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These developments have the potential to foster additional innovation, facilitate future problem-solving and optimisation strategies, and ultimately contribute to mature OWC technologies. Keywords: optical communication; underwater optical wireless communication EN optical communication underwater optical wireless communication 87 90 4 08/24/23 20230801 NES 230801 Since 2011, optical wireless communication (OWC) technologies have gained momentum. These technologies include visible light communications (VLC), underwater VLC, Li-Fi, optical camera communications (OCC), visible light positioning, visible light sensing and free space optics, among others. [Extracted from the article]

Imperfect Channel State Information at the Transmitter (CSIT) is inevitable in modern wireless communication networks, and results in severe multi-user interference in multi-antenna Broadcast Channel (BC). While the capacity of multi-antenna (Gaussian) BC with perfect CSIT is known and achieved by Dirty Paper Coding (DPC), the capacity and the capacity-achieving strategy of multi-antenna BC with imperfect CSIT remain unknown. Conventional approaches therefore rely on applying communication strategies designed for perfect CSIT to the imperfect CSIT setting. In this work, we break this conventional routine and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on the split of messages into common and private parts and linear precoding at the transmitter, and successive interference cancellation at the receivers, can achieve larger rate region than DPC in multi-antenna BC with partial CSIT. Second, we propose a novel scheme, denoted as Dirty Paper Coded Rate-Splitting (DPCRS), that relies on RS to split the user messages into common and private parts, and DPC to encode the private parts. We show that the rate region of DPCRS in Multiple-Input Single-Output (MISO) BC with partial CSIT is enlarged beyond that of conventional DPC and that of linearly precoded RS. Gaining benefits from the capability of RS to partially decode the interference and partially treat interference as noise, DPCRS is less sensitive to CSIT inaccuracies, networks loads and user deployments compared with DPC and other existing transmission strategies. [ABSTRACT FROM AUTHOR]

Social networks are an integral part of everyday life and work of modern people and one of the basic ways of communication and exchange of information among them. The desire for a quick exchange of information regarding scientific achievements and the need for their greater visibility have led to the emergence of social academic networks. Communication on social networks has its positive and negative aspects in both everyday and scientific lives. The need for face-to-face interaction is lost, but the connection and cooperation of researchers can be achieved regardless of place and time. Transparency and availability of scientific results are also provided. These possibilities are the basic characteristics of the Open Science movement. The science of the modern age depends on the visibility, accessibility and possibility of disseminating the results of scientific research. In this paper, an attempt has been made to present a number of academic social networks available to researchers, as well as to analyze their impact on the visibility of scientific results in the academic community. [ABSTRACT FROM AUTHOR]

Joint communications and sensing functionalities integrated into the same communication network have become increasingly relevant due to the large bandwidth requirements of next-generation wireless communication systems and the impending spectral shortage. While there exist system-level guidelines and waveform design specifications for such systems, an information-theoretic analysis of the absolute performance capabilities of joint sensing and communication systems that take into account practical limitations such as fading has not been addressed in the literature. Motivated by this, we undertake a network information-theoretic analysis of a typical joint communications and sensing system in this paper. Towards this end, we consider a state-dependent fading Gaussian multiple access channel (GMAC) setup with an additive state. The state process is assumed to be independent and identically distributed (i.i.d.) Gaussian, and non-causally available to all the transmitting nodes. The fading gains on the respective links are assumed to be stationary and ergodic and available only at the receiver. In this setting, with no knowledge of fading gains at the transmitters, we are interested in joint message communication and estimation of the state at the receiver to meet a target distortion in the mean-squared error sense. Our main contribution here is a complete characterization of the distortion-rate trade-off region between the communication rates and the state estimation distortion for a two-sender GMAC. Our results show that the optimal strategy is based on static power allocation and involves uncoded transmissions to amplify the state, along with the superposition of the digital message streams using appropriate Gaussian codebooks and dirty paper coding (DPC). This acts as a design directive for realistic systems using joint sensing and transmission in next-generation wireless standards and points to the relative benefits of uncoded communications and joint source-channel coding in such systems. [ABSTRACT FROM AUTHOR]

Offshore wind farms are growing in complexity and size, expanding deeper into maritime environments to capture stronger and steadier wind energy. Like other domains in the energy sector, the wind energy domain is continuing to digitalize its systems by embracing Industry 4.0 technologies such as the Industrial Internet of Things (IIoT), virtualization, and edge computing to monitor and manage its critical infrastructure remotely. Adopting these technologies creates dynamic, scalable, and cost-effective data-acquisition systems. At the heart of these data-acquisition systems is a communication network that facilitates data transfer between communicating nodes. Given the challenges of configuring, managing, and troubleshooting large-scale communication networks, this review paper explores the adoption of the state-of-the-art software-defined networking (SDN) and network function virtualization (NFV) technologies in the design of next-generation offshore wind farm IIoT–Edge communication networks. While SDN and NFV technologies present a promising solution to address the challenges of these large-scale communication networks, this paper discusses the SDN/NFV-related performance, security, reliability, and scalability concerns, highlighting current mitigation strategies. Building on these mitigation strategies, the concept of resilience (that is, the ability to recover from component failures, attacks, and service interruptions) is given special attention. The paper highlights the self-X (self-configuring, self-healing, and self-optimizing) approaches that build resilience in the software-defined IIoT–Edge communication network architectures. These resilience approaches enable the network to autonomously adjust its configuration, self-repair during stochastic failures, and optimize performance in response to changing conditions. The paper concludes that resilient software-defined IIoT–Edge communication networks will play a big role in guaranteeing seamless next-generation offshore wind farm operations by facilitating critical, latency-sensitive data transfers. [ABSTRACT FROM AUTHOR]

