Communication In Wireless Networks Research Articles

Covert Communication in a Multirelay-Assisted Wireless Network With an Active Warden

Covert Communication in a Multirelay-Assisted Wireless Network With an Active Warden

Multiband Antenna Design with Integrated AMC Surface and FSS Superstrate for Wireless Body Area Network Communications

Multiband Antenna Design with Integrated AMC Surface and FSS Superstrate for Wireless Body Area Network Communications

Warehouse Management Information System Technology Review

With the rapid development of information technology, warehouse management information systems are playing an increasingly important role in modern logistics management. This paper first elaborates on the importance of warehouse management information systems and the impact of technological development on warehouse management, and then reviews the development process of warehouse management information systems. Next, it focuses on introducing the application of key technologies such as barcode technology, RFID technology, UWB high-precision positioning technology, wireless network communication technology, cloud computing technology, and big data analysis technology in warehouse management. In addition, this paper also analyzes the current problems faced by warehouse management information systems and discusses the application prospects of emerging technologies such as artificial intelligence, Internet of Things, blockchain, automation, and robotics in warehouse management. Finally, it summarizes the main findings of the review and proposes insights and suggestions for the development of warehouse management information systems and future research directions.

Intelligent multi-agent model for energy-efficient communication in wireless sensor networks

The research addresses energy consumption, latency, and network reliability challenges in wireless sensor network communication, especially in military security applications. A multi-agent context-aware model employing the belief-desire-intention (BDI) reasoning mechanism is proposed. This model utilizes a semantic knowledge-based intelligent reasoning network to monitor suspicious activities within a prohibited zone, generating alerts. Additionally, a BDI intelligent multi-level data transmission routing algorithm is proposed to optimize energy consumption constraints and enhance energy-awareness among nodes. The energy optimization analysis involves the Energy Percent Dataset, showcasing the efficiency of four wireless sensor network techniques (E-FEERP, GTEB, HHO-UCRA, EEIMWSN) in maintaining high energy levels. E-FEERP consistently exhibits superior energy efficiency (93 to 98%), emphasizing its effectiveness. The Energy Consumption Dataset provides insights into the joule measurements of energy consumption for each technique, highlighting their diverse energy efficiency characteristics. Latency measurements are presented for four techniques within a fixed transmission range of 5000 m. E-FEERP demonstrates latency ranging from 3.0 to 4.0 s, while multi-hop latency values range from 2.7 to 2.9 s. These values provide valuable insights into the performance characteristics of each technique under specified conditions. The Packet Delivery Ratio (PDR) dataset reveals the consistent performance of the techniques in maintaining successful packet delivery within the specified transmission range. E-FEERP achieves PDR values between 89.5 and 92.3%, demonstrating its reliability. The Packet Received Data further illustrates the efficiency of each technique in receiving transmitted packets. Moreover the network lifetime results show E-FEERP consistently improving from 2550 s to round 925. GTEB and HHO-UCRA exhibit fluctuations around 3100 and 3600 s, indicating variable performance. In contrast, EEIMWSN consistently improves from round 1250 to 4500 s.

Efficient machine learning‐based hybrid resource allocation for device‐to‐device underlay communication in 5G wireless networks

SummaryDevices in close proximity can directly communicate with each other through device‐to‐device (D2D) communication, bypassing the need for base stations. To minimize the delay for D2D active clients, we use a sequential approach to reuse cellular‐type resources. Unlike conventional methods that focus solely on uplink or downlink resource distribution, our study introduces a novel optimization technique to maximize network throughput. Our proposal incorporates a hybrid approach that combines both downlink and uplink techniques for resource allocation. We utilize random forest and game theory algorithms to ensure smooth D2D communication while reducing interference between cellular and D2D pairings. Our hybrid structure effectively addresses challenges arising from intra‐ and inter‐cell interferences resulting from spectrum reusability and deployment. This approach also improves power control and quality of service. Traditionally, NP‐hard optimization solutions are proposed for mixed‐integer nonlinear problems. In our study, the critical stages include channel assignment and energy allocation. The objective problem in resource allocation considers parameters such as the transmission power of D2D active clients, cellular users, connection distance, base stations, and quality of service constraints. Our proposed hybrid method aims to enhance overall spectrum efficiency and network throughput. Simulated results demonstrate the superiority of our modified hybrid technique compared to existing joint resource allocation methods. This comprehensive approach represents a significant advancement in addressing the complexities associated with D2D communication, offering improved efficiency and performance in contemporary network environments.

