Previous Issue
Volume 5, March
 
 

Telecom, Volume 5, Issue 2 (June 2024) – 7 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Select all
Export citation of selected articles as:
16 pages, 9167 KiB  
Article
A Wide Bandwidth Vivaldi Antenna Suitable for 5G/6G Communication Utilizing a CMOS 0.18 μm Process
by Ming-An Chung, Chung-Wu Ting and Kuo-Chun Tseng
Telecom 2024, 5(2), 400-415; https://doi.org/10.3390/telecom5020020 - 14 May 2024
Viewed by 451
Abstract
This text proposes a Vivaldi structure array antenna, using a power divider structure. The composition includes an antenna array with four antennas, suitable for a wideband array structure antenna in the 100 GHz frequency band. The goal is to address the challenges faced [...] Read more.
This text proposes a Vivaldi structure array antenna, using a power divider structure. The composition includes an antenna array with four antennas, suitable for a wideband array structure antenna in the 100 GHz frequency band. The goal is to address the challenges faced by monolithic systems in modern wireless communications, particularly the issue of the inapplicability of antennas on silicon substrates. The Vivaldi antenna was chosen for its wide bandwidth, high efficiency, and stable radiation pattern. It combines the characteristics of a wide scanning angle and ultra-wide bandwidth. Through integration with CMOS technology, the developed antenna achieved a bandwidth of 85.47–102.40 GHz. The peak gain reached −4 dBi, corresponding to a bandwidth of 17.7%. And the antenna volume was only 1.2 mm × 1.2 mm, demonstrating its immense potential in high-frequency wireless applications. Full article
Show Figures

Figure 1

31 pages, 4597 KiB  
Review
Emerging Industrial Internet of Things Open-Source Platforms and Applications in Diverse Sectors
by Eyuel Debebe Ayele, Stylianos Gavriel, Javier Ferreira Gonzalez, Wouter B. Teeuw, Panayiotis Philimis and Ghayoor Gillani
Telecom 2024, 5(2), 369-399; https://doi.org/10.3390/telecom5020019 - 14 May 2024
Viewed by 590
Abstract
Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also [...] Read more.
Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also provides transformative solutions for various sectors. This research looks into open-source IIoT and edge platforms that are applicable to a range of applications with the aim of finding and developing high-potential solutions. It highlights the effect of open-source IIoT and edge computing platforms on traditional IIoT applications, showing how these platforms make development and deployment processes easier. Popular open-source IIoT platforms include DeviceHive and Thingsboard, while EdgeX Foundry is a key platform for edge computing, allowing IIoT applications to be deployed closer to data sources, thus reducing latency and conserving bandwidth. This study seeks to identify potential future domains for the implementation of IIoT solutions using these open-source platforms. Additionally, each sector is evaluated based on various criteria, such as development requirement analyses, market demand projections, the examination of leading companies and emerging startups in each domain, and the application of the International Patent Classification (IPC) scheme for in-depth sector analysis. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data)
Show Figures

Figure 1

22 pages, 5052 KiB  
Article
Low-Cost, Open-Source, Experimental Setup Communication Platform for Emergencies, Based on SD-WAN Technology
by Vasileios Cheimaras, Spyridon Papagiakoumos, Nikolaos Peladarinos, Athanasios Trigkas, Panagiotis Papageorgas, Dimitrios D. Piromalis and Radu A. Munteanu
Telecom 2024, 5(2), 347-368; https://doi.org/10.3390/telecom5020018 - 2 May 2024
Viewed by 694
Abstract
The rapid advancement of communication technologies underscores the urgent need for robust and adaptable emergency communication systems (ECSs), particularly crucial during crises and natural disasters. Although network-based ECSs have been extensively studied, integrating open-source technologies, such as software-defined wide area networks (SD-WAN) with [...] Read more.
The rapid advancement of communication technologies underscores the urgent need for robust and adaptable emergency communication systems (ECSs), particularly crucial during crises and natural disasters. Although network-based ECSs have been extensively studied, integrating open-source technologies, such as software-defined wide area networks (SD-WAN) with private long-term evolution (LTE) base stations, is a relatively unexplored domain. This study endeavors to fill this gap by introducing an experimental ECS platform that utilizes a hybrid network, incorporating a VoIP network to enhance open-source and on-premises communications in targeted areas. Our hypothesis posits that a hybrid network architecture, combining SD-WAN and private LTE, can substantially improve the reliability and efficiency of ECSs. Our findings, supported by the open-source OMNeT++ simulator, illuminate the enhanced communication reliability of the network. Moreover, the proposed platform, characterized by autonomous wireless 4G/LTE base stations and an Asterisk VoIP server, demonstrates improved quality of service (QoS) and quality of experience (QoE), with minimal data loss. This research not only has immediate practical applications but also bears significant implications for the development of cost-effective, open-source communication networks, optimized for emergencies, critical infrastructure, and remote areas. Full article
Show Figures