Over the last decade, the scientific interest in Mars drastically increased. The planned growth of the number of robotic missions, together with the sensors' increasing data acquisition capabilities and the expected crewed expeditions, entails a significant increase in data flow between the Martian assets and Earth both in volume and frequency of contact. In particular, crewed missions would lead to the need for nearly continuous communication with Martian assets. The keystone to avoid the future Martian telecommunication deadlock resides in specialising assets on specific functionalities through infrastructures. In this regard, the paper proposes a distributed Mars-based orbiting system servicing as a communication relay for any scientific and technological mission operating on the red planet's surface. The paper explores the design of a small satellites Martian constellation to maximise the surface coverage and visibility time with respect to ground users while reducing the station keeping efforts of the assets. A relatively novel proposed approach is to exploit the so-called Trans Areostationary Orbits (TASO), which allow low drift of the spacecraft with respect to Mars' surface, with an improved orbital stability than the perfectly stationary orbits. The paper aims at extending the available options by exploring trajectories that leverage the third body gravitation from the two Martian moons, Phobos and Deimos, to possibly further improve stability, coverage of the surface, communication datarates, and manoeuvres costs in general. The costs include the operative phase, as well as all the transfers from Earth to the Martian sphere of influence.As a final contribution, the paper explores the concept of Linked, Autonomous, Interplanetary Satellite Orbit Navigation (LiAISON) (Hill, 2007) for the proposed constellation configurations, to verify the possibility of reconstructing the spacecraft states through relative-only measurements. [ABSTRACT FROM AUTHOR]

The miniaturization and low power consumption characteristics of RF MEMS (Radio Frequency Microelectromechanical System) switches provide new possibilities for the development of microsatellites and nanosatellites, which will play an increasingly important role in future space missions. This paper provides a comprehensive review of RF MEMS switches in satellite communication, detailing their working mechanisms, performance optimization strategies, and applications in reconfigurable antennas. It explores various driving mechanisms (electrostatic, piezoelectric, electromagnetic, thermoelectric) and contact mechanisms (capacitive, ohmic), highlighting their advantages, challenges, and advancements. The paper emphasizes strategies to enhance switch reliability and RF performance, including minimizing the impact of shocks, reducing driving voltage, improving contacts, and appropriate packaging. Finally, it discusses the enormous potential of RF MEMS switches in future satellite communications, addressing their technical advantages, challenges, and the necessity for further research to optimize design and manufacturing for broader applications and increased efficiency in space missions. The research findings of this review can serve as a reference for further design and improvement of RF MEMS switches, which are expected to play a more important role in future aerospace communication systems. [ABSTRACT FROM AUTHOR]

Underwater acoustic (UWA) channel prediction technology, as an important topic in UWA communication, has played an important role in UWA adaptive communication network and underwater target perception. Although many significant advancements have been achieved in underwater acoustic channel prediction over the years, a comprehensive summary and introduction is still lacking. As the first comprehensive overview of UWA channel prediction, this paper introduces past works and algorithm implementation methods of channel prediction from the perspective of linear, kernel-based, and deep learning approaches. Importantly, based on available at-sea experiment datasets, this paper compares the performance of current primary UWA channel prediction algorithms under a unified system framework, providing researchers with a comprehensive and objective understanding of UWA channel prediction. Finally, it discusses the directions and challenges for future research. The survey finds that linear prediction algorithms are the most widely applied, and deep learning, as the most advanced type of algorithm, has moved this field into a new stage. The experimental results show that the linear algorithms have the lowest computational complexity, and when the training samples are sufficient, deep learning algorithms have the best prediction performance. [ABSTRACT FROM AUTHOR]

The ever-growing threats in cybersecurity growing with the rapid development of quantum computing, necessitates the development of robust and quantum-resistant cryptographic systems. This paper introduces a novel cryptosystem, Public Key Cryptosystem based on Systematic Polar Encoding (PKC-SPE), based on the combination of systematic polar encoding and public-key cryptographic principles. The Systematic Polar Encoding (SPE), derived from the well-established field of polar codes, serves as the foundation for this proposed cryptographic scheme. Here, we have used MATLAB Software to introduce and implement the PKC-SPE Cryptosystem. The paper examines key generation, encryption, and decryption algorithms, providing insights into the adaptability and efficiency of systematic polar encoding in public-key cryptography. We assess the efficiency of the PKC-SPE Cryptosystem in three aspects: key size, computational complexity, and system implementation timings. In addition, we compare the PKC-SPE Cryptosystem with PKC-PC cryptosystem and find that it has reduced key sizes ( P r = 0.8436 kbytes). The results obtained through simulations validate the effectiveness of the proposed cryptosystem and highlighting its potential for integration into real-world communication systems. Thus, in the paradigm shift to quantum computing, the PKC-SPE cryptosystem emerges as a promising candidate to secure digital communication in the quantum computing era. [ABSTRACT FROM AUTHOR]

Some passive sensors can provide only relative angles of a signal source. To obtain the signal source location, multiple passive sensors can be constructed into a passive sensor network through communication links. This paper investigates the source localization problem with angle-only measurements in three-dimensional space. First, we present an intersection localization method, which estimates the target position by minimizing the sum of distances between lines formed by angle-only measurements. It has the same target position estimate as the widely used least-squares (LS) method, but with a lower computational cost. Furthermore, considering the differences in measurement accuracy of sensors, the weighted least-squares (WLS) algorithm can achieve better localization performance than the LS method. Unfortunately, since the coefficient matrix and the noise vector are correlated, the WLS method is biased. The bias-compensation WLS (BCWLS) method is also presented in this paper to reduce the bias by estimating the correlation between the coefficient matrix and the pseudolinear noise vector. To evaluate the performance of the presented algorithms, numerical simulations are conducted, indicating that the superiority of the intersection localization method in computational cost and the superiority of the BCWLS method in localization accuracy. [ABSTRACT FROM AUTHOR]

In the context of Industry 4.0, industrial production equipment needs to communicate through the industrial internet to improve the intelligence of industrial production. This requires the current communication network to have the ability of large-scale equipment access, multiple communication protocols/heterogeneous systems interoperability, and end-to-end deterministic low-latency transmission. Time-sensitive network (TSN), as a new generation of deterministic Ethernet communication technology, is the main development direction of time-critical communication technology applied in industrial environments, and Wi-Fi technology has become the main way of wireless access for users due to its advantages of high portability and mobility. Therefore, accessing WiFi in the TSN is a major development direction of the current industrial internet. In this paper, we model the scheduling problem of TSN and WiFi converged networks and propose a scheme based on a greedy strategy distributed estimation algorithm (GE) to solve the scheduling problem. Compared with the integer linear programming (ILP) algorithm and the Tabu algorithm, the algorithm implemented in this paper outperforms the other algorithms in being able to adapt to a variety of different scenarios and in scheduling optimization efficiency, especially when the amount of traffic to be deployed is large. [ABSTRACT FROM AUTHOR]