User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning.

In this paper, the issue of detecting a user's position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for the binary classification of user orientation, neural networks achieved accuracy that was more than 9% higher than that for the well-known threshold method. In addition, the classification of user position angles relative to the reference node was analyzed. It was proven that, using the proposed deep learning approach and the channel impulse response, it was possible to estimate the angle of the user's position in relation to the antenna geometry. Absolute user orientation angle errors of about 4-7° for convolutional neural networks and of about 14-15° for multilayer perceptrons were achieved in approximately 85% of the cases in both tested scenarios.

Dynamic trusted cross-layer IDS for secured communications in wireless networks using routing algorithm and FT-CNN

Recently, security has been necessary in this computer world due to the fast development of technology and enormous user strength. The different kinds of security mechanisms including the Intrusion Detection System (IDS) were developed by many researchers to confirm the security of the data in the communication process. In general, the IDS are used to detect anomalous nodes, and attacks and increase the security level. Even though, the various disadvantages are available to ensure the data reliability on different kinds of applications. For this purpose, this work proposes a cross-layer IDS that is a combination of the trust-based secure routing method, attribute selection and classification algorithms. This study introduces a novel attribute selection approach known as the Weighted Genetic Feature Selection Algorithm (WGFSA). This method is designed to identify and prioritize valuable attributes within the context of network, physical, and data link layers. And introduce a deep classifier called the Hyperparameter-Tuned Fuzzy Temporal Convolutional Neural Network (HFT-CNN) for efficient categorization. Additionally, we propose a pioneering secure routing algorithm known as the Fuzzy Logic and Time-Constrained Dynamic Trusted Cross-Layer-Based Secure Routing Algorithm (FCSRA) to ensure the secure transmission of data packets. The effectiveness of the newly developed system is proved by conducting experiments with the network, standard Aegean Wi-Fi intrusion dataset (AWID) and proved superior to other systems in delay, energy consumption, packet delivery rate, and prediction accuracy.

Efficient key distribution for secure and energy-optimized communication in wireless sensor network using bioinspired algorithms

Wireless Sensor Networks (WSNs) play a major part in numerous applications such as smart agriculture, healthcare, and environmental monitoring. Safeguarding protected communication in this network is dominant. Securing data transmission in WSNs needs a strong key distribution device to defend against malicious attacks as well as illegal access. Traditional techniques like pre-shared or centralized key management are often unreasonable owing to resource limitations, particularly in large-scale sensor systems. To overcome this challenge, a lightweight key distribution technique is employed for safeguarding the security and privacy of data transmission streamlining processes decreasing computational overhead as well as energy consumption. By optimizing and simplifying key distribution devices, we propose to improve the complete efficacy and trustworthiness of WSNs that aid safe communication while preserving valuable energy resources. Therefore, this article designs an Efficient Key Distribution for Secure and Energy-Optimized Communication using Bioinspired Algorithms (EKD-SOCBA) for WSN. The purpose of the EKD-SOCBA technique is to accomplish security and energy efficiency in WSNs. Initially, the EKD-SOCBA technique applies a golden jackal optimization (GJO) based clustering approach to cluster the nodes and select cluster heads (CHs). Also, a lightweight Dynamic Step-wise Tiny Encryption Algorithm (DS-TEA) is applied to secure data transmission in the network. Finally, a lightweight key management phase is employed to protect the encryption key and decrease energy utilization and overhead costs. To exhibit the enhanced act of the EKD-SOCBA model, a comprehensive set of imitations was involved. Extensive results stated enhanced presentation of EKD-SOCBA methodology over other models on WSN.

Single-Photon Counting Receivers for Optical Wireless Communications in Future 6G Networks

Single-Photon Counting Receivers for Optical Wireless Communications in Future 6G Networks

Federated learning enables 6 G communication technology: Requirements, applications, and integrated with intelligence framework

The 5 G networks are effectively deployed worldwide, and academia and industries have begun looking at 6 G network communication technology for consumer electronics applications. 6 G will be built on pervasive artificial intelligence (AI) to enable data-driven Machine Learning (ML) applications in massively scalable and heterogeneous networks. Conventional ML technique involves centralizing train data in data centers where centralized ML algorithms can be employed for data inference and analysis. The data inference and analysis are frequently inconvenient or impracticable for the devices to submit information to the preset sever because of privacy concerns and inadequate communication capabilities in wireless networks. However, privacy limitations and restrictions in wireless network communication capacity are frequently impractical or undesirable for the devices to acquiesce data to the parameter server. Federated learning (FL) enables the devices to train a practical and standard model while needing data exchange and transfer, which might solve these issues. This paper presents an overview of FL, 6 G, and FL enables 6 G communication technology. In particular, 6 G requirements and applications, and the proposed FL framework algorithm with evaluation are described. Finally, FL-enabling 6 G communication technologies open challenges, and research directions are discussed to help future researchers improve the FL-enabled 6 G network.

