Статьи журнала - International Journal of Wireless and Microwave Technologies

Все статьи: 622

A Three-Level Model for Detecting and Identifying Aviation Objects using Deep Learning

A Three-Level Model for Detecting and Identifying Aviation Objects using Deep Learning

Olga Leshchenko, Yuriy Kravchenko, Oksana Herasymenko, Nataliia Dakhno, Оlexandr Makhovych, Serhii Stavytskyi, Denisa Macekova

Статья научная

This paper presents an intelligent software solution for object identification in images using deep learning models, designed for automated interpretation of monitoring results of aviation objects and infrastructure. The proposed approach addresses the growing demand for enhanced flight safety and improved efficiency of aviation operations. To meet this demand, a three-level model is proposed: Level 1 performs object detection, Level 2 provides optical character recognition (OCR) and text normalization, and Level 3 implements fuzzy matching with an object database. Based on comparative testing of detection models, YOLOv8n was selected as the core of the three-level architecture, providing an optimal balance between real-time processing speed and detection accuracy. A detailed analysis of model architectures revealed specific advantages and limitations in identifying monitoring results from image data. Training on a specialized dataset and subsequent testing confirmed the high efficiency of the proposed solution and its ability to reliably localize objects even under challenging visual conditions such as shadows, glare, and partial occlusion. The obtained results demonstrate the significant potential of the proposed intelligent solution for extending computer vision capabilities in the monitoring of aviation objects and infrastructure. The experimental results also confirm the effectiveness of the OCR and fuzzy matching modules in improving object identification accuracy under real-world conditions.

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A Three-Party Password Authenticated Key Exchange Protocol with Key Confirmation

A Three-Party Password Authenticated Key Exchange Protocol with Key Confirmation

Gang Yao

Статья научная

Three-party authenticated key exchange protocol is an important cryptographic technique in the secure communication areas, by which any two clients can verify the ability to use a server to establish communication. Recently, researchers have begun proposing new key exchange protocols that would not require the use of server public keys, but a human-memorable password. In this paper, we propose a new three-party password authenticated key exchange protocol with key confirmation. The security of our proposed protocol relies on the hardness of the bilinear Diffie-Hellman problem and Diffie-Hellman problem in the random oracle model, and the proposed protocol achieves the security attributes: dictionary attack resilience, known session key security, perfect forward secrecy, no key compromise impersonation, no unknown key share and no key control.

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A Trust Evaluation Model for Industrial Control Ethernet Network

A Trust Evaluation Model for Industrial Control Ethernet Network

ZHOU Sen-xin, HAN Jiang-hong, TANG Hao

Статья научная

Industrial control ethernet networks are more impotant in connecting with equipments each other of enterprise comprehensive automation and integrating information. With the explosive growth of network techniques, the traditional control networks can no longer satisfy the security demands on network connectivity, data storage and information exchanges.New types of networks emerged in recent years in order to provide solutions for the increasing requirements on networked services. We propose a trust evaluation model for industrial control ethernet network . Our study shows the importance and necessity of applying theoretical analyses to understand the complex characteristics of trusted industrial control ethernet networks.

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A Trust-based Security Approach in Hierarchical Wireless Sensor Networks

A Trust-based Security Approach in Hierarchical Wireless Sensor Networks

Mohsen Salehi, Jamal Karimian

Статья научная

In recent decades Significant expansion and popularity of wireless sensor networks in various applications have attracted the attention of many researchers. The main challenges of WSN for the researchers are Energy and security restrictions. Recently trust as a new, efficient and soft method has been able to provide satisfactory security in WSN. In this study by using a simple method, first each node calculates the trust values of neighbors and according to these values exchanges data with neighbor nodes, then from each cluster, a node whose trust is greater than a threshold value can be candidate for being cluster head. Finally by using fuzzy logic a node with the most trusted neighbors and desirable energy level among the candidate nodes is selected as a cluster head. Simulation results show that proposed system has been able to greatly improve security and prevent untrusted and malicious nodes from becoming the cluster head.