Ionospheric scintillation is a common phenomenon in the equatorial, auroral, and polar areas, posing a threat to the Global Navigation Satellite System's (GNSS) operation. This ionospheric effect is thought to impact satellite signal propagation, hence, lowering positioning accuracy. Therefore, detecting ionospheric scintillation is critical in enhancing GNSS performance, particularly at low latitudes with severe amplitude scintillation. This paper investigates the effects of ionospheric scintillation on GPS signals at UNIMAS station, the East part of Malaysia. This study aims to identify the occurrence of ionospheric scintillation by calculating the index of scintillation strength during solar maximum 2014. The amplitude scintillation, which is measured in the S 4 index is obtained and classified accordingly from the data recorded at the UNIMAS station. The results have shown that strong scintillation (S 4 ≥ 0.5) occurred in the spring (April) and autumn (September and October) seasons, reaching 8 incidents. This paper also presents the diurnal, seasonal, and solar activity dependence of ionospheric scintillation. It is evident that the occurrence of amplitude scintillation is influenced by variations in solar activity, including solar flares and sunspots, as well as diurnal and seasonal changes. These findings provide valuable insights into the behaviour of the ionosphere and its impact on space-based communication and navigation systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the consensus control problem of Euler–Lagrange systems which can be used to describe the motion of various mechanical systems such as manipulators and quadcopters. We focus on consensus control strategies, which are important for achieving coordinated behavior in multi-agent systems. The paper considers the key challenges posed by random communication delays and packet losses that are increasingly common in networked control systems. In addition, it is assumed that each system receives information from neighboring agents intermittently. Addressing these challenges is critical to ensure the reliability and efficiency of such systems in real-world applications. Communication delay is time-varying and can be very large, but should be smaller than some bounded constant. To decrease the frequency of control input updates, we implement an event-triggered scheme that regulates the controller's updates for each agent. Specifically, it does not update control inputs at traditional fixed intervals, but responds to predefined conditions and introduces a dynamic consensus item to handle information irregularities caused by communication delays and intermittent information exchange. The consensus can be achieved if the communication graph of agents contains a spanning tree with the desired velocity as the root node. That is, all Euler–Lagrange systems need to obtain the desired velocity, directly or indirectly (via neighbors), to reach consensus. We establish that the Zeno behavior can be avoided, ensuring a positive minimum duration between successive event-triggered instances. Finally, we provide simulation results to show the performance of our proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper presents our research on a traffic signal control system (TSCS) at V2X intersections. The overall objective of the study is to create an implementable TSCS. The specific objective of this paper is to investigate a distributed system towards implementation. The objective function of minimizing queue delay is formulated as the integral of queue lengths. The discrete queueing estimation is mixed with macro and micro traffic flow models. The novel proposed architecture alleviates the communication network bandwidth constraint by processing BSMs and computing queue lengths at the local intersection. In addition, a two-stage distributed system is designed to optimize offsets, splits, and cycle length simultaneously and in real time. The paper advances TSCS theories by contributing a novel analytic formulation of delay functions and their first degree of derivatives for a two-stage optimization model. The open-source traffic simulation engine Enhanced Transportation Flow Open-Source Microscopic Model (ETFOMM version 1.2) was selected as a simulation environment to develop, debug, and evaluate the models and the system. The control delay of the major direction, minor direction, and the total network were collected to assess the system performance. Compared with the optimized TSCS timing plan by the Virginia Department of Transportation, the system generated a 21% control delay reduction in the major direction and a 7% control delay reduction in the minor direction at just a 10% penetration rate of connected vehicles. Finally, the proposed distributed and centralized systems present similar performances in the case study. [ABSTRACT FROM AUTHOR]

Many properties of the structure and dynamics of complex networks derive from the characteristics of the spectrum of the associated Laplacian matrix, specifically from the set of its eigenvalues. In this paper, we show that there exist graphs for which the ratio between the length of the spectrum (that is, the difference between the largest and smallest eigenvalues of the Laplacian matrix) and its spread (the difference between the second smallest eigenvalue and the smallest one) is equal to the golden ratio. We call such graphs Golden Laplacian Graphs (GLG). In this paper, we first find all such graphs with a number of nodes n ≤ 10 . We then prove several graph-theoretic and algebraic properties that characterize these graphs. These graphs prove to be extremely robust, as they have large vertex and edge connectivity along with a large isoperimetric constant. Finally, we study the synchronization properties of GLGs, showing that they are among the top synchronizable graphs of the same size. Therefore, GLGs represent very good candidates for engineering and communication networks. [ABSTRACT FROM AUTHOR]

With the rapid development of information transfer technology and the influence of complex electromagnetic environment, the signal components in communication systems are becoming more and more complex, and the spectrum congestion is further aggravated, which seriously affects the performance of communication systems. Single-channel blind source separation technology is an effective solution, but the existing algorithms are deficient in terms of estimation accuracy, time delay and computational complexity. Based on the powerful feature extraction capability and timing signal processing capability of deep learning, this paper proposes an end-to-end time-domain blind separation convolutional network structure, including three parts: encoder, separation module and decoder. The attention mechanism module is also introduced into the encoding layer of the network to enhance the deep feature extraction ability of the network, highlight the influence of important timing features of communication signals, further improve the separation performance and enhance the practicality of the network. The experimental results show that the algorithm has superior performance and can effectively separate the mixed communication signal of various modulation types, and it can also extract own-side communication signals from high-power masked signals. Compared with the existing algorithms, the network in this paper has high separation accuracy and low computational complexity, which breaks the bottleneck of traditional single-channel blind separation algorithms in complex communication electromagnetic environment. [ABSTRACT FROM AUTHOR]

This article discusses a special issue of the International Conference on Computing and Communications Networks (ICCCN 2022), which focuses on various topics in computing and networking. The special issue includes 12 selected papers that cover a range of subjects, such as code-mixed language identification, sentiment analysis, sleep quality assessment, gait analysis, cervical precancerous lesion classification, marine radar monitoring, text summarization, software optimization, fault diagnosis, imbalanced data analysis, neonatal hypoglycemia brain injury, and feature selection for classification problems. The authors present their research methodologies, experimental results, and conclusions for each paper. The guest editors hope that the research contributions in this special issue will be beneficial to readers. [Extracted from the article]

