other paths, as well as in the directions of interfering users. Finally, the multiple paths of the desired user are recombined before data detection. The process is repeated for each user. Broadband beamforming is employed to account for the broadband nature of acoustic signals. The beamformer coefficients on each carrier depend on the angles of signal arrivals, which are estimated during the uplink transmission and used to construct both the uplink and the downlink beamformer. On the downlink, the base station utilizes angle information to assemble beamforming weights and point in the direction of stable paths of the users. It superimposes multiuser signals and transmits the sum signal to the users. The signal intended for a given user reaches only that user, requiring just a simple detector. Each user is equipped by a single-element transducer. To demonstrate the design concepts, we conducted simulations using a shallow water channel model and performed experimental over-the-air tests in an indoor environment using an acoustic communications testbed. The results were excellent, thereby encouraging future implementations in practical systems.

Models of Chemical Communication for Micro/Nanoparticles.

Engineering chemical communication between micro/nanosystems (via the exchange of chemical messengers) is receiving increasing attention from the scientific community. Although a number of micro- and nanodevices (e.g., drug carriers, sensors, and artificial cells) have been developed in the last decades, engineering communication at the micro/nanoscale is a recent emergent topic. In fact, most of the studies in this research area have been published within the last 10 years. Inspired by nature─where information is exchanged by means of molecules─the development of chemical communication strategies holds wide implications as it may provide breakthroughs in many areas including nanotechnology, artificial cell research, biomedicine, biotechnology, and ICT. Published examples rely on nanotechnology and synthetic biology for the creation of micro- and nanodevices that can communicate. Communication enables the construction of new complex systems capable of performing advanced coordinated tasks that go beyond those carried out by individual entities. In addition, the possibility to communicate between synthetic and living systems can further advance our understanding of biochemical processes and provide completely new tailored therapeutic and diagnostic strategies, ways to tune cellular behavior, and new biotechnological tools. In this Account, we summarize advances by our laboratories (and others) in the engineering of chemical communication of micro- and nanoparticles. This Account is structured to provide researchers from different fields with general strategies and common ground for the rational design of future communication networks at the micro/nanoscale. First, we cover the basis of and describe enabling technologies to engineer particles with communication capabilities. Next, we rationalize general models of chemical communication. These models vary from simple linear communication (transmission of information between two points) to more complex pathways such as interactive communication and multicomponent communication (involving several entities). Using illustrative experimental designs, we demonstrate the realization of these models which involve communication not only between engineered micro/nanoparticles but also between particles and living systems. Finally, we discuss the current state of the topic and the future challenges to be addressed.

Molecular Beamforming for Actuation in Molecular Communication Networks.

The actuation accuracy of sensing tasks performed by molecular communication (MC) schemes is a very important metric. Reducing the effect of sensors fallibility can be achieved by improvements and advancements in the sensor and communication networks design. Inspired by the technique of beamforming used extensively in radio frequency communication systems, a novel molecular beamforming design is proposed in this paper. This design can find application in tasks related to actuation of nano machines in MC networks. The main idea behind the proposed scheme is that the utilization of more sensing nano machines in a network can increase the overall accuracy of that network. In other words, the probability of an actuation error reduces as the number of sensors that collectively take the actuation decision increases. In order to achieve this, several design procedures are proposed. Three different scenarios for the observation of the actuation error are investigated. For each case, the analytical background is provided and compared with the results obtained by computer simulations. The improvement in the actuation accuracy by means of molecular beamforming is verified for a uniform linear array as well as for a random topology.

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.

The Full m Index Sets of P2×Pn

Shiu and Kwong (2008) studied the full friendly index set of P2×Pn, which only addressed the cases where m=0 or 1. In this paper, we significantly extend their work by determining the full m index set MP2×Pn for all values of m. Our key approach is to utilize graph embedding and recursion methods to deduce MP2×Pn for general m. In particular, we embed small graphs like C4 and K2 into P2×Pn and apply recursive techniques to prove the main results. This work expands the scope of previous graph labeling studies and provides new insights into determining the full m index set of product graphs. Given the broad range of applications for labeled graphs, this research can potentially impact fields like coding theory, communication network design, and more.