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A Weighed Least Square TDOA Location Algorithm for TDMA Multi-target

A Weighed Least Square TDOA Location Algorithm for TDMA Multi-target

WANG XU, HE ZI-SHU

Статья научная

In order to improve the location precision of multiple targets in a time division multiple address (TDMA) system, a new weighed least square algorithm is presented for multi-target ranging and locating. According to the time synchronization of the TDMA system, the range difference model between multiple targets is built using the time relations among the slot signals. Thus, the range of one target can be estimated by the other one's, and a group of estimated value can be acquired for every target. Then, the weighed least square algorithm is used to estimate the range of every target. Due to the time differences of arrival (TDOA) of all targets are used in one target's location, the location precision is improved. The ambiguity and non-solution problems in the traditional TDOA location algorithm are avoided also in the presented algorithm. At the end, the simulation results illustrate the validity of the proposed algorithm.

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A Wireless Solution to Collecting and Displaying Oil Temperature Data Based on Zigbee Network

A Wireless Solution to Collecting and Displaying Oil Temperature Data Based on Zigbee Network

Cui Jingcong, Chen Lidong, Li Xunming, Huang Chunhai

Статья научная

In some oil fields of China, monitoring oil temperature during producing almost relies on manual operation. According to this, we designed a solution based on Zigbee network and sensor technology. In our design of sampling nodes, with JN5139 module as the core, uses sensor PT100 to collect temperature data and LCD module LCM141C-01 to display the final result. The whole solution has an advantage of a simple structure, low power consumption etc, therefore, it has a positive meaning in improving monitoring work efficiency in oil fields.

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A double auction scheme based on secret sharing and safe comparing protocol

A double auction scheme based on secret sharing and safe comparing protocol

Bin Zhang, Qiuliang Xu, Han Jiang

Статья научная

At present most practical electrical auction schemes that based on secret sharing, group signature and hash chain assume the existence of a trusted thid party, while the schemes that based on commitment, zero knowledge or homomorphic encryption without the TTP model face the problem of high cost of communication and computation. The double auction scheme proposed by Bogetoft is based on secure multiparty computation without a TTP and get very high efficiency. In this article, we improve the above scheme. Based on secret sharing and constant round safe comparing protocol, we reduce the requirement of honest majority in the original scheme. We improve the security of the scheme while maintain the high efficiency.

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A hybrid cryptosystem to enhance security in IoT health care system

A hybrid cryptosystem to enhance security in IoT health care system

Kavitha.S., P.J.A.Alphonse

Статья научная

Internet of Things (IoT) based health care system provides an essential interface between tiny devices and customers, who require customary checking by remedial focus. The technological innovation is important to guarantee the data protection and security among customer and devices, though it is vulnerable by various security assaults. The cryptographic technique is a prominent method for data protection in a healthcare management system. Single cryptographic algorithm based solution suffered to provide efficient security as its high probability of attacks. So this paper proposes a hybrid cryptographic algorithm that secures the sensitive medicinal information in IoT health care system. The proposed hybrid algorithm is dealing with various security attacks in a proficient way, and also increases its performance when compared to other cryptographic algorithms.

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A modified semi-supervised color image segmentation method

A modified semi-supervised color image segmentation method

Wei Hongru, Chai Fangyong

Статья научная

The paper proposed a modified color image segmentation method basing on semi-supervised hidden Markov random fields (HMRF) with constraints. Making use of MeanShift algorithm to get supervision information and, cluster number and initial values for cluster centroids, color images can be segmented effectively with the method in this paper by K-Means algorithm. The experimental results are very encouraging.