This paper presents a new polar logic circuit using a single current conveyor, two MOS switches and two resistors in each case. Thus, polar NAND and NOR circuits are proposed. The circuits' operation details and simulation results are given in support of the proposed theory. The circuits are designed using CMOS CCII + with ±2 V supply voltage. The polar logic levels at the output are −1 and 1 V for logic 0 and 1, respectively. The gates' functioning for capacitive loading is also tested. The new circuits are expected to be useful in digital and communication systems. [ABSTRACT FROM AUTHOR]

This paper proposes a compact design of dual-sense circularly polarized (CP) antenna for simultaneous transmit (Tx) and receive (Rx) communication systems. The primary radiating aperture of the proposed antenna is a 2 × 2 unit-cell metasurface (MS). The MS is excited by the asymmetric patch in the center, which acts as the CP source of the whole antenna structure. By properly tuning the feeding positions, dual-sense CP with high isolation can be achieved. For verification, an antenna prototype with compact dimensions of 0.36λ × 0.36λ × 0.02λ (λ is the free-space wavelength at the center operating frequency) is fabricated and measured. The measured operating bandwidth is 1.6% (2.45–2.49 GHz), in which the reflection and transmission coefficients are less than—10 dB and the axial ratio is lower than 3 dB. Within this band, the maximum isolation value is 39 dB, and the peak gain is 5.7 dBi. [ABSTRACT FROM AUTHOR]

Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol's operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space. [ABSTRACT FROM AUTHOR]

In this paper, based on linear matrix inequality technique, a simple controller and a compensatory controller are designed. It can track arbitrary fixed points and any periodic orbits. In addition, a synchronization control method via Chebyshev neural network with external disturbances is proposed. An adaptive controller is given. The Chebyshev neural network is used to approximate the uncertain nonlinear function and the adaptive law is used to adjust the corresponding parameters in the system. Taking a 4D memristive chaotic system as examples, the results are in consistent with the simulations. From a framework and control theoretical point of view, the proposed synchronization approach via compensation controller and Chebyshev neural network is firstly presented. From an application point of view, the proposed scheme can simplify the complexity of controller design. It is promising in many applications for mem-systems as secure communications and neural networks. [ABSTRACT FROM AUTHOR]

The growing number of vehicles on the roads has resulted in several challenges, including increased accident rates, fuel consumption, pollution, travel time, and driving stress. However, recent advancements in intelligent vehicle technologies, such as sensors and communication networks, have the potential to revolutionize road traffic and address these challenges. In particular, the concept of platooning for autonomous vehicles, where they travel in groups at high speeds with minimal distances between them, has been proposed to enhance the efficiency of road traffic. To achieve this, it is essential to determine the precise position of vehicles relative to each other. Global positioning system (GPS) devices have an intended positioning error that might increase due to various conditions, e.g., the number of available satellites, nearby buildings, trees, driving into tunnels, etc., making it difficult to compute the exact relative position between two vehicles. To address this challenge, this paper proposes a new architectural framework to improve positioning accuracy using images captured by onboard cameras. It presents a novel algorithm and performance results for vehicle positioning based on GPS and video data. This approach is decentralized, meaning that each vehicle has its own camera and computing unit and communicates with nearby vehicles. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of mobility on underwater acoustic communication networks in which the propagation delay is comparable to or larger than the packet duration. An underwater acoustic wireless network, consisting of static and mobile nodes, is studied for its link-layer channel utilization. Synchronous and asynchronous media access control (MAC) protocols are employed with ALOHA, TDMA (time-division multiple access), and artificial intelligence (AI) agent nodes. The simulation results of a multi-node network show that the asynchronous MAC protocols achieve up to 6.66× higher channel utilization than synchronous protocols by allowing time slots to be shorter than the maximum propagation delay among nodes and permitting asynchronous transmission time. The high mobility of a few mobile nodes also favors asynchronous protocols and increases the overall channel utilization. However, node mobility causes more difficulties for the AI node to learn the environment, which may be ineffective to achieve higher gains in channel utilization. [ABSTRACT FROM AUTHOR]

Circular antenna arrays (CAAs) find extensive utility in a range of cutting-edge communication applications such as 5G networks, the Internet of Things (IoT), and advanced beamforming technologies. In the realm of antenna design, the side lobes levels (SLL) in the radiation pattern hold significant importance within communication systems. This is primarily due to its role in mitigating signal interference across the entire radiation pattern's side lobes. In order to suppress the subsidiary lobe, achieve the required primary lobe orientation, and improve directivity, an optimization problem is used in this work. This paper introduces a method aimed at enhancing the radiation pattern of CAA by minimizing its SLL using a Hybrid Sooty Tern Naked Mole-Rat Algorithm (STNMRA). The simulation results show that the hybrid optimization method significantly reduces side lobes while maintaining reasonable directivity compared to the uniform array and other competitive metaheuristics. [ABSTRACT FROM AUTHOR]

A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of heterogeneous Quality of Service metrics makes it advantageous for the development of routing models where various technical–economic aspects, often conflicting, should be tackled. Our work is focused on multiobjective path problem formulations and resolution methods and their applications to routing methods. We review basic concepts and present main formulations of multiobjective path problems, considering different types of objective functions. We outline the different types of resolution methods for these problems, including a classification and overview of relevant algorithms concerning different types of problems. Afterwards, we outline background concepts on routing models and present an overview of selected papers considered as representative of different types of applications of multiobjective path problem formulations and algorithms. A broad characterization of major types of path problems relevant in this context is shown regarding the overview of contributions in different technological and architectural network environments. Finally, we outline research trends in this area, in relation to recent technological evolutions in communication networks. [ABSTRACT FROM AUTHOR]