Radio Map-Based Trajectory Design for UAV-Assisted Wireless Energy Transmission Communication Network by Deep Reinforcement Learning

In this paper, we consider a wireless energy-carrying communication network of a UAV. In this communication network, the internet of things (IoT) devices maintain their work via the power supply of batteries. The energy of batteries is slowly consumed over time. The UAV adopts the full-duplex working mode and the flight hover protocol, that is, they can power the target device in the hover position and collect base station data at the same time. Unlike traditional methods, which seek to achieve wireless energy transmission, this paper adopts deep reinforcement learning. On the one hand, the deep reinforcement learning algorithm seeks to solve the dynamic programming problem without a model. The traditional method often requires a prior channel model, to form a formula about variables for convex optimization, while reinforcement learning only requires the interaction between agents and the environment. Then, the strategy is optimized according to the reward function feedback. On the other hand, traditional optimization methods generally solve static programming problems. Since IoT devices constantly collect information from the surrounding physical environment, and their requirements for power supply change dynamically, traditional methods are relatively complex and require huge computational overhead, while deep reinforcement learning performs well in complex problems. The purpose of our work is that with the assistance of the radio map, a UAV can find the best hover position, maximize the energy supplied by the UAV, maximize the data throughput collected, and minimize the energy consumption. The simulation results show that the proposed algorithm can well find the best hovering position of the UAVs and significantly improve the performance of the UAV-assisted wireless energy transmission communication network.

Designing communication networks for discrete-time consensus for performance and privacy guarantees

Designing communication networks for discrete-time consensus for performance and privacy guarantees

Multiple-beam colloidal quantum dot lasers in a waveguide-grating-waveguide microcavity

In this work, multiple-beam colloidal quantum dot lasers are achieved in a double waveguide-grating (waveguide-grating-waveguide, W-G-W) microcavity. The grating is fabricated simply using interference lithography, and CdSe/CdS/ZnS colloidal quantum dots (CQDs) are spin-coated as the gain to form an active waveguide-grating structure. The photoresist film, which is not completely etched to the bottom, provides another waveguide-grating structure. In the W-G-W structure, low-threshold multiple-beam laser output is realized under optical pumping with emission peaks at 664.6 and 645.2 nm. The oblique laser is derived from a quasi-propagation mode. The thresholds of the two laser modes are 22.7 and 28.3 μJ/cm2, respectively, and both laser modes are TE0 modes. In addition, the emission wavelengths of the two modes of the designed distributed feedback laser can be flexibly tuned by changing the thickness of the CQDs' waveguide layer. The presence of quasi-propagation modes provides another method for designing compact laser sources, which could help in the design of wireless communication networks, hyperspectral 3D sensing, and color laser displays.

ENHANCING SECURITY IN SOFTWARE-DEFINED NETWORKING THROUGH ROUTING TECHNIQUES EXPLORATION

In today's world, network security is a key issue of information security. Virtual Networks have become an integral part of modern IT infrastructure, which presents us with challenges in the field of security. One solution to this problem is the use of software-defined networking (SDN), which provides a means to control and manage network traffic. However, as with any technology, SDN has its vulnerabilities that must be considered when deploying it. One of the tools that helps to take into account the vulnerabilities of network infrastructure is the Common Vulnerability Scoring System (CVSS) standard. It allows you to quantify the level of vulnerability of the infrastructure, which enables effective network protection. Analysis of the CVSS standard is an important stage in the development of a network security strategy. This paper analyzes the standards for building software-configured networks. It is noted that SDN is a modern approach to the design, construction, and operation of information communication networks. Using SDN makes it possible to directly program and dynamically manage the network, as well as to abstract the functionality of the infrastructure layer. However, the growing interest in SDN has revealed the shortcomings of their application in the fight against cybersecurity threats. The SDN architecture itself, external malicious attacks, and insufficient access control and encryption tools were found to be the main security challenges. The use of secure routing tools based on vulnerability metrics is proposed to increase the level of SDN data plane network security. According to the conducted analysis of SDN data plane vulnerabilities and the functionality of routing tools, the authors recommend using the CVSS standard to quantify the level of infrastructure vulnerability during the development and research of promising approaches to secure routing in the data plane of software-configured networks.