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A novel energy efficient cluster head selection method for wireless sensor networks

A novel energy efficient cluster head selection method for wireless sensor networks

Jasvir Kaur, Sukhchandan Randhawa, Sushma Jain

Статья научная

Wireless Sensor Networks are becoming a worldwide sensational topic with recent advances in wireless communications and digital electronics. It serves as the backbone for controlling real-life applications. It consists of group of sensor nodes that sense the information from an event area and passes it to the base station which reacts according to the environment. There are number of cluster based routing protocols, in which a region is divided into number of clusters and within each cluster, a cluster head is elected based on some parameter. So, a novel selection method for the cluster head having efficiency in energy is based on Flower Pollination Algorithm (FPA) is proposed in this paper. The performance of our proposed scheme is being analyzed and is compared with the already existing protocols like LEACH, C-LEACH and K-Means in terms of energy efficiency, number of alive nodes, packet drop ratio and energy dissipation etc

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A power-based method for improving the ODMRP protocol performance in mobile ad-hoc networks

A power-based method for improving the ODMRP protocol performance in mobile ad-hoc networks

Arash.Ghafouri, Ahmad Ghasemi, Mohammad Reza. Hasani Ahangar

Статья научная

Mobile AD hoc Networks as a special type of wireless networks have received special attention due to having special features such as no need for central management, no need for infrastructure and high mobility capability and can be used in cases where creating an effective communication infrastructure is not cost-effective or is practically impossible, such as conferences, such as battles and communications after natural disasters. Several routing protocols are proposed for these networks. ODMRP protocol is one of the most famous and used protocols in Mobile AD hoc networks. This study was carried out aimed to discuss this routing protocol and then provide a new routing method for this protocol for increasing its efficiency. In the ODMRP protocol, the optimal route is selected based on the shortest route. In wireless communications and getting the nodes away from each other, the received signal levels are weakened and may result in loss of data, and in practice, the shortest path that works based on the number of hops loses its effectiveness. In the proposed protocol, the route is selected based on the received signal strength level. According to the simulation results, the performance of the proposed protocol increases by decreasing control overhead and increasing the packet delivery rate compared to the original protocol.

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A proof of work: securing majority-attack in blockchain using machine learning and algorithmic game theory

A proof of work: securing majority-attack in blockchain using machine learning and algorithmic game theory

Somdip Dey

Статья научная

Blockchain’s vast applications in different industries have drawn several researchers to pursue extensive research in securing blockchain technologies. In recent times we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority attack from taking place.

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A stable routing protocol based on DSR protocol for mobile ad hoc networks

A stable routing protocol based on DSR protocol for mobile ad hoc networks

Golsum Najafi, Sajjad Jahanbakhsh Gudakahriz

Статья научная

Mobile ad hoc network is a wireless non-centralized network. This network includes a set of distributed nodes with any base or central management, develop a temporary network. Such a way, routing is of the basic challenges of these kinds of networks. Till now, various protocols have been provided for routing in these kinds of networks. One of the optimum routing techniques in these networks is stable routing. In the stable routing, the target is to use paths for send and receive that probably have a higher life period. This causes the data to be sent from a more confident path and the need to new routing will be less, due to liquidation of the current path. In this paper, the target is to provide a stable routing protocol with high efficiency for these kinds of networks, by improving the DSR routing protocol. In the provided protocol, beside the path stability, the energy of the path nodes and path length will be considered too, in order to discover a path with higher quality and use it. The provided protocol will be called as ST-DSR. The result of stimulation in the NS-2 environment shows that the ST-DSR has a better operation toward the base protocol, meaning DSR.

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A study on Need of Adaptation Layer in 6LoWPAN Protocol Stack

A study on Need of Adaptation Layer in 6LoWPAN Protocol Stack

Ruchi Garg, Sanjay Sharma

Статья научная

Emergence of wireless embedded applications is resulting in the communication among sensor nodes connected in a wireless personal area network. Sensor nodes gather the real time information and transmit it to the desired application. This requires transmission of IPv6 packets over Low-power wireless personal area network and is called 6LoWPAN. IPv6 is resource intensive protocol whereas 6LoWPAN is resource constraint due to small packet size, limited device memory, short transmission range, and less data rate of sensor nodes. Also these nodes in 6LoWPAN are mainly battery operated hence minimum power consumption is also a major constraint. To make the efficient transmission of information in such a resource constraint network, an adaptation layer was suggested and implemented by Internet Engineering Task Force (IETF). The placing of this additional layer is in between network layer and data link layer of TCP/IP protocol stack. This paper contributes in the detailed analysis of need of adaptation layer in 6LoWPAN protocol stack. The necessity of this additional layer is justified by explaining the major functions like header compression, fragmentation and reassembly of packets and packet routing handled by it.