This paper studies the input‐to‐state stability of an uncertain switched linear system with external disturbances, whose feedback loop is closed over a digital communication network. In the network, only a finite bit rate can be provided to transmit the feedback signal and unknown network delay always exists. By using reachable set approximation and propagation methods, it can well handle with the effects of model uncertainty, external disturbances and network delay on the stability of the system. To save network resources, event‐triggered sampling is taken here. Under the event‐triggered sampling strategies, a new encoder is proposed, which consumes less feedback bits than the conventional time‐triggered encoders. It is proven that even in the existence of model uncertainty, external disturbances and network delay, the proposed event‐triggered sampling strategies require a lower feedback bit rate to stabilize the switched system than conventional periodic sampling methods. To save network resources, event‐triggered sampling is taken here. Under the event‐triggered sampling strategies, a new encoder is proposed, which consumes less feedback bits than the conventional time‐triggered encoders. It is proven that even in the existence of model uncertainty, external disturbances and network delay, the proposed event‐triggered sampling strategies require a lower feedback bit rate to stabilize the switched system than conventional periodic sampling methods. [ABSTRACT FROM AUTHOR]

This paper proposed a new disturbance observer (DO) based on the fixed-time supper-twisting algorithm (FTSTA) for rejecting perturbations of secure communication of the fractional-order chaotic systems (FOCSs). First, the FOCSs are remodeled into the Takagi–Sugeno fuzzy (TSF) system with the expectation of softening the calculations of the design of the controller and observer. Second, the synchronization control was designed based on the FTSTA sliding mode control (SMC). Third, a new DO for the secure communication system (SCS) of FOCSs was proposed to estimate the disturbance on public channels and uncertainty variations. Fourth, the stability of the proposed synchronization control was obtained by using the Lyapunov condition. Finally, to verify the correction of the proposed method, the MATLAB simulation with the use of FONCOM toolbox was used to meet the desired expectations of theoretically proposed method. There are, small reaching times, small steady-states, and most tested disturbances and parameters' variations were compensated by the proposed DO. [ABSTRACT FROM AUTHOR]

This paper investigates the design of transmit beamforming in an integrated sensing and communication system, where an unmanned aerial vehicle (UAV) equipped with a uniform linear array (ULA) transmits combined information‐carrying and dedicated sensing signals to perform multi‐user communication and simultaneously sense potential targets. First, the transmit beamforming design is formulated as a series of non‐convex optimisation problems, and then jointly design the information and sensing beamforming to maximise the minimum communication rate under an optimised UAV deployment location, subject to the sensing beampattern gain requirements and the limited transmit power of the UAV. However, due to the application of ULA on the UAV, the formulated problems are highly non‐convex and difficult to solve optimally. To address the aforementioned issue, an efficient algorithm is proposed to find suboptimal yet high‐quality solutions. This is achieved by adopting the successive convex approximation and semidefinite relaxation. The numerical results confirm the effectiveness of the proposed algorithm and demonstrate that the transmit beamforming design achieves a balance between communication and sensing performance. [ABSTRACT FROM AUTHOR]

The reconfiguration of wireless channels with reconfigurable reflecting surface (RIS) technology offers new design options for future wireless networks. Due to its high altitude and increased probability of establishing line-of-sight linkages with ground source/destination nodes, aerial RIS (ARIS) has greater deployment flexibility than traditional terrestrial RIS. It also provides a wider-view signal reflection. To leverage the advantages of ARIS-enabled systems, this paper defines air-to-ground linkages via Nakagami-m small-scale fading and inverse-Gamma large-scale shadowing, considering realistic composite fading channels. To construct a tight approximate closed-form formula for the outage probability (OP), a new mathematical framework is proposed. Additionally, a deep-learning-based system called the BiLSTM model is deployed to evaluate OP performance in the 3D spatial movement of the ARIS system. In the offline phase, the proposed model is trained with real-value channel state estimation sets and enhances OP performance in the online phase by learning channel information in a bidirectional manner. Simulation results demonstrate that the proposed BiLSTM model outperforms all other models in analyzing OP for the ARIS system. [ABSTRACT FROM AUTHOR]

Ambient noise tomography on the basis of distributed acoustic sensing (DAS) deployed on existing telecommunication networks provides an opportunity to image the urban subsurface at regional scales and high-resolution. This capability has important implications in the assessment of the urban subsurface's potential for sustainable and safe utilization, such as geothermal development. However, extracting coherent seismic signals from the DAS ambient wavefield in urban environments at low cost remains a challenge. One obstacle is the presence of complex sources of noise in urban environments, which may not be homogeneously distributed. Consequently, long recordings are required for the calculation of high-quality virtual shot gathers, which necessitates significant time and computational cost. In this paper, we present the analysis of 15 d of DAS data recorded on a pre-existing fibre optic cable (dark fibres), running along an 11-km-long major road in urban Berlin (Germany), hosting heavy traffic including vehicles and trains. To retrieve virtual shot gathers, we apply interferometric analysis based on the cross-correlation approach where we exclude low-quality virtual shot gathers to increase the signal-to-noise ratio of the stacked gathers. Moreover, we modify the conventional ambient noise interferometry workflow by incorporating a coherence-based enhancement approach designed for wavefield data recorded with large-N arrays. We then conduct multichannel analysis of surface waves to retrieve 1-D velocity models for two exemplary fibre subsegments, and compare the results of the conventional and modified workflows. The resulting 1-D velocity models correspond well with available lithology information. The modified workflow yields improved dispersion spectra, particularly in the low-frequency band (<1 Hz) of the signal. This leads to an increased investigation depth along with lower uncertainties in the inversion result. Additionally, these improved results were achieved using significantly less data than required using conventional approaches, thus opening the opportunity for shortening required acquisition times and accordingly lowering costs. [ABSTRACT FROM AUTHOR]

In different modern and future wireless communication networks, a large number of low-power user equipment (UE) devices like Internet of Things, sensor terminals, and smart modules have to be supported over constrained power and bandwidth resources. Therefore, wireless-powered communication (WPC) is considered a promising technology for varied applications in which the energy harvesting (EH) from radio frequency radiations is exploited for data transmission. This requires efficient resource allocation schemes to optimize the performance of WPC and prolong the network lifetime. In this paper, harvest-then-transmit-based WP non-orthogonal multiple access (WP-NOMA) system is designed with time-split (TS) and power control (PC) allocation strategies. To evaluate the network performance, the sum rate and UEs' rates expressions are derived considering power-domain NOMA with successive interference cancellation detection. For comparison purposes, the rate performance of the conventional WP orthogonal multiple access (WP-OMA) is derived also considering orthogonal frequency-division multiple access and time-division multiple access schemes. Intensive investigations are conducted to obtain the best TS and PC resource parameters that enable maximum EH for higher data transmission rates compared with the reference WP-OMA techniques. The achieved outcomes demonstrate the effectiveness of designed resource allocation approaches in terms of the realized sum rate, UE's rate, rate region, and fairness without distressing the restricted power of far UEs. [ABSTRACT FROM AUTHOR]