Figure 1

14 pages, 1504 KiB  
Article
Feature-Selection-Based DDoS Attack Detection Using AI Algorithms
by Muhammad Saibtain Raza, Mohammad Nowsin Amin Sheikh, I-Shyan Hwang and Mohammad Syuhaimi Ab-Rahman
Telecom 2024, 5(2), 333-346; https://doi.org/10.3390/telecom5020017 - 17 Apr 2024
Viewed by 841
Abstract
SDN has the ability to transform network design by providing increased versatility and effective regulation. Its programmable centralized controller gives network administration employees more authority, allowing for more seamless supervision. However, centralization makes it vulnerable to a variety of attack vectors, with distributed [...] Read more.
SDN has the ability to transform network design by providing increased versatility and effective regulation. Its programmable centralized controller gives network administration employees more authority, allowing for more seamless supervision. However, centralization makes it vulnerable to a variety of attack vectors, with distributed denial of service (DDoS) attacks posing a serious concern. Feature selection-based Machine Learning (ML) techniques are more effective than traditional signature-based Intrusion Detection Systems (IDS) at identifying new threats in the context of defending against distributed denial of service (DDoS) attacks. In this study, NGBoost is compared with four additional machine learning (ML) algorithms: convolutional neural network (CNN), Stochastic Gradient Descent (SGD), Decision Tree, and Random Forest, in order to assess the effectiveness of DDoS detection on the CICDDoS2019 dataset. It focuses on important measures such as F1 score, recall, accuracy, and precision. We have examined NeTBIOS, a layer-7 attack, and SYN, a layer-4 attack, in our paper. Our investigation shows that Natural Gradient Boosting and Convolutional Neural Networks, in particular, show promise with tabular data categorization. In conclusion, we go through specific study results on protecting against attacks using DDoS. These experimental findings offer a framework for making decisions. Full article
Show Figures

Figure 1

21 pages, 9358 KiB  
Article
Simple Compact UWB Vivaldi Antenna Arrays for Breast Cancer Detection
by Sahar Saleh, Tale Saeidi and Nick Timmons
Telecom 2024, 5(2), 312-332; https://doi.org/10.3390/telecom5020016 - 8 Apr 2024
Viewed by 668
Abstract
In this study, at ultra-wideband (UWB) frequency band (3.1–10.6 GHz), we propose the use of compact 2:1 and 3:1 nonuniform transmission line Wilkinson power dividers (NTL WPDs) as feeding networks for simple 2 × 1 linear UWB Vivaldi tapered and nonuniform slot antenna [...] Read more.
In this study, at ultra-wideband (UWB) frequency band (3.1–10.6 GHz), we propose the use of compact 2:1 and 3:1 nonuniform transmission line Wilkinson power dividers (NTL WPDs) as feeding networks for simple 2 × 1 linear UWB Vivaldi tapered and nonuniform slot antenna (VTSA and VNSA) arrays. The 2:1 and 3:1 tapered transmission line (TTL) WPDs are designed and tested in this work as benchmarks for NTL WPDs. The VTSA array provides measured S11 < −10.28 dB at 2.42–11.52 GHz, with a maximum gain of 8.61 dBi, which is 24.39% higher than the single element. Using the VNSA array, we achieve 52% compactness and 6.76% bandwidth enhancement, with good measured results of S11 < −10.2 dB at 3.24–13 GHz and 15.11% improved gain (8.14 dBi) compared to the VNSA single element. The findings show that the NTL and Vivaldi nonuniform slot profile antenna (VNSPA) theories are successful at reducing the size of the UWB WPD and VTSA without sacrificing performance. They also emphasize the Vivaldi antenna’s compatibility with other circuits. These compact arrays are ideal for high-resolution medical applications like breast cancer detection (BCD) because of their high gain, wide bandwidth, directive stable radiation patterns, and low specific absorption rate (SAR). A simple BCD simulation scenario is addressed in this work. Detailed parametric studies are performed on the two arrays for impedance-matching enhancement. The computer simulation technology (CST) software is used for the simulation. Hardware measurement results prove the validity of the proposed arrays. Full article
Show Figures