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ACO Algorithm Applied to Multi-Objectives Optimization of Capacity Expansion in Next Generation Wireless Network

ACO Algorithm Applied to Multi-Objectives Optimization of Capacity Expansion in Next Generation Wireless Network

Dac-Nhuong Le, Son HongNgo, Vinh Trong Le

Статья научная

The optimal capacity expansion of base station subsystems in Next Generation Wireless Network (NGWN) problem with respect to multi-demand type and system capacity constraints is known to be NP-complete. In this paper, we propose a novel ant colony optimization algorithm to solve a network topology has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. There are two important aspects of upgrading to NGWN. The first importance of backward compatibility with pre-existing networks, and the second is the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. Our objective function is the sources to concentrators connectivity costas well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We evaluate the performance of our algorithm with a set of real world and data randomly generated. Numerical results show that our algorithms is a promising approach to solve this problem.

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AI-Driven Network Security: Innovations in Dynamic Threat Adaptation and Time Series Analysis for Proactive Cyber Defense

AI-Driven Network Security: Innovations in Dynamic Threat Adaptation and Time Series Analysis for Proactive Cyber Defense

Mansoor Farooq, Mubashir Hassan Khan

Статья научная

This research presents a pioneering investigation into the tangible outcomes of implementing an Artificial Intelligence (AI) driven network security strategy, with a specific emphasis on dynamic threat landscape adaptation and the integration of time series analysis algorithms. The study focuses on the innovative fusion of adaptive mechanisms to address the ever-evolving threat landscape, coupled with the application of the Autoregressive Integrated Moving Average (ARIMA) time series analysis algorithm. Real-world case studies are employed to provide concrete evidence of the efficacy of these strategies in fortifying network defenses and responding dynamically to cyber threats. Novelty is introduced through the unified integration of dynamic threat landscape adaptation mechanisms that continuously learn and evolve. The paper details adaptive access controls, showcasing how the security system dynamically adjusts permissions in real time to respond to emerging threats. Additionally, the application of the ARIMA time series analysis algorithm represents a pioneering contribution to the field of cybersecurity. By unveiling temporal patterns in security incidents, ARIMA adds a predictive element to network defense strategies, offering valuable insights into potential future threats and enabling a proactive response. The findings underscore the practical impact of the applied strategies, with real-world case studies demonstrating substantial improvements in threat detection rates, the effectiveness of adaptive responses, and the predictive capabilities facilitated by ARIMA. This research contributes to the advancement of AI in network security by providing tangible evidence of the innovative and effective nature of the integrated approach. The outcomes bridge the gap between theoretical concepts and practical applications, offering valuable insights for organizations seeking adaptive and predictive strategies to enhance their cybersecurity resilience in dynamic threat environments.

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Adaptation of Propagation Model Parameters toward Efficient Cellular Network Planning using Robust LAD Algorithm

Adaptation of Propagation Model Parameters toward Efficient Cellular Network Planning using Robust LAD Algorithm

Isabona Joseph, Divine O. Ojuh

Статья научная

All new mobile radio communication systems undergo a cautious cellular network planning and re-planning process in order to resourcefully utilize the allotted frequency band and also ensure that the geographical area of focus is adequately fortified with integrated base stations transmitters. To this end, efficient radio propagation model prediction and tuning is of huge importance, as it assists radio network engineers to effectively assess and plan the cellular network signal coverage area. In this research work, an adaptive least absolute deviation approach is proposed and verified to fine-tune the parameters of Ericsson propagation model. The adaptive tuning technique have been verified experimentally with field propagation loss data acquired over three different suburban locations of a recently deployed LTE radio cellular network in Waterlines area of Port Harcourt City. In terms of the mean absolute percentage error and coefficient of efficiency, the outcomes of the proposed adaptive tuning approach show a higher degree of prediction performance accuracy on the measured loss data compared to the commonly applied least squares regression tuning technique.