Road safety is a serious concern worldwide, and traffic signs play a critical role in confirming road safety, particularly in the context of AVs. Therefore, there is a need for ongoing advancements in traffic sign evaluation methodologies. This paper comprehensively analyzes the relationship between traffic sign retroreflectivity and LiDAR intensity to enhance visibility and communication on road networks. Using Python 3.10 programming and statistical techniques, we thoroughly analyzed handheld retroreflectivity coefficients alongside LiDAR intensity data from two LiDAR configurations: 2LRLiDAR and 1CLiDAR systems. The study focused specifically on RA1 and RA2 traffic sign classes, exploring correlations between retroreflectivity and intensity and identifying factors that may impact their performance. Our findings reveal variations in retroreflectivity compliance rates among different sign categories and color compositions, emphasizing the necessity for targeted interventions in sign design and production processes. Additionally, we observed distinct patterns in LiDAR intensity distributions, indicating the potential of LiDAR technology for assessing sign visibility. However, the limited correlations between retroreflectivity and LiDAR intensity underscore the need for further investigation and standardization efforts. This study provides valuable insights into optimizing traffic sign effectiveness, ultimately contributing to improved road safety conditions. [ABSTRACT FROM AUTHOR]

The increased seismic activity observed in the Himalayas, coupled with the expanding urbanization of the surrounding areas in northern India, poses significant risks to both human lives and property. Developing an earthquake early warning system in the region could help in alleviating these risks, especially benefiting cities and towns in mountainous and foothill regions close to potential earthquake epicenters. To address this concern, the government and the science and engineering community collaborated to establish the Uttarakhand State Earthquake Early Warning System (UEEWS). The government of Uttarakhand successfully launched this full-fledged operational system to the public on 4 August 2021. The UEEWS includes an array of 170 accelerometers installed in the seismogenic areas of the Uttarakhand. Ground motion data from these sensors are transmitted to the central server through the dedicated private telecommunication network 24 hours a day, seven days a week. This system is designed to issue warnings for moderate to high-magnitude earthquakes via a mobile app freely available for smartphone users and by blowing sirens units installed in the buildings earmarked by the government. The UEEWS has successfully issued alerts for light earthquakes that have occurred in the instrumented region and warnings for moderate earthquakes that have triggered in the vicinity of the instrumented area. This paper provides an overview of the design of the UEEWS, details of instrumentation, adaptation of attributes and their relation to earthquake parameters, operational flow of the system, and information about dissemination of warnings to the public. [ABSTRACT FROM AUTHOR]

With increasing needs for high-bitrate, ultra-reliability, spectral efficiency, power efficiency, and reducing latency in the wireless network, global studies on the sixth generation of this network began in 2020. In this paper, we will look at intelligent reconfigurable surface structure and its application in new promising physical layer technologies, such as terahertz communications and UM-MIMO systems, to support very high-bitrate and superior network capacity in the 6G wireless communications. However, terahertz communications and UM-MIMO systems are the primary research points and confront many challenges for practical implementation. They require many RF chains and create problems in terms of cost and hardware complexity which RIS can simplify hardware and reduce cost. Therefore, we will present different modeling of wireless communication systems based on RIS for different phase information. Simulation results obtained by examining SNR performance and the error probability that shows the improvement of the received signal quality. According to results, RIS-based wireless communications can become an optimized model for future wireless communication systems. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) technology is widely used in integrated radar and communication systems (IRCSs). Moreover, index modulation (IM) is a reliable OFDM transmission scheme in the field of communication, which transmits information by arranging several distinguishable constellations. In this paper, we propose a sparse reconstruction-based joint signal processing scheme for integrated MIMO-OFDM-IM systems. Combining the advantages of MIMO and OFDM-IM technologies, the integrated MIMO-OFDM-IM signal design is realized through the reasonable allocation of bits and subcarriers, resulting in better intercarrier interference (ICI) resistance and a higher transmission efficiency. Taking advantage of the sparseness of OFDM-IM, an improved target parameter estimation method based on sparse signal reconstruction is explored to eliminate the influence of empty subcarriers on the matched filtering at the receiver side. In addition, an improved sequential Monte Carlo signal detection method is introduced to realize the efficient detection of communication signals. The simulation results show that the proposed integrated system is 5 dB lower in the peak sidelobe ratio (PSLR) and 1.5 × 10 5 lower in the number of complex multiplications than the latest MIMO-OFDM system and can achieve almost the same parameter estimation performance. With the same spectral efficiency, it has a lower bit error rate (BER) than existing methods. [ABSTRACT FROM AUTHOR]