Figure 1

16 pages, 4929 KiB  
Article
Horn Antenna on Chip Operating at 180 GHz Using the SiGe CMOS Process
by Ming-An Chung, Zi-Yu Huang and Yu-Hsun Chen
Telecom 2024, 5(2), 296-311; https://doi.org/10.3390/telecom5020015 - 8 Apr 2024
Viewed by 601
Abstract
This article proposes a chip antenna on millimeter-Waves. This antenna combined with TSMC 180 nm SiGe CMOS technology has the advantage of being small in size and is suitable for wireless communications. The multilayer architecture Horn antenna implemented on M4–M6 can meet both [...] Read more.
This article proposes a chip antenna on millimeter-Waves. This antenna combined with TSMC 180 nm SiGe CMOS technology has the advantage of being small in size and is suitable for wireless communications. The multilayer architecture Horn antenna implemented on M4–M6 can meet both process reliability specifications and radiation performance. The results of the simulation show that the maximum gain is −4.2 dBi. The return loss measurement results are almost consistent with the simulation results, and the bandwidth range is 177.4–183 GHz. This article first describes the antenna production process and measurement results, analyses the impact of the parameters on the antenna, and further compares it with other designs. The excellence of this article is that it proposes a design that solves the problem of large millimeter wave loss and successfully reduces the area. At the same time, this article can contribute to readers’ future optimization and continued research directions, and at the same time contribute simulation and measurement trends to let readers understand the stability of CMOS chip antenna simulation and measurement. Full article
Show Figures

Figure 1

16 pages, 724 KiB  
Article
Optimization of Signal Detection Using Deep CNN in Ultra-Massive MIMO
by Chittapon Keawin, Apinya Innok and Peerapong Uthansakul
Telecom 2024, 5(2), 280-295; https://doi.org/10.3390/telecom5020014 - 29 Mar 2024
Viewed by 613
Abstract
This paper addresses the evolving landscape of communication technology, emphasizing the pivotal role of 5G and the emerging 6G networks in accommodating the increasing demand for high-speed and accurate data transmission. We delve into the advancements in 5G technology, particularly the implementation of [...] Read more.
This paper addresses the evolving landscape of communication technology, emphasizing the pivotal role of 5G and the emerging 6G networks in accommodating the increasing demand for high-speed and accurate data transmission. We delve into the advancements in 5G technology, particularly the implementation of millimeter wave (mmWave) frequencies ranging from 30 to 300 GHz. These advancements are instrumental in enhancing applications requiring massive data transmission and reception, facilitated by massive MIMO (multiple input multiple output) systems. Looking towards the future, this paper forecasts the necessity for faster data transmission technologies, shifting the focus toward the development of 6G networks. These future networks are projected to employ ultra-massive MIMO systems in the terahertz band, operating within 0.1–10 THz frequency ranges. A significant part of our research is dedicated to exploring advanced signal detection techniques, helping to mitigate the impact of interference and improve accuracy in data transmission and enabling more efficient communication, even in environments with high levels of noise, and including zero forcing (ZF) and minimum mean square error (MMSE) methods, which form the cornerstone of our proposed approach. Additionally, signal detection contributes to the development of new communication technologies such as 5G and 6G, which require a high data transmission efficiency and rapid response speeds. The core contribution of this study lies in the application of deep learning to signal detection in ultra-massive MIMO systems, a critical component of 6G technology. We compare this approach with existing ELMx-based machine learning methods, focusing on algorithmic efficiency and computational performance. Our comparative analysis included the regularized extreme learning machine (RELM) and the outlier robust extreme learning machine (ORELM), juxtaposed with ZF and MMSE methods. Simulation results indicated the superiority of our convolutional neural network for signal detection (CNN-SD) over the traditional ELMx-based, ZF, and MMSE methods, particularly in terms of channel capacity and bit error rate. Furthermore, we demonstrate the computational efficiency and reduced complexity of the CNN-SD method, underscoring its suitability for future expansive MIMO systems. Full article
Show Figures

Figure 1

Previous Issue
Back to TopTop