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Adaptive Beamforming of Linear Array Antenna System Using Particle Swarm Optimization and Genetic Algorithm

Adaptive Beamforming of Linear Array Antenna System Using Particle Swarm Optimization and Genetic Algorithm

Akila Nipo, Rubayed All Islam, Md. Imdadul Islam

Статья научная

One of the key aspects of 5G networks is the implementation of massive MIMO (Multiple Input Multiple Output) technology combined with adaptive beamforming. This study explores the use of a linear array antenna to manage and reduce unwanted signals such as jamming, interference, and noise, while also boosting the signal strength towards the intended user or device. The main challenge lay in optimizing the weights of the antenna elements, which was tackled by employing adaptive algorithms like LCMV (Linearly Constrained Minimum Variance) and RLS (Recursive Least Squares). To simplify the optimization process, two soft computing techniques—Particle Swarm Optimization (PSO) and Genetic Algorithm (GA)—were utilized. The performance of the beamforming weights and radiation patterns was assessed in terms of minimizing unwanted signals and maximizing the desired signal. To check how well the proposed methods work, some commonly used algorithms like MVDR (Minimum Variance Distortionless Response) and LCMV are also applied. The outcomes were compared to those from other algorithms. A Differential Beamforming method is applied to examine how effectively the system can focus the signal in the target direction while minimizing unwanted interference from other directions. Additionally, the fminsearch algorithm, which is a basic local search method, is used to compare how well it can adjust the beamforming weights compared to the more advanced global optimization techniques. The results indicate that PSO and GA produce highly similar performance levels.

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Adaptive Cell Pride Traffic Load Balancing for Reliable 5G Mmwave Handovers

Adaptive Cell Pride Traffic Load Balancing for Reliable 5G Mmwave Handovers

Emmanuel O. Isatayo, Samuel I. Olotu, Mary T. Kinga

Статья научная

Handover (HO) management in millimeter-wave (mmWave) fifth-generation (5G) networks faces critical challenges including limited propagation distance, blockage, and frequent disconnections, particularly in dense urban environments. Most existing solutions target high mobility scenarios, while dense urban traffic with low-speed heterogeneous environments and frequent stop-and-go scenarios remains under-explored. This study proposes a novel concept of cell pride where the neighbouring cells cooperate and select the best performing cell for each user equipment (UE) instead of competing with each other. Based on this idea, the Adaptive Cell Pride Traffic Load Balancing (ACPT-LB) framework is developed to enhance the reliability of handover and connection stability in 5G mmWave networks by combining cooperative cell selection, adaptive load balancing, and a neighbour discovery mechanism. The simulated results showed Handover Success Rate (HSR) of 100%, Ping-Pong Avoidance Rate (PPAR) of 100%, and Connection Stability (CS) of more than 88% for all simulations with UE densities ranging from 1000 to 5000, highlighting the effectiveness of the framework in low mobility and high-density urban environments. These results confirm that ACPT-LB offers a scalable and robust solution for mobility and traffic management in 5G and Beyond 5G networks.

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Adaptive Cross-layer Resource Allocation by HNN in OFDM-MISO System

Adaptive Cross-layer Resource Allocation by HNN in OFDM-MISO System

Mingyan Jiang, Yulong Liu

Статья научная

This paper presents an adaptive cross-layer resource allocation problem with the fairness in multi-user OFDM-MISO communication systems, and provides two solutions with Hopfield Neural Network (HNN) and Genetic Algorithm (GA) for the problem. We utilized HNN’s characteristics such as parallel processing, fast convergence speed and easy convergence to the optimum, to solve this problem under the conditions of proportional fairness for satisfying system performances and users’ requirements. The method is simplified in the computation by dividing the bit-loading matrix into three matrixes. The simulation results show that HNN and GA can effectively solve optimization problems of resource allocation in such system, and results of selected HNN and GA methods are more effective than that of the traditional method.

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