This paper presents the design of a performance-improved 4-port multiple-input–multiple-output (MIMO) antenna proposed for millimeter-wave applications, especially for short-range communication systems. The antenna exhibits compact size, simplified geometry, and low profile along with wide bandwidth, high gain, low coupling, and a low Envelope Correlation Coefficient (ECC). Initially, a single-element antenna was designed by the integration of rectangular and circular patch antennas with slots. The antenna is superimposed on a Roger RT/Duroid 6002 with total dimensions of 17 × 12 × 1.52 mm3. Afterward, a MIMO configuration is formed along with a novel decoupling structure comprising a parasitic patch and a Defected Ground Structure (DGS). The parasitic patch is made up of strip lines with a rectangular box in the center, which is filled with circular rings. On the other side, the DGS is made by a combination of etched slots, resulting in separate ground areas behind each MIMO element. The proposed structure not only reduces coupling from −17.25 to −44 dB but also improves gain from 9.25 to 11.9 dBi while improving the bandwidth from 26.5–30.5 GHz to 25.5–30.5 GHz. Moreover, the MIMO antenna offers good performance while offering strong MIMO performance parameters, including ECC, diversity gain (DG), channel capacity loss (CCL), and mean effective gain (MEG). Furthermore, a state-of-the-art comparison is provided that results in the overperforming results of the proposed antenna system as compared to already published work. The antenna prototype is also fabricated and tested to verify software-generated results obtained from the electromagnetic (EM) tool HFSS. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of coplanar waveguide (CPW) structures loaded with symmetric circular and polygonal split-ring resonators (SRRs) for microwave and RF applications, leveraging their unique electromagnetic properties. These properties make them suitable for metamaterials, sensors, filters, resonators, antennas, and communication systems. The objectives of this study are to analyze the impact of different SRR shapes on the transmission characteristics of CPWs and to explore their potential for realizing compact and efficient microwave components. The CPW-SRR structures are fabricated on a dielectric substrate, and their transmission properties and spectrogram are experimentally characterized in the frequency range of 4 GHz to 10 GHz with the rotation angles of the SRR gap. The simulation results demonstrate that the resonant frequencies and magnitude of the transmission coefficient of the CPW-SRR structures are influenced by the geometry of the SRR shapes and the rotation angles of the SRR gap, with certain shapes exhibiting enhanced performance characteristics compared to others. Moreover, the symmetric circular and polygonal SRRs offer design flexibility and enable the realization of miniaturized microwave components with improved performance metrics. Overall, this study provides valuable insights into the design and optimization of CPW-based microwave circuits utilizing symmetric SRR shapes, paving the way for advancements in the miniaturization and integration of RF systems. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of the Internet of Vehicles, virtual reality, automatic driving and the industrial Internet, the terminal devices in the network show explosive growth. As a result, more and more information is generated from the edge of the network, which makes the data throughput increase dramatically in the mobile communication network. As the key technology of the fifth-generation mobile communication network, mobile edge caching technology which caches popular data to the edge server deployed at the edge of the network avoids the data transmission delay of the backhaul link and the occurrence of network congestion. With the growing scale of the network, distributing hot data from cloud servers to edge servers will generate huge energy consumption. To realize the green and sustainable development of the communication industry and reduce the energy consumption of distribution of data that needs to be cached in edge servers, we make the first attempt to propose and solve the problem of edge caching data distribution with minimum energy consumption (ECDDMEC) in this paper. First, we model and formulate the problem as a constrained optimization problem and then prove its NP-hardness. Subsequently, we design a greedy algorithm with computational complexity of O (n 2) to solve the problem approximately. Experimental results show that compared with the distribution strategy of each edge server directly requesting data from the cloud server, the strategy obtained by the algorithm can significantly reduce the energy consumption of data distribution. [ABSTRACT FROM AUTHOR]

Packaging solutions have recently evolved to become smart and intelligent thanks to technologies such as RFID tracking and communication systems, but the integration of sensing functionality in these systems is still under active development. In this paper, chipless RFID humidity sensors suitable for smart packaging are proposed together with a novel strategy to tune their performances and their operating range. The sensors are flexible, fast, low-cost and easy to fabricate and can be read wirelessly. The sensitivity and the humidity range where they can be used are adjustable by changing one of the sensor's structural parameters. Moreover, these sensors are proposed as double parameter sensors, using both the frequency shift and the intensity variation of the resonance peak for the measure of the relative humidity. The results show that the sensitivity can vary remarkably among the sensors proposed, together with the operative range. The sensor suitability in two specific smart packaging applications is discussed. In the first case, a threshold sensor in the low-humidity range for package integrity verification is analyzed, and in the second case, a more complex measurement of humidity in non-hermetic packages is investigated. The discussion shows that the sensor configuration can easily be adapted to the different application needs. [ABSTRACT FROM AUTHOR]

Orthogonal chirp division multiplexing (OCDM) offers a promising modulation technology for shallow water underwater acoustic (UWA) communication systems due to multipath fading resistance and Doppler resistance. To handle the various channel distortions and interferences, obtaining accurate channel state information is vital for robust and efficient shallow water UWA communication. In recent years, deep learning has attracted widespread attention in the communication field, providing a new way to improve the performance of physical layer communication systems. In this paper, the pilot-based channel estimation is transformed into a matrix completion problem, which is mathematically equivalent to the image super-resolution problem arising in the field of image processing. Simulation results show that the deep learning-based method can improve the channel distortion, outperforming the equalization performed by traditional estimator, the performance of Bit Error Rate is improved by 2.5 dB compared to the MMSE method in OCDM system. At the 7.5 to 20 dB region, it achieves better bit error rate performance than OFDM systems, and the bit error rate is reduced by approximately 53% compared to OFDM when the SNR value is 20, which is very useful in shallow water UWA channels with multipath extension and severe time-varying characteristics. [ABSTRACT FROM AUTHOR]

The article presents the discussion on fast evolution of computer and networking technologies. Topics include distributed data storage facilities which are being increasingly implemented using replicated, tamper-proof blockchain ledgers; and plethora of existing security- and privacy-related constraints on the networks are exacerbated, rather than solved, by blockchain technology.

The article presents the discussion on considerable aspects of face-to-face human interactions remain difficult to relay. Topics include computer's ability capturing a human's emotion called affective sensing, alternatively called emotion sensing and more recently emotional artificial intelligence (emotional AI); and use of emotions in crowd and traffic management; to relaying emotions to and from the metaverse.

The article presents the discussion on sustainable urban development as populations rise and cities draw ever-larger populations. Topics include industrial Internet and Internet of Vehicles, smart energy systems, building management systems, cyber security; and presenting the technological advancement and challenges of smart cities and smart villages from the system design and implementation point of view.

The article presents the discussion on study on integrating AI/ML into 5G with MIMO. Topics include MIMO being one of the key technical enablers for 5G in 3GPP in accommodating use cases and services such as evolved mobile broadband (eMBB), ultra-reliability low latency communications (URLLC); and Serving XR services being extremely demanding due to high throughput and low latency needs.