Low-Power and Wireless Communication Research on Underground Displacement Three-Dimensional Monitoring System.

Underground displacement monitoring is a crucial means of preventing geological disasters. Compared to existing one-dimensional methods (measuring only horizontal or vertical displacement), the underground displacement three-dimensional measurement method and monitoring system proposed by the author's research team can more accurately reflect the internal movement of rock and soil mass, thereby improving the timeliness and accuracy of geological disaster prediction. To ensure the reliability and long-term operation of the underground displacement three-dimensional monitoring system, this article further introduces low-power design theory and Bluetooth wireless transmission technology into the system. By optimizing the power consumption of each sensing unit, the current during the sleep period of a single sensing unit is reduced to only 0.09 mA. Dynamic power management technology is employed to minimize power consumption during each detection cycle. By using Bluetooth wireless transmission technology, the original wired communication of the system is upgraded to a relay-type wireless network communication, effectively solving the problem of the entire sensing array's operation being affected when a single sensing unit is damaged. These optimized designs not only maintain monitoring accuracy (horizontal and vertical displacement errors not exceeding 1 mm) but also enable the monitoring system to operate stably for an extended period under harsh weather conditions.

Performance Analysis and Simulation of IRS-Aided Wireless Networks Communication

This paper introduces the novel IRS-based Optimal Relay Selection (ORS-IRS) method, aimed at analyzing the performance of wireless communication systems with an emphasis on symmetry. The ORS-IRS approach presents an innovative communication algorithm that seamlessly integrates Intelligent Reflecting Surfaces (IRS) with relay selection techniques. Through adaptive adjustments of reflection coefficients, IRS elements efficiently manipulate incoming signals, fostering symmetry in signal strength enhancement and latency reduction for improved signal delivery to the intended destination. This symmetrical optimization in channel capacity and transmission power ensures reliable data transmission with low latency, achieved through the seamless integration of IRS and relay selection techniques. In contrast, the Cell-Free Massive MIMO (CF-M-MIMO), with its decentralized architecture, excels in serving a larger user base and attaining remarkable capacity gains, showcasing a different dimension of symmetry. The Decode-and-Forward (DF) relaying approach demonstrates its potential in enhancing signal reliability across extended distances, contributing to the overall symmetry of the comparative analysis. This comprehensive evaluation provides valuable insights into selecting appropriate transmission strategies, particularly for applications that demand high capacity and reliability in the design of modern wireless communication systems with a symmetrical focus.

LoRaWAN-based hybrid internet of wearable things system implementation for smart healthcare

This study introduces the design and development of an Internet of Wearable Things-based Hybrid Healthcare Monitoring System (IoWT-HHMS) for smart medical applications. The system incorporates smart wearable sensing units for real-time, remote monitoring of vital health parameters such as Blood Pressure (BP), Heart Rate (HR), and Body Temperature (BT). A key innovation is the development of a hybrid wireless network communication mechanism within the IoWT-HHMS, utilising the FiPy microcontroller. This mechanism supports both short- and long-range connectivity and integrates an algorithm for efficient data acquisition and updating to the IoT platform. The IoWT-HHMS has undergone extensive testing and validation across various scenarios, including sensor functionality, performance of Wi-Fi and LoRaWAN networks, hybrid network connectivity, and accuracy assessment using the Datacake dashboard. The tests evaluated crucial aspects such as communication reliability, power consumption, and latency. The results demonstrate the system's high stability and accuracy in reading health parameters. Comparisons with reference devices reveal impressive accuracy levels for Systolic BP (SBP), Diastolic BP (DBP), HR, and BT, recording 96.37 %, 95.17 %, 97 %, and 98.57 % accuracy, respectively. Both Wi-Fi and LoRaWAN networks proved reliable in indoor and outdoor settings, maintaining data transmission over distances up to 1.5 km without data loss. In conclusion, the developed IoWT-HHMS shows great promise for efficient and effective real-time remote monitoring of patients' health conditions using an innovative hybrid wireless network communication mechanism.