A Novel UAV-Assisted Multi-Mobility Channel Model for Urban Transportation Emergency Communications

With the increasing requirements for unmanned aerial vehicle (UAV) communication in various application scenarios, the UAV-assisted emergency communication in urban transportation scenario has received great attention. In this paper, a novel UAV-assisted UAV-to-vehicle (U2V) geometry-based stochastic model (GBSM) for the urban traffic communication scenario is proposed. The three-dimensional (3D) multi-mobilities of the transmitter (Tx), receiver (Rx), and clusters are considered by introducing the time-variant acceleration and velocity correspondingly. The velocity variation of the clusters is used to simulate the motion of vehicles around the Rx. Moreover, to describe the vehicles’ moving states, Markov chain is adopted to analyze the changes in cluster motion states, including survival, death, dynamic, and static states. By adjusting the scenario-specific parameters, such as the vehicle density (ρ) and dynamic–static ratio (Ω), the model can support various urban traffic scenarios. Based on the proposed model, several key statistical properties, namely the root mean square (RMS) delay spread, temporal autocorrelation function (ACF), level-crossing rate (LCR), power delay profile (PDP), and stationary interval, under different clusters and antenna accelerations are obtained and analyzed. The accuracy of the proposed model is verified by the measured data. The results demonstrate the usability of our model, which can be provided as a reference for the design, evaluation, and optimization of future communication networks between UAV and vehicles in urban transportation emergency communications.

Identification of Indoor Radio Environment Properties from Channel Impulse Response with Machine Learning Models

The design and optimization of next-generation indoor wireless communication networks require detailed and precise descriptions of the indoor environments. Environmental awareness can serve as a fundamental basis for the dynamic adaptation of the wireless system to channel conditions and can improve the system’s performance. Methods that combine wireless technology with machine learning are promising for identifying the properties of the indoor radio environment (RE) without requiring specialized equipment or manual intervention. In the paper, we propose an approach for identifying the materials of the surfaces using channel impulse response (CIR) and RE identification models built with machine learning. To train the models and assess their performance, we acquired radio propagation data from rooms with different sizes and materials using ray tracing. We explored tree-based methods, ensemble-based methods, kernel-based methods, and neural networks for training the models. The performance of the models is evaluated in three realistic scenarios defined by the location of the radio nodes and the room sizes. The multilayer perceptron models performed best in most of the evaluation settings. The results show that the models are capable of accurately predicting the materials in rooms with sizes that were not included in the training procedure. Including CIRs from a large number of rooms with different sizes and surface materials estimated with different radio node positions in the training process results in models with wider practical applicability.

Price of Anarchy and Price of Stability Mapping for Analyzing Topology Design of Communication Networks

The goal of game theory is to model actions among players or users in a common space who deal with various situations and face various outcomes. The study of game theory is widely applied to a wide range of economic fields, including auctions, renewable energy, wireless sensor networks, and software defined networks. Resource allocation and cooperation between networks or terminals are important in the field of game theory networking. In order to infer concrete solutions for the players, game formulas are used. A solution is determined by classifying players and calculating the Price of Anarchy (PoA) and Price of Stability (PoS) in order to determine Nash equilibrium and evaluate efficiency. Using the Open Systems Interconnection (OSI) layer as a lens, this study examines a variety of applications of game theory in non-cooperative environments and communication systems. This study focuses on the 'presence of governing' or participation nodes in a set of players in a network. Also, a comparison of different research fields in game theory is made.