Fuzzy graphs are very important when we are trying to understand and study complex systems with uncertain and not exact information. Among different types of fuzzy graphs, cubic fuzzy graphs are special due to their ability to represent the membership degree of both vertices and edges using intervals and fuzzy numbers, respectively. To figure out how things are connected in cubic fuzzy graphs, we need to know about cubic α−strong, cubic β−strong and cubic δ−weak edges. These concepts better help in making decisions, solving problems and analyzing things like transportation, social networks and communication systems. The applicability of connectivity and comprehension of cubic fuzzy graphs have urged us to discuss connectivity in the domain of cubic fuzzy graphs. In this paper, the terms partial cubic α−strong and partial cubic δ−weak edges are introduced for cubic fuzzy graphs. The bounds and exact expression of connectivity index for several cubic fuzzy graphs are estimated. The average connectivity index for cubic fuzzy graphs is also defined and some results pertaining to these concepts are proved in this paper. The results demonstrate that removing some vertices or edges may cause a change in the value of connectivity index or average connectivity index, but the change will not necessarily be related to both values. This paper also defines the concepts of partial cubic connectivity enhancing node and partial cubic connectivity reducing node and some related results are proved. Furthermore, the concepts of cubic α−strong, cubic β− strong, cubic δ−weak edge, partial cubic α−strong and partial cubic δ−weak edges are utilized to identify areas most affected by a tsunami resulting from an earthquake. Finally, the research findings are compared with the existing methods to demonstrate their suitability and creativity. [ABSTRACT FROM AUTHOR]

This research paper presents a circuit-based phase noise model of a cross-coupled LC tank oscillator. The effect of the Oscillator's noise is one of the most critical items in designing modern RF communication systems. The noise factor necessitates a more thorough comprehension of design tradeoffs in RF VCO IC implementations. This research paper introduces a new analytical derivation to produce a well-bounded third-order polynomial equation accurately representing the LC oscillator's phase noise behaviour. The third-order polynomial equation includes circuit parameters such as capacitance, inductance and quality factors to understand the phase noise characteristics. The proposed method determines the amplitude and phase noise and forms a link with the circuit operating point, and phase noise is produced as a direct result of the circuit parameters. The advantage of the proposed resulting equation is that it avoids the need for complex simulations to identify the noise characteristics in such a process. The proposed equation was validated by comparing the tank circuit simulation results. The simulation results verify the applicability of the third-order polynomial equation representing the noise characteristics of the LC oscillator. [ABSTRACT FROM AUTHOR]

In this paper, the adaptive consensus problem of unknown non-linear multi-agent systems (MAs) with communication noises under Markov switching topologies is studied. Based on the adaptive control theory, a novel distributed control protocol for non-linear multi-agent systems is designed. It consists of the local interfered relative information and the estimation of the unknown dynamic. The Radial Basis Function networks (RBFNNs) approximate the nonlinear dynamic, and the estimated weight matrix is updated by utilizing the measurable state information. Then, using the stochastic Lyapunov analysis method, conditions for attaining consensus are derived on the consensus gain and the weight of RBFNNs. The main findings of this paper are as follows: the consensus control of multi-agent systems under more complicated and practical circumstances, including unknown nonlinear dynamic, Markov switching topologies and communication noises, is discussed; the nonlinear dynamic is approximated based on the RBFNNs and the local interfered relative information; the consensus gain k must to be small to guarantee the consensus performance; and the proposed algorithm is validated by the numerical simulations finally. [ABSTRACT FROM AUTHOR]

Wireless communication is growing day by day to satisfy the need for voice and high data speed from the industry and users. To meet this demand we are upgrading communication system to 5G networks. This new technology has raised the demand of high data rate with voice and Quality of service (QoS) of signal parameters. These all also leads to the requirement of energy requirements. This high requirements also creates many issues related to human health and environment congestions. This paper is addressing the issue and challenges related to energy consumption, challenges in the development of low energy network, green energy concept in every parameter of 5G communication. We need to make a way to maintain demand and supply ration with green energy in all aspects. Here in this paper survey is done for the energy and resource relevant parameter and techniques for various domain like spectrum allocation and sharing, network density at different level, antenna designs, Internet of things (IoT) future applications, cell traffic, hardware solutions, resource allocations, energy harvesting and transfer, deployment and planning. In this paper, we address the effect of high energy requirement in upcoming 5G technology, the effect of high energy and power on the environment, green energy solution on different parameters and designs. [ABSTRACT FROM AUTHOR]

Because of the increased mobility of vehicle users, it might be difficult to keep communication services in vehicle networks effective and dependable. Huge hurdles have been presented to vehicular networks as a result of the meteoric rise in the amount of data, which comes with the needs of high dependability and low latency. The deployment of access point servers at geographic locations that are closer to the vehicles in order to provide real-time service to applications that are based on the vehicles is one possible option. However, there is a limited amount of cache store space, and there is also a lack of a tractable access mode allocation method. As a result of these factors, it is very difficult to strike a compromise between the network transmission performance and fronthaul savings. Because the signal-to-interference-ratio (SIR) can be enhanced with switching mode in vehicular infrastructure, it may be possible to achieve higher levels of dependability. To serve all of the vehicles, the conventional allocation in vehicular network may not be sufficient on its own for two reasons: (1) the number of vehicles exceeds the number of paths, and (2) a vehicle may be located outside of the coverage path. Therefore, the implementation of switching mode allocation in vehicular communication is very necessary in order to increase the number of vehicles that can be supplied. In this paper, allocation using V2I, V2V, and V2X modes have been analyzed to provide dependable coverage for vehicles. These methods are used for communicating with other vehicles. In this paper, the numerical analysis has been performed such that SIR is optimized. In switching mode allocation, it has been shown that establishing a variable SIR threshold is helpful in achieving a path coverage that can be relied upon. It has been shown beyond a reasonable doubt that the coverage probability is likewise directly dependent on SIR thresholds. The theoretical analysis is verified, and it is confirmed that the suggested method is capable of achieving significant performance improvement in terms of coverage probability and data rate. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT), which is built on software-defined networking (SDN), employs a paradigm known as channel reassignment. This paradigm has great potential for enhancing the communication capabilities of the network. The traffic loads may be scheduled more effectively with the help of an SDN controller, which allows for the transaction of matching channels via a single connection. The present techniques of channel reassignment, on the other hand, are plagued by problems with optimisation and cooperative multi-channel reassignment, which affect both traffic and routers. In this paper, we provide a framework for SDN–IoT in the cloud that permits multi-channel reassignment and traffic management simultaneously. The multi-channel reassignment based on traffic management is optimised via the use of a deep reinforcement learning technique, which was developed in this paper. We do an analysis of the performance metrics in order to optimise the throughput while simultaneously reducing the rate of packet loss and the amount of delay in the process. This is achieved by distributing the required traffic loads over the linked channels that make up a single connection. [ABSTRACT FROM AUTHOR]