Additively Manufactured Stress-strain Dependant Frequency Reconfigurable Antenna for Pressure Sensor Applications

A novel additive-manufactured antenna for stretchable sensor application is designed, simulated and measured. The fully transparent antenna has air as a substrate and a conductive aluminium metal sheet as a patch. The layers are defined with thin Thermo Poly Urethane (TPU) material, as its flexible/stretchable property doesn't disturb the actual property of air. The air substrate is locked within the flexible TPU with a thickness of 200 microns, and the conducting patch is also dimensioned with the 3D printing method. The stretchable antenna is fabricated with 3D printing technology, considered a dielectric medium, and the conducting medium is a conducting aluminium sheet. Re-configurability is achieved with the pressure level applied over the air–substrate antenna. Hence, the minimal change in shape changes the dielectric constant, thus changing the antenna parameter and radiation pattern. The antenna achieves improved size and performance with a gain of 7.2 dB, a directivity of 7.574 dB, a radiation efficiency of 95.67 %, and a 12:509 front-to-back ratio. The fabricated antenna is tested for its resonant characteristics and radiation properties. This reconfigurable antenna can be used for various applications, including Wireless Local Area Network (WLAN) communication.

Energy-efficient aware and predicting bandwidth estimation routing protocol for hybrid communication in wireless body area networks

Energy-efficient aware and predicting bandwidth estimation routing protocol for hybrid communication in wireless body area networks

Integrated Sensing, Localization, and Communication in Holographic MIMO-Enabled Wireless Network: A Deep Learning Approach

Integrated Sensing, Localization, and Communication in Holographic MIMO-Enabled Wireless Network: A Deep Learning Approach

Retracted: Design of English Mobile Learning Platform Based on GSM-R Wireless Network Communication System

Retracted: Design of English Mobile Learning Platform Based on GSM-R Wireless Network Communication System

Transient analysis of energy-saving strategy for cognitive radio networks using G-queue with heterogeneity

Energy efficiency, high data speeds, and effective spectrum utilization stand as the primary factors governing 5G and beyond networks. A base station (BS) in a cognitive radio network (CRN) that conserves energy during sleep periods is a promising contender for achieving more effective spectrum allocation. An efficient energy-saving strategy is offered in this study to achieve greener communication in wireless cellular networks. This study aims to propose and analyze an energy-saving scheme for the BS, taking into account the heterogeneity and reliability of networks. The entire system is modeled as a three-dimensional Markov chain by establishing a discrete-time preemptive priority queueing model with single vacation, heterogeneous packets, and negative packets such as viruses. Then, the transient analysis of the Markov chain is performed using the recursive method. Utilizing the transient probability distribution, we present numerical results derived from reliability analysis and queueing analysis to substantiate the validity of the proposed model. Furthermore, results based on the energy-saving degree are showcased to affirm the effectiveness of the proposed scheme. Finally, a reward cost function is obtained depending on the successful transmission of secondary packets, and the Quasi-Newton method is used to determine the optimal reward cost.

Wearable Full-Textile Spoof Surface Plasmon Polariton Transmission Line for Secured Communication in Wireless Body Area Network

Wearable Full-Textile Spoof Surface Plasmon Polariton Transmission Line for Secured Communication in Wireless Body Area Network

Blockchain based mobile communication data privacy protection algorithm for cellular networks

The rapid development of mobile communication technology not only brings great convenience to users, but also brings the risk of user data privacy leakage. Due to the broadcasting nature of mobile communication transmission, open wireless interfaces have become a security vulnerability for mobile devices such as mobile phones, which can be easily eavesdropped. This article studied a data privacy protection algorithm suitable for mobile communication in cellular networks based on the anonymous mechanism of blockchain. This article first analyzes the overall framework and anonymity technology of blockchain data from the perspective of privacy and queryability. Then, based on blockchain technology, consistency mechanisms, privacy control, and access rights management are designed. Finally, mobile communication data privacy protection algorithms are designed and implemented through data encryption and verification. The latency of transactions under different task volumes and throughput at different nodes were analyzed to verify the reliability of several anonymous mechanisms in cellular network mobile communication data privacy protection in blockchain. Based on the experimental results, it was concluded that the reliability range of CryptoNote and the zero coin and zero currency protocol mechanism in the specified nodes was between 92 and 99%. This article utilized blockchain technology to distribute mobile communication data in nodes and achieve decentralized data transmission, thus protecting the privacy of wireless network communication data. By analyzing the reliability of anonymous mechanisms based on blockchain in mobile communication nodes, it was concluded that this method had certain research value.